GUYE Maxime

maxime.guye@ap-hm.fr
Phone : +33491388464

CNS

Professor at AMU, MD, PhD

Director of the Centre for Magnetic Resonance in Biology and Medicine (CRMBM) at Aix-Marseille University (AMU) and director of the medical site of CRMBM at the University Hospital in Marseille, France.

Lead PI and coordinator of the “7T Aix-Marseille Initiative” project around the whole-body 7T MRI scanner hosted and operated by CRMBM.

Medical Doctor (MD)

Professor (MD, PhD)

Detailed Activities

Maxime Guye, M.D., Ph.D., is a Neurologist, Professor of Biophysics at the School of Medicine, Aix-Marseille University (AMU), and in the Medical Imaging Department of the Marseille University Hospital. He is director of the Centre for Magnetic Resonance in Biology and Medicine (CRMBM). After a fellowship in the UCL Epilepsy Imaging Group (London, UK), he started a research activity on epilepsy imaging using multimodal MRI and electrophysiology in Marseille in 2002. Since 2014 he is leading the 7T MRI facility in Marseille and is particularly involved in clinical research and applications of 7T MRI in neurological diseases.

He is actively involved in the MRI community at national and international level. He was elected to the ISMRM High Field Study Group committee and was a member of the ISMRM program committee. He has been elected President of the French Society for Magnetic Resonance in Biology & Medicine and a member of the scientific committee of the French Society of Radiology. He is also a member of the scientific committee of the French Society of Clinical Neurophysiology and of the French League Against Epilepsy.
Maxime has published over 190 peer-reviewed papers in the field of MRI and Neurology.
His research interests are: Ultra-high field MRI; combining and comparing multimodal MRI methods (fMRI, dMRI, MRSI, 23Na-MRI) with electrophysiological recordings ((ic)EEG, EEG/fMRI); and brain connectivity.

Keywords

  • Brain Connectivity
  • Ultra-high field MRI

Research Projects

Publications :

180164 GUYE 1 harvard-cite-them-right-no-et-al 50 date desc year 1838 https://crmbm.univ-amu.fr/wp-content/plugins/zotpress/
%7B%22status%22%3A%22success%22%2C%22updateneeded%22%3Afalse%2C%22instance%22%3Afalse%2C%22meta%22%3A%7B%22request_last%22%3A200%2C%22request_next%22%3A50%2C%22used_cache%22%3Atrue%7D%2C%22data%22%3A%5B%7B%22key%22%3A%22IRDNCDL2%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Gauer%20et%20al.%22%2C%22parsedDate%22%3A%222025-11-05%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BGauer%2C%20L.%2C%20Haast%2C%20R.A.M.%2C%20Azilinon%2C%20M.%2C%20El%20Mendili%2C%20M.M.%2C%20Makhalova%2C%20J.%2C%20Dary%2C%20H.%2C%20Dinkelacker%2C%20V.%2C%20Ridley%2C%20B.%2C%20Ranjeva%2C%20J.-P.%2C%20Zaaraoui%2C%20W.%2C%20Bartolomei%2C%20F.%20and%20Guye%2C%20M.%20%282025%29%20%26%23x201C%3BInvestigating%20sodium%20homeostasis%20of%20structural%20brain%20hubs%20in%20focal%20epilepsy%20using%207%20T%20MRI%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BBrain%3A%20A%20Journal%20of%20Neurology%26lt%3B%5C%2Fi%26gt%3B%2C%20p.%20awaf409.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1093%5C%2Fbrain%5C%2Fawaf409%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1093%5C%2Fbrain%5C%2Fawaf409%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Investigating%20sodium%20homeostasis%20of%20structural%20brain%20hubs%20in%20focal%20epilepsy%20using%207%20T%20MRI%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lucas%22%2C%22lastName%22%3A%22Gauer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Roy%20A.%20M.%22%2C%22lastName%22%3A%22Haast%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mikhael%22%2C%22lastName%22%3A%22Azilinon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mohamed%20Mounir%22%2C%22lastName%22%3A%22El%20Mendili%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Julia%22%2C%22lastName%22%3A%22Makhalova%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hugo%22%2C%22lastName%22%3A%22Dary%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Vera%22%2C%22lastName%22%3A%22Dinkelacker%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ben%22%2C%22lastName%22%3A%22Ridley%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Wafaa%22%2C%22lastName%22%3A%22Zaaraoui%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabrice%22%2C%22lastName%22%3A%22Bartolomei%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%5D%2C%22abstractNote%22%3A%22Besides%20their%20crucial%20role%20in%20cerebral%20connectivity%2C%20brain%20hubs%20are%20regions%20vulnerable%20to%20the%20energy%20deficit%20associated%20with%20various%20brain%20disorders.%20Changes%20in%20sodium%20homeostasis%20of%20cortical%20regions%20have%20been%20observed%20in%20focal%20epilepsy%20and%20may%20reflect%20energy%20failure.%20We%20investigated%20whether%20nodal%20structural%20connectivity%20is%20differently%20affected%20within%20the%20hub%20and%20non-hub%20regions%20by%20ionic%20perturbations%20associated%20with%20focal%20epilepsy.%20Our%20hypothesis%20was%20that%20the%20metabolic%20demands%20of%20hub%20regions%20may%20be%20associated%20with%20a%20distinct%20ionic%20profile%20detectable%20by%20sodium%20MRI%20and%20that%20this%20profile%20is%20altered%20in%20focal%20epilepsy.%20We%20included%2039%20patients%20with%20drug-resistant%20focal%20epilepsy%20and%2021%20age-%20and%20gender-matched%20healthy%20controls.%20Anatomical%2C%20diffusion-weighted%2C%20and%20sodium%20imaging%20was%20performed%20using%20a%207%20Tesla%20MRI%20scanner.%20Patients%20underwent%20pre-surgical%20work-up%2C%20including%20stereo-electroencephalographic%20recordings%20for%20defining%20the%20epileptogenic%20regions.%20Anatomical%20parcellation%20and%20multimodal%20coregistration%20allowed%20the%20use%20of%20parcels%20as%20nodes%20of%20whole-brain%20structural%20connectomes%2C%20linking%20structural%20connectivity%20measures%20to%20epileptogenicity%20and%20sodium%20parameters.%20Sodium%20parameters%20in%20patients%20were%20z-scored%20concerning%20homologous%20parcels%20in%20controls%20to%20allow%20comparison%20across%20regions%20of%20interest.%20Hub%20regions%20had%20higher%20total%20sodium%20concentration%20%28TSC%29%20than%20non-hub%20regions%20in%20both%20patients%20and%20controls%2C%20and%20this%20difference%20was%20not%20observed%20for%20sodium%20signal%20fraction%20%28f%2C%20a%20proxy%20of%20intracellular%20sodium%20homeostasis%29.%20Compared%20to%20controls%2C%20patients%20showed%20increased%20TSC%20in%20both%20epileptogenic%20and%20non-epileptogenic%20zones%2C%20and%20this%20increase%20in%20TSC%20was%20consistent%20in%20both%20hub%20and%20non-hub%20regions.%20On%20the%20contrary%2C%20f%20was%20increased%20only%20within%20the%20epileptogenic%20zones%20and%20was%20not%20affected%20by%20the%20hubness%20of%20a%20region.%20Our%20results%20also%20confirm%20the%20whole%20brain%20increase%20in%20TSC%20and%20the%20local%20increase%20of%20the%20f%20value%20within%20epileptogenic%20zones%20previously%20observed%20in%20focal%20epilepsy%20patients.%20Therefore%2C%20we%20propose%20that%20sodium%20imaging%20can%20probe%20distinct%20tissue%20properties%3A%20TSC%20appears%20sensitive%20to%20microstructural%20alterations%2C%20while%20f%20could%20reflect%20homeostatic%20disruptions%20specific%20to%20epileptogenic%20regions.%22%2C%22date%22%3A%222025-11-05%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1093%5C%2Fbrain%5C%2Fawaf409%22%2C%22ISSN%22%3A%221460-2156%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22KJQH9V8M%22%2C%22UP3H3ICX%22%2C%22HVJZKIZG%22%2C%22P66W67T8%22%2C%22F2AGIUQU%22%2C%22XTA6KS7L%22%2C%22FBQIKF54%22%2C%229RMECNPE%22%5D%2C%22dateModified%22%3A%222025-11-12T13%3A35%3A34Z%22%7D%7D%2C%7B%22key%22%3A%22C2999DIC%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Stellmann%20et%20al.%22%2C%22parsedDate%22%3A%222025-11-05%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BStellmann%2C%20J.-P.%2C%20Maarouf%2C%20A.%2C%20Nicolescu%2C%20M.%2C%20Boutiere%2C%20C.%2C%20Rico%2C%20A.%2C%20Zaaraoui%2C%20W.%2C%20Guye%2C%20M.%2C%20Pelletier%2C%20J.%2C%20Ranjeva%2C%20J.-P.%20and%20Audoin%2C%20B.%20%282025%29%20%26%23x201C%3BEarly%20structural%20hub%20disruption%20leads%20to%20premature%20functional%20adaption%20in%20multiple%20sclerosis%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BBrain%20Structure%20%26amp%3B%20Function%26lt%3B%5C%2Fi%26gt%3B%2C%20230%289%29%2C%20p.%20172.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs00429-025-03023-2%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs00429-025-03023-2%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Early%20structural%20hub%20disruption%20leads%20to%20premature%20functional%20adaption%20in%20multiple%20sclerosis%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan-Patrick%22%2C%22lastName%22%3A%22Stellmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Adil%22%2C%22lastName%22%3A%22Maarouf%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mihaela%22%2C%22lastName%22%3A%22Nicolescu%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Cl%5Cu00e9mence%22%2C%22lastName%22%3A%22Boutiere%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Audrey%22%2C%22lastName%22%3A%22Rico%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Wafaa%22%2C%22lastName%22%3A%22Zaaraoui%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean%22%2C%22lastName%22%3A%22Pelletier%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Phillipe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Bertrand%22%2C%22lastName%22%3A%22Audoin%22%7D%5D%2C%22abstractNote%22%3A%22In%20Multiple%20Sclerosis%2C%20inflammation%20and%20neurodegeneration%20disrupt%20structural%20and%20functional%20brain%20networks.%20While%20the%20association%20between%20structural%20connectivity%20and%20disability%20is%20rather%20clear%2C%20functional%20connectivity%20changes%20are%20not%20yet%20characterised%20as%20a%20physiological%20response%20to%20the%20disease%2C%20as%20functionally%20meaningful%20adaptation%20or%20as%20a%20deceptive%20response.%20We%20explored%20the%20topology%20of%20brain%20networks%20of%2065%20Multiple%20Sclerosis%20patients%20over%20up%20to%20seven%20years%20in%20comparison%20to%2059%20controls.%20Connectomes%20based%20on%20probabilistic%20tractography%20from%20diffusion%20weighted%20imaging%20and%20resting-state%20MRI%2C%20were%20analysed%20with%20graph%20theory.%20The%20hub%20disruption%20index%20estimated%20connectivity%20perturbation%20in%20relation%20to%20the%20network%20hierarchy.%20In%20controls%2C%20we%20observed%20a%20transient%20increase%20in%20functional%20hub%20connectivity%20in%20the%205th%20and%206th%20age%20decade%20as%20a%20response%20to%20a%20subtle%20diffuse%20loss%20of%20structural%20connectivity%2C%20before%20structural%20and%20functional%20connectomes%20show%20a%20pronounced%20loss%20of%20hub%20connectivity.%20In%20Multiple%20Sclerosis%2C%20structural%20hub%20disruption%20was%20present%20from%20the%20disease%20onset%20while%20the%20transient%20upregulation%20of%20functional%20hub%20connectivity%20in%20the%20middle%20age%20was%20lacking.%20Patients%20seem%20to%20transition%20directly%20into%20an%20exhausted%20hub%20connectivity%20configuration.%20However%2C%20we%20observed%20the%20transient%20functional%20reorganisation%20of%20hubs%20in%20the%20first%20years%20after%20disease%20onset.%20Multiple%20Sclerosis%20patients%20present%20a%20probable%20physiological%20response%20to%20structural%20connectivity%20loss%20very%20early%20in%20the%20disease%2C%20potentially%20leading%20to%20an%20accelerated%20hub%20overload%20with%20accelerated%20neurodegeneration.%20The%20onset%20of%20chronic%20progression%20in%20the%205th%20age%20decade%20might%20be%20partially%20driven%20by%20the%20absence%20of%20the%20physiological%20increased%20hub%20connectivity%20observed%20in%20healthy%20individuals.%22%2C%22date%22%3A%222025-11-05%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1007%5C%2Fs00429-025-03023-2%22%2C%22ISSN%22%3A%221863-2661%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22KJQH9V8M%22%2C%22UP3H3ICX%22%2C%22B4EWFM7E%22%2C%229L2KHJ5X%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-11-06T15%3A36%3A25Z%22%7D%7D%2C%7B%22key%22%3A%22T9ZKI5F9%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Martin%20et%20al.%22%2C%22parsedDate%22%3A%222025-09-08%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BMartin%2C%20S.%2C%20Trabelsi%2C%20A.%2C%20Guye%2C%20M.%2C%20Dubois%2C%20M.%2C%20Abdeddaim%2C%20R.%2C%20Bendahan%2C%20D.%20and%20Andr%26%23xE9%3B%2C%20R.%20%282025%29%20%26%23x201C%3BOptimized%20reconstruction%20of%20undersampled%20Dixon%20sequences%20using%20new%20memory-efficient%20unrolled%20deep%20neural%20networks%3A%20HalfVarNet%20and%20HalfDIRCN%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BMagnetic%20Resonance%20in%20Medicine%26lt%3B%5C%2Fi%26gt%3B%20%5BPreprint%5D.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fmrm.70070%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fmrm.70070%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Optimized%20reconstruction%20of%20undersampled%20Dixon%20sequences%20using%20new%20memory-efficient%20unrolled%20deep%20neural%20networks%3A%20HalfVarNet%20and%20HalfDIRCN%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sandra%22%2C%22lastName%22%3A%22Martin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Amira%22%2C%22lastName%22%3A%22Trabelsi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marc%22%2C%22lastName%22%3A%22Dubois%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Redha%22%2C%22lastName%22%3A%22Abdeddaim%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Bendahan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22R%5Cu00e9mi%22%2C%22lastName%22%3A%22Andr%5Cu00e9%22%7D%5D%2C%22abstractNote%22%3A%22PURPOSE%3A%20Fat%20fraction%20%28FF%29%20quantification%20in%20individual%20muscles%20using%20quantitative%20MRI%20is%20of%20major%20importance%20for%20monitoring%20disease%20progression%20and%20assessing%20disease%20severity%20in%20neuromuscular%20diseases.%20Undersampling%20of%20MRI%20acquisitions%20is%20commonly%20used%20to%20reduce%20scanning%20time.%20The%20present%20paper%20introduces%20novel%20unrolled%20neural%20networks%20for%20the%20reconstruction%20of%20undersampled%20MRI%20acquisitions.%20These%20networks%20are%20designed%20with%20the%20aim%20of%20maintaining%20accurate%20FF%20quantification%20while%20reducing%20reconstruction%20time%20and%20memory%20usage.%5CnMETHODS%3A%20The%20proposed%20approach%20relies%20on%20a%20combination%20of%20a%20simplified%20architecture%20%28Half%20U-Net%29%20with%20unrolled%20networks%20that%20achieved%20high%20performance%20in%20the%20well-known%20FastMRI%20challenge%20%28variational%20network%20%5BVarNet%5D%20and%20densely%20interconnected%20residual%20cascading%20network%20%5BDIRCN%5D%29.%20The%20algorithms%20were%20trained%20and%20evaluated%20using%203D%20MRI%20Dixon%20acquisitions%20of%20the%20thigh%20from%20controls%20and%20patients%20with%20neuromuscular%20diseases.%20The%20study%20was%20performed%20by%20applying%20a%20retrospective%20undersampling%20with%20acceleration%20factors%20of%204%20and%208.%20Reconstructed%20images%20were%20used%20to%20computed%20FF%20maps.%5CnRESULTS%3A%20Results%20disclose%20that%20the%20novel%20unrolled%20neural%20networks%20were%20able%20to%20maintain%20reconstruction%2C%20biomarker%20assessment%2C%20and%20segmentation%20quality%20while%20reducing%20memory%20usage%20by%2024%25%20to%2016%25%20and%20reducing%20reconstruction%20time%20from%2021%25%20to%2017%25.%20Using%20an%20acceleration%20factor%20of%208%2C%20the%20proposed%20algorithms%2C%20HalfVarNet%20and%20HalfDIRCN%2C%20achieved%20structural%20similarity%20index%20%28SSIM%29%20scores%20of%2093.76%5Cu2009%5Cu00b1%5Cu20090.38%20and%2094.95%5Cu2009%5Cu00b1%5Cu20090.32%2C%20mean%20squared%20error%20%28MSE%29%20values%20of%2012.76%5Cu2009%5Cu00b1%5Cu20091.08%5Cu2009%5Cu00d7%5Cu200910-2%20and%2010.25%5Cu2009%5Cu00b1%5Cu20090.87%20%5Cu00d7%5Cu200910-2%2C%20and%20a%20relative%20FF%20quadratic%20error%20of%200.23%5Cu2009%5Cu00b1%5Cu20090.02%25%20and%200.17%5Cu2009%5Cu00b1%5Cu20090.02%25%2C%20respectively.%5CnCONCLUSION%3A%20The%20proposed%20method%20enables%20time%20and%20memory-efficient%20reconstruction%20of%20undersampled%203D%20MRI%20data%2C%20supporting%20its%20potential%20for%20clinical%20application.%22%2C%22date%22%3A%222025-09-08%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1002%5C%2Fmrm.70070%22%2C%22ISSN%22%3A%221522-2594%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22NW6SZQBR%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-11-19T13%3A59%3A34Z%22%7D%7D%2C%7B%22key%22%3A%22WE66JXHA%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Nimje%20et%20al.%22%2C%22parsedDate%22%3A%222025-08%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BNimje%2C%20S.%2C%20Arti%26%23xE8%3Bres%2C%20T.%2C%20Guye%2C%20M.%20and%20de%20Rochefort%2C%20L.%20%282025%29%20%26%23x201C%3BInsights%20on%20Scan-Specific%20Deep-Learning%20Strategies%20for%20Brain%20MRI%20Parallel%20Imaging%20Reconstruction%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BNMR%20in%20biomedicine%26lt%3B%5C%2Fi%26gt%3B%2C%2038%288%29%2C%20p.%20e70079.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fnbm.70079%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fnbm.70079%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Insights%20on%20Scan-Specific%20Deep-Learning%20Strategies%20for%20Brain%20MRI%20Parallel%20Imaging%20Reconstruction%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Swetali%22%2C%22lastName%22%3A%22Nimje%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thierry%22%2C%22lastName%22%3A%22Arti%5Cu00e8res%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ludovic%22%2C%22lastName%22%3A%22de%20Rochefort%22%7D%5D%2C%22abstractNote%22%3A%22Scan-specific%20deep%20learning%20strategies%20have%20been%20proposed%20for%20parallel%20imaging%20reconstruction%20in%20which%20auto-calibrated%20signals%20%28ACS%29%20are%20used%20for%20training.%20Here%2C%20we%20introduce%20methods%20to%20objectively%20optimize%20architecture%20and%20training%20details.%20In%20addition%2C%20we%20introduce%20a%20new%20metric%20to%20better%20characterize%20the%20quality%20of%20the%20reconstructed%20images.%20Various%20brain%20MRI%20situations%20are%20considered.%20The%20evaluated%20models%20encompass%20single-layer%20and%20three-layer%20residual%20CNN%20architectures%20with%20real%20and%20complex%20convolutions.%20Hyperparameters%20such%20as%20the%20level%20of%20linearity%20in%20leaky%20activation%20functions%2C%20loss%20function%2C%20kernel%20sizes%20and%20depths%20are%20optimized%20using%20grid-search%20with%20K-fold%20cross%20validation.%20The%20performances%20regarding%20ACS%20reference%20size%20and%20mode%20are%20also%20evaluated.%20An%20innovative%20COrrelation-Based%20Residual%20Artifact%20Index%20%28COBRAI%29%20quantifying%20the%20level%20of%20structured%20residual%20artifacts%20is%20proposed.%20Qualitative%20and%20quantitative%20comparisons%20are%20performed%20both%20on%20the%20FastMRI%20and%20in-house%20multi-contrasts%202D%20data.%20The%20proposed%20objective%20grid-search%20strategy%20based%20on%20ACS%20successfully%20provided%20optimized%20hyperparameters%2C%20retrospectively%20validated%20by%20enhanced%20image%20quality%20metrics.%20Notably%2C%20it%20is%20shown%20that%20nonlinearities%20produce%20structured%20residual%20artifacts%2C%20and%20that%2C%20among%20the%20models%20tested%2C%20a%20three-layer%20residual%20linear%20CNN%20with%20complex%20implementation%20and%20a%20reduced%20number%20of%20parameters%20is%20more%20robust%2C%20particularly%20providing%20less%20structured%20artifacts%20with%20less%20training%20data%2C%20leading%20to%20larger%20acceleration%20rates.%20Deep-learning%20MRI%20parallel%20image%20reconstruction%20in%20the%20scan-specific%20approach%20can%20be%20optimized%20using%20grid-search%20with%20K-fold%20cross%20validation.%20It%20was%20successfully%20applied%20in%20various%202D%20brain%20MRI%20situations.%20The%20quantification%20of%20structured%20residual%20artifacts%20with%20COBRAI%20is%20a%20useful%20complementary%20characterization%20to%20state-of-the-art%20metrics%2C%20and%20it%20can%20be%20used%20to%20drive%20model%20selection.%22%2C%22date%22%3A%222025-08%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1002%5C%2Fnbm.70079%22%2C%22ISSN%22%3A%221099-1492%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22DNKN89WD%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-11-19T13%3A59%3A28Z%22%7D%7D%2C%7B%22key%22%3A%22ZFVS4C2I%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Mostame%20et%20al.%22%2C%22parsedDate%22%3A%222025-06-13%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BMostame%2C%20P.%2C%20Wirsich%2C%20J.%2C%20Alderson%2C%20T.%2C%20Ridley%2C%20B.%2C%20Giraud%2C%20A.-L.%2C%20Carmichael%2C%20D.W.%2C%20Vulliemoz%2C%20S.%2C%20Guye%2C%20M.%2C%20Lemieux%2C%20L.%20and%20Sadaghiani%2C%20S.%20%282025%29%20%26%23x201C%3BA%20multiplex%20of%20connectome%20trajectories%20enables%20several%20connectivity%20patterns%20in%20parallel%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BeLife%26lt%3B%5C%2Fi%26gt%3B%2C%2013%2C%20p.%20RP98777.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.7554%5C%2FeLife.98777%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.7554%5C%2FeLife.98777%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22A%20multiplex%20of%20connectome%20trajectories%20enables%20several%20connectivity%20patterns%20in%20parallel%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Parham%22%2C%22lastName%22%3A%22Mostame%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jonathan%22%2C%22lastName%22%3A%22Wirsich%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Alderson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ben%22%2C%22lastName%22%3A%22Ridley%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anne-Lise%22%2C%22lastName%22%3A%22Giraud%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%20W.%22%2C%22lastName%22%3A%22Carmichael%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Serge%22%2C%22lastName%22%3A%22Vulliemoz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Louis%22%2C%22lastName%22%3A%22Lemieux%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sepideh%22%2C%22lastName%22%3A%22Sadaghiani%22%7D%5D%2C%22abstractNote%22%3A%22Complex%20brain%20function%20comprises%20a%20multitude%20of%20neural%20operations%20in%20parallel%20and%20often%20at%20different%20speeds.%20Each%20of%20these%20operations%20is%20carried%20out%20across%20a%20network%20of%20distributed%20brain%20regions.%20How%20multiple%20distributed%20processes%20are%20facilitated%20in%20parallel%20is%20largely%20unknown.%20We%20postulate%20that%20such%20processing%20relies%20on%20a%20multiplex%20of%20dynamic%20network%20patterns%20emerging%20in%20parallel%20but%20from%20different%20functional%20connectivity%20%28FC%29%20timescales.%20Given%20the%20dominance%20of%20inherently%20slow%20fMRI%20in%20network%20science%2C%20it%20is%20unknown%20whether%20the%20brain%20leverages%20such%20multi-timescale%20network%20dynamics.%20We%20studied%20FC%20dynamics%20concurrently%20across%20a%20breadth%20of%20timescales%20%28from%20infraslow%20to%20%5Cu03b3-range%29%20in%20rare%2C%20simultaneously%20recorded%20intracranial%20EEG%20and%20fMRI%20in%20humans%2C%20and%20source-localized%20scalp%20EEG-fMRI%20data%20in%20humans.%20We%20examined%20spatial%20and%20temporal%20convergence%20of%20connectome%20trajectories%20across%20timescales.%20%26%23039%3BSpatial%20convergence%26%23039%3B%20refers%20to%20spatially%20similar%20EEG%20and%20fMRI%20connectome%20patterns%2C%20while%20%26%23039%3Btemporal%20convergence%26%23039%3B%20signifies%20the%20more%20specific%20case%20of%20spatial%20convergence%20at%20corresponding%20timepoints%20in%20EEG%20and%20fMRI.%20We%20observed%20spatial%20convergence%20but%20temporal%20divergence%20across%20FC%20timescales%3B%20connectome%20states%20%28recurrent%20FC%20patterns%29%20with%20partial%20spatial%20similarity%20were%20found%20in%20fMRI%20and%20all%20EEG%20frequency%20bands%2C%20but%20these%20occurred%20asynchronously%20across%20FC%20timescales.%20Our%20findings%20suggest%20that%20hemodynamic%20and%20frequency-specific%20electrophysiological%20signals%2C%20while%20involving%20similar%20large-scale%20networks%2C%20represent%20functionally%20distinct%20connectome%20trajectories%20that%20operate%20at%20different%20FC%20speeds%20and%20in%20parallel.%20This%20multiplex%20is%20poised%20to%20enable%20concurrent%20connectivity%20across%20multiple%20sets%20of%20brain%20regions%20independently.%22%2C%22date%22%3A%222025-06-13%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.7554%5C%2FeLife.98777%22%2C%22ISSN%22%3A%222050-084X%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22HVJZKIZG%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-11-19T13%3A59%3A21Z%22%7D%7D%2C%7B%22key%22%3A%22DNR3BIPC%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Mourre%20et%20al.%22%2C%22parsedDate%22%3A%222025-05-19%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BMourre%2C%20H.%2C%20Makhalova%2C%20J.%2C%20Soncin%2C%20L.%2C%20Garnier%2C%20E.%2C%20Dary%2C%20H.%2C%20Le%20Troter%2C%20A.%2C%20Haast%2C%20R.A.M.%2C%20Testud%2C%20B.%2C%20Arthuis%2C%20M.%2C%20Villalon%2C%20S.M.%2C%20Lagarde%2C%20S.%2C%20Pizzo%2C%20F.%2C%20B%26%23xE9%3Bnar%2C%20C.%2C%20Ranjeva%2C%20J.-P.%2C%20Guye%2C%20M.%20and%20Bartolomei%2C%20F.%20%282025%29%20%26%23x201C%3BNuclei-Specific%20Amygdala%20Enlargement%20Is%20Linked%20to%20Psychiatric%20Comorbidities%20in%20Drug-Resistant%20Focal%20Epilepsy%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BAnnals%20of%20Clinical%20and%20Translational%20Neurology%26lt%3B%5C%2Fi%26gt%3B%20%5BPreprint%5D.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Facn3.70071%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Facn3.70071%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Nuclei-Specific%20Amygdala%20Enlargement%20Is%20Linked%20to%20Psychiatric%20Comorbidities%20in%20Drug-Resistant%20Focal%20Epilepsy%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22H%5Cu00e9l%5Cu00e8ne%22%2C%22lastName%22%3A%22Mourre%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Julia%22%2C%22lastName%22%3A%22Makhalova%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lisa%22%2C%22lastName%22%3A%22Soncin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Elodie%22%2C%22lastName%22%3A%22Garnier%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hugo%22%2C%22lastName%22%3A%22Dary%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Arnaud%22%2C%22lastName%22%3A%22Le%20Troter%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Roy%20A.%20M.%22%2C%22lastName%22%3A%22Haast%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Benoit%22%2C%22lastName%22%3A%22Testud%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marie%22%2C%22lastName%22%3A%22Arthuis%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Samuel%20Medina%22%2C%22lastName%22%3A%22Villalon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stanislas%22%2C%22lastName%22%3A%22Lagarde%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Francesca%22%2C%22lastName%22%3A%22Pizzo%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christian%22%2C%22lastName%22%3A%22B%5Cu00e9nar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabrice%22%2C%22lastName%22%3A%22Bartolomei%22%7D%5D%2C%22abstractNote%22%3A%22OBJECTIVE%3A%20Amygdala%20enlargement%20has%20been%20the%20subject%20of%20controversial%20studies%20regarding%20its%20significance%20in%20terms%20of%20pathogenicity%20both%20in%20epilepsy%20and%20in%20psychiatric%20comorbidities%20such%20as%20anxiety%2C%20depression%2C%20and%20post-traumatic%20stress%20disorder.%20However%2C%20no%20causal%20link%20has%20been%20established%20in%20either%20direction%2C%20and%20the%20role%20of%20distinct%20amygdala%20nuclei%20remains%20unknown.%20We%20investigated%20volumetric%20changes%20of%20the%20amygdala%20and%20its%20nine%20main%20nuclei%20and%20their%20associations%20with%20psychiatric%20comorbidities%20in%20patients%20with%20drug-resistant%20focal%20epilepsy.%5CnMETHODS%3A%20Eighty-seven%20adult%20patients%20with%20drug-resistant%20focal%20epilepsy%2C%20available%207%5Cu2009T%20MRI%2C%20and%20completed%20standardized%20psychiatric%20assessments%20were%20included.%20Whole%20amygdala%20and%20nuclei%20volumes%20were%20quantified%20and%20compared%20to%20healthy%20controls.%20Correlations%20between%20the%20amygdala%20or%20nuclei%20volumes%20and%20psychiatric%20scores%20were%20analyzed%2C%20as%20well%20as%20the%20prevalence%20and%20severity%20of%20each%20comorbidity%20depending%20on%20the%20presence%20of%20enlargement.%5CnRESULTS%3A%20Amygdala%20enlargement%20was%20present%20in%2041%25%20of%20patients%2C%20with%20bilateral%20enlargement%20observed%20in%2030%25%20of%20these%20cases%2C%20while%20atrophy%20was%20noted%20in%202%25.%20Bilateral%20enlargement%20correlated%20with%20higher%20posttraumatic%20stress%20disorder%20and%20depression%20scores.%20Central%20nucleus%20enlargement%20was%20associated%20with%20a%20greater%20prevalence%20of%20depression%20and%20more%20severe%20anxiety.%20Bilateral%20enlargement%20of%20distinct%20nuclei%20in%20the%20basolateral%20group%20was%20linked%20to%20more%20severe%20depression%20or%20posttraumatic%20stress%20disorder.%5CnINTERPRETATION%3A%20These%20findings%20suggest%20that%20bilateral%20amygdala%20enlargement%2C%20particularly%20in%20specific%20nuclei%2C%20may%20serve%20as%20a%20morphological%20marker%20of%20psychiatric%20comorbidities%20in%20epilepsy.%20Further%20research%20is%20needed%20to%20explore%20the%20specific%20roles%20of%20amygdala%20nuclei%20in%20psycho-epileptogenesis.%22%2C%22date%22%3A%222025-05-19%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1002%5C%2Facn3.70071%22%2C%22ISSN%22%3A%222328-9503%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22UP3H3ICX%22%2C%225P5FWCR9%22%2C%22XTA6KS7L%22%2C%22FBQIKF54%22%5D%2C%22dateModified%22%3A%222025-05-27T08%3A14%3A24Z%22%7D%7D%2C%7B%22key%22%3A%22YCW6SA77%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Cotinat%20et%20al.%22%2C%22parsedDate%22%3A%222025-05%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BCotinat%2C%20M.%2C%20Messaoudi%2C%20N.%2C%20Robinet%2C%20E.%2C%20Suissa%2C%20L.%2C%20Doche%2C%20E.%2C%20Guye%2C%20M.%2C%20Audoin%2C%20B.%2C%20Bensoussan%2C%20L.%2C%20Ranjeva%2C%20J.-P.%20and%20Zaaraoui%2C%20W.%20%282025%29%20%26%23x201C%3BDynamics%20of%20Ionic%20and%20Cytotoxic%20Edema%20During%20Acute%20and%20Subacute%20Stages%20of%20Patients%20With%20Ischemic%20Stroke%3A%20Complementarity%20of%2023Na%20MRI%20and%20Diffusion%20MRI%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BNMR%20in%20biomedicine%26lt%3B%5C%2Fi%26gt%3B%2C%2038%285%29%2C%20p.%20e70028.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fnbm.70028%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fnbm.70028%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Dynamics%20of%20Ionic%20and%20Cytotoxic%20Edema%20During%20Acute%20and%20Subacute%20Stages%20of%20Patients%20With%20Ischemic%20Stroke%3A%20Complementarity%20of%2023Na%20MRI%20and%20Diffusion%20MRI%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ma%5Cu00ebva%22%2C%22lastName%22%3A%22Cotinat%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22No%5Cu00eblle%22%2C%22lastName%22%3A%22Messaoudi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Emmanuelle%22%2C%22lastName%22%3A%22Robinet%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Laurent%22%2C%22lastName%22%3A%22Suissa%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Emilie%22%2C%22lastName%22%3A%22Doche%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Bertrand%22%2C%22lastName%22%3A%22Audoin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Laurent%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Wafaa%22%2C%22lastName%22%3A%22Zaaraoui%22%7D%5D%2C%22abstractNote%22%3A%22Cerebral%20imaging%20is%20crucial%20in%20the%20diagnosis%20and%20treatment%20algorithm%20of%20acute%20stroke%20to%20determine%20salvageable%20brain%20tissue.%20While%20diffusion%20MRI%20is%20commonly%20used%20to%20define%20the%20ischemic%20core%2C%20it%20cannot%20reliably%20distinguish%20irreversibly%20damaged%20from%20salvageable%20tissue.%20We%20investigated%20the%20added%20value%20of%2023Na%20MRI%20to%20define%20irreversible%20necrotic%20tissue%20after%20a%20stroke.%20Fifteen%20patients%20with%20acute%20stroke%20involving%20medial%20cerebral%20artery%20occlusion%20were%20longitudinally%20explored%20with%20conventional%20and%2023Na%20MRI%20within%2024%5Cu2009h%2C%2070%5Cu2009h%20following%20stroke%20and%20at%203%5Cu2009months%20to%20characterize%20the%20necrotic%20area.%20Time-courses%20of%20sodium%20accumulations%20were%20observed%20within%20regions%20presenting%20with%20or%20spared%20by%20cytotoxic%5C%2Fionic%20edema%20and%20converting%20or%20not%20to%20necrosis.%20Dynamics%20of%20sodium%20accumulations%20were%20very%20different%20across%20subjects.%20At%20the%20group%20level%2C%20time-courses%20of%20sodium%20signal%20in%20cytotoxic%20edema%20showed%20a%20non-linear%20increase%20with%20an%20upper%20asymptote%20of%2059%5Cu2009%5Cu00b1%5Cu20096%25%25%20relative%20to%20the%20contralateral%20hemisphere.%20Regions%20with%20a%20larger%20early%20increase%20in%2023Na%20signal%20%28ionic%20edema%29%20showed%20a%20non-linear%20accumulation%20during%20the%20first%2070%5Cu2009h%20and%20were%20associated%20with%20subsequent%20necrosis%20at%20month%203.%20Some%20of%20the%20regions%20with%20no%20ionic%20edema%20during%20the%20first%2070%5Cu2009h%20became%20necrotic%20at%20month%203%2C%20showing%20that%20pejorative%20pathophysiological%20processes%20could%20worsen%20after%2070%5Cu2009h%20following%20attack.%20Final%20necrotic%20volume%20was%20well%20predicted%20by%20the%20cytotoxic%20volume%20%28ADC%20decrease%29%20during%20the%20first%2024%5Cu2009h%2C%20and%20by%20the%20volume%20of%20ionic%20edema%20during%20the%20subacute%20period%20%2825-70%5Cu2009h%29%20following%20attack.%20The%20regions%20showing%20ionic%20edema%20showed%20a%20non-linear%20increase%20of%2023Na%20signal%20during%20the%20first%2070%5Cu2009h%2C%20with%20larger%20sodium%20accumulations%20in%20regions%20converting%20to%20necrosis%20at%20month%203.%20It%20may%20be%20of%20interest%20to%20consider%20the%20role%20of%20ionic%20edema%20imaging%20in%20the%2070%5Cu2009h%20after%20stroke%20and%20reperfusion%2C%20with%20a%20view%20to%20better%20understand%20stroke%20pathophysiology.%20Sodium%20MRI%20could%20add%20complementary%20information%20about%20the%20fate%20of%20cell%20necrosis%20within%20low%20ADC%20signal%20regions.%22%2C%22date%22%3A%222025-05%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1002%5C%2Fnbm.70028%22%2C%22ISSN%22%3A%221099-1492%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22UP3H3ICX%22%2C%22P66W67T8%22%2C%226KPLZTET%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-11-19T13%3A59%3A13Z%22%7D%7D%2C%7B%22key%22%3A%22NW8ZZ25N%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Dollomaja%20et%20al.%22%2C%22parsedDate%22%3A%222025-04-11%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BDollomaja%2C%20B.%2C%20Wang%2C%20H.E.%2C%20Guye%2C%20M.%2C%20Makhalova%2C%20J.%2C%20Bartolomei%2C%20F.%20and%20Jirsa%2C%20V.K.%20%282025%29%20%26%23x201C%3BVirtual%20epilepsy%20patient%20cohort%3A%20Generation%20and%20evaluation%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BPLoS%20computational%20biology%26lt%3B%5C%2Fi%26gt%3B%2C%2021%284%29%2C%20p.%20e1012911.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1371%5C%2Fjournal.pcbi.1012911%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1371%5C%2Fjournal.pcbi.1012911%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Virtual%20epilepsy%20patient%20cohort%3A%20Generation%20and%20evaluation%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Borana%22%2C%22lastName%22%3A%22Dollomaja%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Huifang%20E.%22%2C%22lastName%22%3A%22Wang%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Julia%22%2C%22lastName%22%3A%22Makhalova%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabrice%22%2C%22lastName%22%3A%22Bartolomei%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Viktor%20K.%22%2C%22lastName%22%3A%22Jirsa%22%7D%5D%2C%22abstractNote%22%3A%22Epilepsy%20is%20a%20prevalent%20brain%20disorder%2C%20characterized%20by%20sudden%2C%20abnormal%20brain%20activity%2C%20making%20it%20difficult%20to%20live%20with.%20One-third%20of%20people%20with%20epilepsy%20do%20not%20respond%20to%20anti-epileptic%20drugs.%20Drug-resistant%20epilepsy%20is%20treated%20with%20brain%20surgery.%20Successful%20surgical%20treatment%20relies%20on%20identifying%20brain%20regions%20responsible%20for%20seizure%20onset%2C%20known%20as%20epileptogenic%20zones%20%28EZ%29.%20Despite%20various%20methods%20for%20EZ%20estimation%2C%20evaluating%20their%20efficacy%20remains%20challenging%20due%20to%20a%20lack%20of%20ground%20truth%20for%20empirical%20data.%20To%20address%20this%2C%20we%20generated%20and%20evaluated%20a%20cohort%20of%2030%20virtual%20epilepsy%20patients%2C%20using%20patient-specific%20anatomical%20and%20functional%20data%20from%2030%20real%20drug-resistant%20epilepsy%20patients.%20This%20personalized%20modeling%2C%20based%20on%20the%20patient%26%23039%3Bs%20brain%20data%2C%20is%20called%20a%20virtual%20brain%20twin.%20For%20each%20virtual%20patient%2C%20we%20provided%20data%20that%20included%20anatomically%20parcellated%20brain%20regions%2C%20structural%20connectivity%2C%20reconstructed%20intracranial%20electrodes%2C%20simulated%20brain%20activity%20at%20both%20the%20brain%20region%20and%20electrode%20levels%2C%20and%20key%20parameters%20of%20the%20virtual%20brain%20twin.%20These%20key%20parameters%2C%20which%20include%20the%20EZ%20hypothesis%2C%20serve%20as%20the%20ground-truth%20for%20simulated%20brain%20activity.%20For%20each%20virtual%20brain%20twin%2C%20we%20generated%20synthetic%20spontaneous%20seizures%2C%20stimulation-induced%20seizures%20and%20interictal%20activity.%20We%20systematically%20evaluated%20these%20simulated%20brain%20signals%20by%20quantitatively%20comparing%20them%20against%20their%20corresponding%20empirical%20intracranial%20recordings.%20Simulated%20signals%20based%20on%20patient-specific%20EZ%20captured%20spatio-temporal%20seizure%20generation%20and%20propagation.%20Through%20in-silico%20exploration%20of%20stimulation%20parameters%2C%20we%20also%20demonstrated%20the%20role%20of%20patient-specific%20stimulation%20location%20and%20amplitude%20in%20reproducing%20empirically%20stimulated%20seizures.%20The%20virtual%20epileptic%20cohort%20is%20openly%20available%2C%20and%20can%20be%20directly%20used%20to%20systematically%20evaluate%20methods%20for%20the%20estimation%20of%20EZ%20or%20source%20localization%20using%20ground%20truth%20EZ%20parameters%20and%20source%20signals.%22%2C%22date%22%3A%222025-04-11%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1371%5C%2Fjournal.pcbi.1012911%22%2C%22ISSN%22%3A%221553-7358%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22XTA6KS7L%22%2C%229RMECNPE%22%5D%2C%22dateModified%22%3A%222025-11-19T13%3A59%3A15Z%22%7D%7D%2C%7B%22key%22%3A%22WXTRWDEL%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Cotinat%20et%20al.%22%2C%22parsedDate%22%3A%222025-04-09%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BCotinat%2C%20M.%2C%20Robinet%2C%20E.%2C%20Messaoudi%2C%20N.%2C%20Suissa%2C%20L.%2C%20Doche%2C%20E.%2C%20Guye%2C%20M.%2C%20Bensoussan%2C%20L.%2C%20Zaaraoui%2C%20W.%20and%20Ranjeva%2C%20J.-P.%20%282025%29%20%26%23x201C%3BAdded%20Value%20of%20Sodium%20MR%20Imaging%20and%20Proton%20MR%20Spectroscopy%20to%20Conventional%20MR%20Imaging%20for%20a%20Better%20Characterization%20of%20the%20Ischemic%20Stroke%3A%20A%20Narrative%20Review%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BMagnetic%20resonance%20in%20medical%20sciences%3A%20MRMS%3A%20an%20official%20journal%20of%20Japan%20Society%20of%20Magnetic%20Resonance%20in%20Medicine%26lt%3B%5C%2Fi%26gt%3B%20%5BPreprint%5D.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.2463%5C%2Fmrms.rev.2025-0002%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.2463%5C%2Fmrms.rev.2025-0002%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Added%20Value%20of%20Sodium%20MR%20Imaging%20and%20Proton%20MR%20Spectroscopy%20to%20Conventional%20MR%20Imaging%20for%20a%20Better%20Characterization%20of%20the%20Ischemic%20Stroke%3A%20A%20Narrative%20Review%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ma%5Cu00ebva%22%2C%22lastName%22%3A%22Cotinat%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Emmanuelle%22%2C%22lastName%22%3A%22Robinet%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22No%5Cu00eblle%22%2C%22lastName%22%3A%22Messaoudi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Laurent%22%2C%22lastName%22%3A%22Suissa%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Emilie%22%2C%22lastName%22%3A%22Doche%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Laurent%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Wafaa%22%2C%22lastName%22%3A%22Zaaraoui%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%5D%2C%22abstractNote%22%3A%22Stroke%20is%20a%20major%20cause%20of%20disability%20and%20death%20in%20adults%20worldwide.%20In%20clinical%20setting%2C%20time%20efficient%20MRI%20protocols%20including%20diffusion%20weighted%20images%2C%20fluid%20attenuated%20inversion%20recovery%2C%20fast%20T2%2A-weighted%20images%20and%20MR%20angiography%20aim%20to%20establish%20ischemic%20stroke%20diagnosis%2C%20visualize%20vessel%20occlusion%20and%20determine%20the%20extent%20of%20ischemia%20damage%20distinguishing%20between%20the%20salvageable%20ischemic%20penumbra%20and%20the%20infarct%20core.%20Thus%2C%20MRI%20plays%20a%20pivotal%20role%20in%20diagnosis%2C%20treatment%20decision-making%2C%20and%20prognostic%20assessment%2C%20although%20prediction%20based%20on%20these%20elements%20remains%20limited%20and%20can%20be%20improved.%20We%20reviewed%20the%20added-values%20of%20alternative%20MRI%20methods%20such%20as%20sodium%2823Na%29%20MRI%20and%201H%20MR%20spectroscopic%20imaging%20that%20open%20new%20temporal%20and%20pathophysiological%20windows%20on%20ionic%20dys-homeostasis%20and%20metabolism%20alteration%20in%20the%20context%20of%20ischemic%20stroke%20and%20reperfusion.%20Insights%20on%20the%20timeline%20of%20the%20cellular%20events%20accessible%20using%20these%20alternative%20methods%20and%20perspectives%20to%20improve%20clinical%20outcome%20prediction%20of%20ischemic%20stroke%20patients%20are%20discussed.%22%2C%22date%22%3A%222025-04-09%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.2463%5C%2Fmrms.rev.2025-0002%22%2C%22ISSN%22%3A%221880-2206%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22UP3H3ICX%22%2C%22HVJZKIZG%22%2C%22P66W67T8%22%5D%2C%22dateModified%22%3A%222025-11-19T13%3A59%3A19Z%22%7D%7D%2C%7B%22key%22%3A%22NRCIS67N%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Roger%20et%20al.%22%2C%22parsedDate%22%3A%222025-03-20%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BRoger%2C%20C.%2C%20Lasbleiz%2C%20A.%2C%20Dary%2C%20H.%2C%20Pini%2C%20L.%2C%20Ancel%2C%20P.%2C%20Kovarova%2C%20A.%2C%20Ranjeva%2C%20M.-P.%2C%20Darmon%2C%20P.%2C%20Gaborit%2C%20B.%2C%20Fu%2C%20Y.%2C%20Cozzone%2C%20P.J.%2C%20Guye%2C%20M.%2C%20Dutour%2C%20A.%20and%20Ranjeva%2C%20J.-P.%20%282025%29%20%26%23x201C%3BStructural%20alterations%20of%20individual%20hypothalamic%20nuclei%20in%20young%20females%20with%20obesity%20and%20anorexia%20nervosa%3A%20an%20in%20vivo%207-T%20MRI%20study%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BThe%20American%20Journal%20of%20Clinical%20Nutrition%26lt%3B%5C%2Fi%26gt%3B%2C%20pp.%20S0002-9165%2825%2900071%26%23x2013%3B1.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.ajcnut.2025.02.003%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.ajcnut.2025.02.003%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Structural%20alterations%20of%20individual%20hypothalamic%20nuclei%20in%20young%20females%20with%20obesity%20and%20anorexia%20nervosa%3A%20an%20in%20vivo%207-T%20MRI%20study%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Coleen%22%2C%22lastName%22%3A%22Roger%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Adele%22%2C%22lastName%22%3A%22Lasbleiz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hugo%22%2C%22lastName%22%3A%22Dary%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lauriane%22%2C%22lastName%22%3A%22Pini%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Patricia%22%2C%22lastName%22%3A%22Ancel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anezka%22%2C%22lastName%22%3A%22Kovarova%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marie-Pierre%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Patrice%22%2C%22lastName%22%3A%22Darmon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Benedicte%22%2C%22lastName%22%3A%22Gaborit%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yu%22%2C%22lastName%22%3A%22Fu%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Patrick%20J.%22%2C%22lastName%22%3A%22Cozzone%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anne%22%2C%22lastName%22%3A%22Dutour%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%5D%2C%22abstractNote%22%3A%22BACKGROUND%3A%20The%20hypothalamus%20%28HT%29%20plays%20a%20crucial%20role%20in%20regulating%20eating%20behaviors.%20Disruptions%20in%20its%20function%20have%20been%20linked%20to%20the%20development%20of%20weight-related%20disorders.%20Nevertheless%2C%20its%20characterization%20remains%20a%20challenge.%5CnOBJECTIVES%3A%20We%20assessed%20the%20structural%20alterations%20of%20individual%20HT%20nuclei%20related%20to%20eating%20behaviors%20in%20patients%20with%20weight-related%20disorders%2C%20and%20their%20association%20with%20body%20mass%20index%20%28BMI%29%20and%20severity%20of%20eating%20disorders.%5CnMETHODS%3A%20Forty-four%20young%20females%20with%20normal%20weight%20%28HC%2C%20n%20%3D%2021%29%2C%20restrictive%20anorexia%20nervosa%20%28AN%2C%20n%20%3D%2013%29%2C%20and%20living%20with%20obesity%20%28OB%2C%20n%20%3D%2010%29%20were%20explored%20in%20vivo%20using%207-T%20high-resolution%20%280.6%20mm%20isotropic%20voxel%29%20T1%20quantitative%20magnetic%20resonance%20imaging%20%28MRI%29.%20Volumes%20and%20quantitative%20T1%20values%20of%20individual%20HT%20nuclei%20were%20compared%20after%20whole-brain%20normalization%20using%20nonparametric%20tests%20%28corrected%20for%20multiple%20comparisons%20for%20groups%20and%20regions%29.%20We%20investigated%20the%20parameters%20associated%20with%20BMI%20and%20eating%20disorders%2C%20such%20as%20MRI%20parameters%20of%20HT%20nuclei%2C%20ghrelin%20and%20leptin%20levels%2C%20depression%2C%20and%20anxiety%20using%20multivariate%20nonlinear%20partial%20least%20square%20%28NIPALS%29.%5CnRESULTS%3A%20Both%20AN%20and%20OB%20showed%20higher%20volumes%20of%20HT%20relative%20to%20HC%20%28Zscores%3A%200.78%20%5Cu00b1%201.06%3B%201.43%20%5Cu00b1%201.51%29.%20AN%20showed%20significantly%20higher%20volumes%20and%20T1%20values%20of%20the%20right%20paraventricular%20nucleus%20%28PaVN%29%20%28volume%20Zscore%3A%201.82%20%5Cu00b1%201.45%3B%20T1%20Zscore%3A%203.76%20%5Cu00b1%204.67%29%2C%20and%20higher%20T1%20values%20of%20the%20left%20PaVN%20%28Zscore%3A%202.25%20%5Cu00b1%202.37%29%20and%20right%20periventricular%20nuclei%20%28Zscore%3A%203.73%20%5Cu00b1%204.81%29.%20NIPALS%20models%20showed%20that%20lower%20BMI%20in%20AN%20was%20associated%20with%20structural%20alterations%20of%20the%20bilateral%20PaVN%2C%20right%20anterior%20commissure%2C%20and%20left%20fornix%20%28FX%29.%20Higher%20BMI%20in%20OB%20was%20associated%20with%20structural%20alterations%20within%20the%20right%20PaVN%2C%20bilateral%20FX%2C%20left%20posterior%20hypothalamic%20nucleus%2C%20right%20lateral%20HT%2C%20and%20right%20anterior%20hypothalamic%20area.%20Finally%2C%20the%20severity%20of%20eating%20disorders%20was%20associated%20with%20larger%20structural%20alterations%20within%20the%20bilateral%20PaVN%2C%20bilateral%20arcuate%20hypothalamic%20nuclei%2C%20right%20bed%20nucleus%20of%20stria%20terminalis%2C%20left%20medial%20preoptic%20nucleus%2C%20and%20right%20tubero-mammillary%20hypothalamic%20nucleus.%5CnCONCLUSIONS%3A%20Weight-related%20disorders%20are%20associated%20with%20significant%20micro%20and%20macrostructural%20alterations%20in%20HT%20nuclei%20involved%20in%20eating%20behaviors.%22%2C%22date%22%3A%222025-03-20%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.ajcnut.2025.02.003%22%2C%22ISSN%22%3A%221938-3207%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22UP3H3ICX%22%2C%224ZGX55W3%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-11-19T13%3A59%3A25Z%22%7D%7D%2C%7B%22key%22%3A%22BDR4Y4EI%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Testud%20et%20al.%22%2C%22parsedDate%22%3A%222025-03-08%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BTestud%2C%20B.%2C%20Destruel%2C%20A.%2C%20Troalen%2C%20T.%2C%20Ranjeva%2C%20J.-P.%20and%20Guye%2C%20M.%20%282025%29%20%26%23x201C%3BReview%20of%207T%20MRI%20imaging%20of%20pituitary%20microadenomas%3A%20are%20we%20there%20yet%3F%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BNeuroradiology%26lt%3B%5C%2Fi%26gt%3B%20%5BPreprint%5D.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs00234-025-03554-9%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs00234-025-03554-9%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Review%20of%207T%20MRI%20imaging%20of%20pituitary%20microadenomas%3A%20are%20we%20there%20yet%3F%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Benoit%22%2C%22lastName%22%3A%22Testud%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Aur%5Cu00e9lien%22%2C%22lastName%22%3A%22Destruel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Troalen%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%5D%2C%22abstractNote%22%3A%22PURPOSE%3A%207T%20MRI%20imaging%20of%20the%20pituitary%20gland%20is%20an%20emerging%20technique.%20The%20purpose%20of%20this%20article%20is%20to%20review%20the%20current%20status%20of%20the%207T%20MRI%20of%20the%20pituitary%20gland%2C%20particularly%20in%20the%20context%20of%20pituitary%20microadenoma%20pathology.%20We%20will%20discuss%20technical%20challenges%20and%20parallel%20transmission%20opportunities.%5CnMETHODS%3A%20Follow-up%20study%20selection%20and%20data%20extraction%20were%20performed%20following%20PRISMA%20guidelines.%20We%20focused%20on%20diagnostic%20performance%20and%20acquisition%20protocols.%20Inclusion%20criteria%20were%3A%20MRI%20imaging%20studies%20of%20pituitary%20adenoma%20at%207T.%20Exclusion%20criteria%20were%3A%20Case%20reports%20and%20reviews%3B%20studies%20which%20did%20not%20report%20MRI%20protocols%3B%20surgical%20planning%20studies%3B%20studies%20focusing%20exclusively%20on%20macroadenomas%20for%20which%20ultra-high%20magnetic%20field%20imaging%20is%20less%20decisive%20than%20microadenomas%20in%20clinical%20practice.%5CnRESULTS%3A%20Six%20studies%20were%20included.%207T%20MRI%20outperformed%201.5%20or%203T%20MRI%20for%20the%20detection%20of%20microadenomas.%20Acquisition%20protocols%20employed%20were%20heterogeneous%2C%20with%20two-dimensional%20T2-w%20and%20T1-w%20turbo%20spin-echo%20sequences%2C%20three-dimensional%20T1-w%20isotropic%20spin-echo%20and%20gradient-echo%20sequences%20%28resolution%3A%200.6%20and%200.8%5Cu00a0mm%29%2C%20and%20dynamic%20contrast-enhanced%20T1-w%20sequences.%5CnCONCLUSION%3A%207T%20MRI%20is%20a%20promising%20tool%20for%20overcoming%20the%20difficulties%20encountered%20by%20conventional%20MRI%2C%20particularly%20in%20the%20case%20of%20Cushing%20disease.%20However%2C%20there%20is%20insufficient%20data%20to%20precisely%20define%20an%20optimal%20protocol%20yet.%22%2C%22date%22%3A%222025-03-08%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1007%5C%2Fs00234-025-03554-9%22%2C%22ISSN%22%3A%221432-1920%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22UP3H3ICX%22%2C%22XTA6KS7L%22%2C%22PCMV2W5C%22%2C%22R8ARNQR7%22%5D%2C%22dateModified%22%3A%222025-11-19T13%3A59%3A04Z%22%7D%7D%2C%7B%22key%22%3A%225NQRWUU6%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Licht%20et%20al.%22%2C%22parsedDate%22%3A%222025-01-21%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BLicht%2C%20C.%2C%20Ilicak%2C%20E.%2C%20Boada%2C%20F.E.%2C%20Guye%2C%20M.%2C%20Z%26%23xF6%3Bllner%2C%20F.G.%2C%20Schad%2C%20L.R.%20and%20Rapacchi%2C%20S.%20%282025%29%20%26%23x201C%3BA%20noise-robust%20post-processing%20pipeline%20for%20accelerated%20phase-cycled%2023Na%20Multi-Quantum%20Coherences%20MRI%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BZeitschrift%20Fur%20Medizinische%20Physik%26lt%3B%5C%2Fi%26gt%3B%2C%20pp.%20S0939-3889%2824%2900117-X.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.zemedi.2024.12.004%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.zemedi.2024.12.004%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22A%20noise-robust%20post-processing%20pipeline%20for%20accelerated%20phase-cycled%2023Na%20Multi-Quantum%20Coherences%20MRI%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christian%22%2C%22lastName%22%3A%22Licht%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Efe%22%2C%22lastName%22%3A%22Ilicak%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fernando%20E.%22%2C%22lastName%22%3A%22Boada%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Frank%20G.%22%2C%22lastName%22%3A%22Z%5Cu00f6llner%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lothar%20R.%22%2C%22lastName%22%3A%22Schad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stanislas%22%2C%22lastName%22%3A%22Rapacchi%22%7D%5D%2C%22abstractNote%22%3A%22PURPOSE%3A%20To%20develop%20an%20improved%20post-processing%20pipeline%20for%20noise-robust%20accelerated%20phase-cycled%20Cartesian%20Single%20%28SQ%29%20and%20Triple%20Quantum%20%28TQ%29%20sodium%20%2823Na%29%20Magnetic%20Resonance%20Imaging%20%28MRI%29%20of%20in%20vivo%20human%20brain%20at%207%20T.%5CnTHEORY%20AND%20METHODS%3A%20Our%20pipeline%20aims%20to%20tackle%20the%20challenges%20of%2023Na%20Multi-Quantum%20Coherences%20%28MQC%29%20MRI%20including%20low%20Signal-to-Noise%20Ratio%20%28SNR%29%20and%20time-consuming%20Radiofrequency%20%28RF%29%20phase-cycling.%20Our%20method%20combines%20low-rank%20k-space%20denoising%20for%20SNR%20enhancement%20with%20Dynamic%20Mode%20Decomposition%20%28DMD%29%20to%20robustly%20separate%20SQ%20and%20TQ%20signal%20components.%20This%20separation%20is%20crucial%20for%20computing%20the%20TQ%5C%2FSQ%20ratio%2C%20a%20key%20parameter%20of%2023Na%20MQC%20MRI.%20We%20validated%20our%20pipeline%20in%20silico%2C%20in%20vitro%20and%20in%20vivo%20in%20healthy%20volunteers%2C%20comparing%20it%20with%20conventional%20denoising%20and%20Fourier%20transform%20%28FT%29%20methods.%20Additionally%2C%20we%20assessed%20its%20robustness%20through%20ablation%20experiments%20simulating%20a%20corrupted%20RF%20phase-cycle%20step.%5CnRESULTS%3A%20Our%20denoising%20algorithm%20doubled%20SNR%20compared%20to%20non-denoised%20images%20and%20enhanced%20SNR%20by%20up%20to%2029%25%20compared%20to%20Wavelet%20denoising.%20The%20low-rank%20approach%20produced%20high-quality%20images%20even%20at%20later%20echo%20times%2C%20allowing%20reduced%20signal%20averaging.%20DMD%20effectively%20separated%20the%20SQ%20and%20TQ%20signals%2C%20even%20with%20missing%20RF%20phase%20cycle%20steps%2C%20resulting%20in%20superior%20Structural%20Similarity%20%28SSIM%29%20of%200.89%5Cu00b10.024%20and%20lower%20Root%20Mean%20Squared%20Error%20%28RMSE%29%20of%200.055%5Cu00b10.008%20compared%20to%20conventional%20FT%20methods%20%28SSIM%3D0.71%5Cu00b10.061%2C%20RMSE%3D0.144%5Cu00b10.036%29.%20This%20pipeline%20enabled%20high-quality%208x8x15mm3%20in%20vivo%2023Na%20MQC%20MRI%2C%20with%20a%20reduction%20in%20acquisition%20time%20from%2048%20to%2010%5Cu202fmin%20at%207%20T.%5CnCONCLUSION%3A%20The%20proposed%20pipeline%20improves%20robustness%20in%2023Na%20MQC%20MRI%20by%20exploiting%20low-rank%20properties%20to%20denoise%20signals%20and%20DMD%20to%20effectively%20separate%20SQ%20and%20TQ%20signals.%20This%20approach%20ensures%20high-quality%20MR%20images%20of%20both%20SQ%20and%20TQ%20components%2C%20even%20in%20accelerated%20and%20incomplete%20RF%20phase-cycling%20cases.%22%2C%22date%22%3A%222025-01-21%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.zemedi.2024.12.004%22%2C%22ISSN%22%3A%221876-4436%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22SK6VWU7K%22%5D%2C%22dateModified%22%3A%222025-11-19T13%3A59%3A11Z%22%7D%7D%2C%7B%22key%22%3A%22PY4E2DQ4%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Martin%20et%20al.%22%2C%22parsedDate%22%3A%222025-01-11%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BMartin%2C%20S.%2C%20Andr%26%23xE9%3B%2C%20R.%2C%20Trabelsi%2C%20A.%2C%20Michel%2C%20C.P.%2C%20Fortanier%2C%20E.%2C%20Attarian%2C%20S.%2C%20Guye%2C%20M.%2C%20Dubois%2C%20M.%2C%20Abdeddaim%2C%20R.%20and%20Bendahan%2C%20D.%20%282025%29%20%26%23x201C%3BImportance%20of%20neural%20network%20complexity%20for%20the%20automatic%20segmentation%20of%20individual%20thigh%20muscles%20in%20MRI%20images%20from%20patients%20with%20neuromuscular%20diseases%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BMagma%20%28New%20York%2C%20N.Y.%29%26lt%3B%5C%2Fi%26gt%3B%20%5BPreprint%5D.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs10334-024-01221-3%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs10334-024-01221-3%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Importance%20of%20neural%20network%20complexity%20for%20the%20automatic%20segmentation%20of%20individual%20thigh%20muscles%20in%20MRI%20images%20from%20patients%20with%20neuromuscular%20diseases%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sandra%22%2C%22lastName%22%3A%22Martin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22R%5Cu00e9mi%22%2C%22lastName%22%3A%22Andr%5Cu00e9%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Amira%22%2C%22lastName%22%3A%22Trabelsi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Constance%20P.%22%2C%22lastName%22%3A%22Michel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Etienne%22%2C%22lastName%22%3A%22Fortanier%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shahram%22%2C%22lastName%22%3A%22Attarian%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marc%22%2C%22lastName%22%3A%22Dubois%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Redha%22%2C%22lastName%22%3A%22Abdeddaim%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Bendahan%22%7D%5D%2C%22abstractNote%22%3A%22OBJECTIVE%3A%20Segmentation%20of%20individual%20thigh%20muscles%20in%20MRI%20images%20is%20essential%20for%20monitoring%20neuromuscular%20diseases%20and%20quantifying%20relevant%20biomarkers%20such%20as%20fat%20fraction%20%28FF%29.%20Deep%20learning%20approaches%20such%20as%20U-Net%20have%20demonstrated%20effectiveness%20in%20this%20field.%20However%2C%20the%20impact%20of%20reducing%20neural%20network%20complexity%20remains%20unexplored%20in%20the%20FF%20quantification%20in%20individual%20muscles.%5CnMATERIAL%20AND%20METHODS%3A%20U-Net%20architectures%20with%20different%20complexities%20have%20been%20compared%20for%20the%20quantification%20of%20the%20fat%20fraction%20in%20each%20muscle%20group%20selected%20in%20the%20central%20part%20of%20the%20thigh%20region.%20The%20corresponding%20performance%20has%20been%20assessed%20in%20terms%20of%20Dice%20score%20%28DSC%29%20and%20FF%20quantification%20error.%20The%20database%20contained%201450%20thigh%20images%20from%2059%20patients%20and%2014%20healthy%20subjects%20%28age%3A%2047%5Cu2009%5Cu00b1%5Cu200917%5Cu00a0years%2C%20sex%3A%2036F%2C%2037M%29.%20Ten%20individual%20muscles%20were%20segmented%20in%20each%20image.%20The%20performance%20of%20each%20model%20was%20compared%20to%20nnU-Net%2C%20a%20complex%20architecture%20with%204.35%20%5Cu00d7%20107%20parameters%2C%2012.8%20Gigabytes%20of%20peak%20memory%20usage%20and%20167%5Cu00a0h%20of%20training%20time.%5CnRESULTS%3A%20As%20expected%2C%20nnU-Net%20achieved%20the%20highest%20DSC%20%2894.77%5Cu2009%5Cu00b1%5Cu20090.13%25%29.%20A%20simpler%20U-Net%20%285.81%20%5Cu00d7%20105%20parameters%2C%202.37%20Gigabytes%2C%2014%5Cu00a0h%20of%20training%20time%29%20achieved%20a%20lower%20DSC%20but%20still%20above%2090%25.%20Surprisingly%2C%20both%20models%20achieved%20a%20comparable%20FF%20estimation.%5CnDISCUSSION%3A%20The%20poor%20correlation%20between%20observed%20DSC%20and%20FF%20indicates%20that%20less%20complex%20architectures%2C%20reducing%20GPU%20memory%20utilization%20and%20training%20time%2C%20can%20still%20accurately%20quantify%20FF.%22%2C%22date%22%3A%222025-01-11%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1007%5C%2Fs10334-024-01221-3%22%2C%22ISSN%22%3A%221352-8661%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22NW6SZQBR%22%2C%22ZP8JD3DQ%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-11-19T13%3A59%3A34Z%22%7D%7D%2C%7B%22key%22%3A%22R59C7KNK%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Appukuttan%20et%20al.%22%2C%22parsedDate%22%3A%222025%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BAppukuttan%2C%20S.%2C%20Grapperon%2C%20A.-M.%2C%20El%20Mendili%2C%20M.M.%2C%20Dary%2C%20H.%2C%20Guye%2C%20M.%2C%20Verschueren%2C%20A.%2C%20Ranjeva%2C%20J.-P.%2C%20Attarian%2C%20S.%2C%20Zaaraoui%2C%20W.%20and%20Gilson%2C%20M.%20%282025%29%20%26%23x201C%3BEvaluating%20machine%20learning%20pipelines%20for%20multimodal%20neuroimaging%20in%20small%20cohorts%3A%20an%20ALS%20case%20study%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BFrontiers%20in%20Neuroinformatics%26lt%3B%5C%2Fi%26gt%3B%2C%2019%2C%20p.%201568116.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffninf.2025.1568116%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffninf.2025.1568116%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Evaluating%20machine%20learning%20pipelines%20for%20multimodal%20neuroimaging%20in%20small%20cohorts%3A%20an%20ALS%20case%20study%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shailesh%22%2C%22lastName%22%3A%22Appukuttan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Aude-Marie%22%2C%22lastName%22%3A%22Grapperon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mounir%20Mohamed%22%2C%22lastName%22%3A%22El%20Mendili%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hugo%22%2C%22lastName%22%3A%22Dary%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Annie%22%2C%22lastName%22%3A%22Verschueren%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shahram%22%2C%22lastName%22%3A%22Attarian%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Wafaa%22%2C%22lastName%22%3A%22Zaaraoui%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Matthieu%22%2C%22lastName%22%3A%22Gilson%22%7D%5D%2C%22abstractNote%22%3A%22Advancements%20in%20machine%20learning%20hold%20great%20promise%20for%20the%20analysis%20of%20multimodal%20neuroimaging%20data.%20They%20can%20help%20identify%20biomarkers%20and%20improve%20diagnosis%20for%20various%20neurological%20disorders.%20However%2C%20the%20application%20of%20such%20techniques%20for%20rare%20and%20heterogeneous%20diseases%20remains%20challenging%20due%20to%20small-cohorts%20available%20for%20acquiring%20data.%20Efforts%20are%20therefore%20commonly%20directed%20toward%20improving%20the%20classification%20models%2C%20in%20an%20effort%20to%20optimize%20outcomes%20given%20the%20limited%20data.%20In%20this%20study%2C%20we%20systematically%20evaluated%20the%20impact%20of%20various%20machine%20learning%20pipeline%20configurations%2C%20including%20scaling%20methods%2C%20feature%20selection%2C%20dimensionality%20reduction%2C%20and%20hyperparameter%20optimization.%20The%20efficacy%20of%20such%20components%20in%20the%20pipeline%20was%20evaluated%20on%20classification%20performance%20using%20multimodal%20MRI%20data%20from%20a%20cohort%20of%2016%20ALS%20patients%20and%2014%20healthy%20controls.%20Our%20findings%20reveal%20that%2C%20while%20certain%20pipeline%20components%2C%20such%20as%20subject-wise%20feature%20normalization%2C%20help%20improve%20classification%20outcomes%2C%20the%20overall%20influence%20of%20pipeline%20refinements%20on%20performance%20is%20modest.%20Feature%20selection%20and%20dimensionality%20reduction%20steps%20were%20found%20to%20have%20limited%20utility%2C%20and%20the%20choice%20of%20hyperparameter%20optimization%20strategies%20produced%20only%20marginal%20gains.%20Our%20results%20suggest%20that%2C%20for%20small-cohort%20studies%2C%20the%20emphasis%20should%20shift%20from%20extensive%20tuning%20of%20these%20pipelines%20to%20addressing%20data-related%20limitations%2C%20such%20as%20progressively%20expanding%20cohort%20size%2C%20integrating%20additional%20modalities%2C%20and%20maximizing%20the%20information%20extracted%20from%20existing%20datasets.%20This%20study%20provides%20a%20methodological%20framework%20to%20guide%20future%20research%20and%20emphasizes%20the%20need%20for%20dataset%20enrichment%20to%20improve%20clinical%20utility.%22%2C%22date%22%3A%222025%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.3389%5C%2Ffninf.2025.1568116%22%2C%22ISSN%22%3A%221662-5196%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22UP3H3ICX%22%2C%22P66W67T8%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-11-19T13%3A59%3A27Z%22%7D%7D%2C%7B%22key%22%3A%22VB3DDV37%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Grapperon%20et%20al.%22%2C%22parsedDate%22%3A%222025%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BGrapperon%2C%20A.-M.%2C%20El%20Mendili%2C%20M.M.%2C%20Maarouf%2C%20A.%2C%20Ranjeva%2C%20J.-P.%2C%20Guye%2C%20M.%2C%20Verschueren%2C%20A.%2C%20Attarian%2C%20S.%20and%20Zaaraoui%2C%20W.%20%282025%29%20%26%23x201C%3BIn%20vivo%20mapping%20of%20sodium%20homeostasis%20disturbances%20in%20individual%20ALS%20patients%3A%20A%20brain%2023Na%20MRI%20study%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BPloS%20One%26lt%3B%5C%2Fi%26gt%3B%2C%2020%281%29%2C%20p.%20e0316916.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1371%5C%2Fjournal.pone.0316916%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1371%5C%2Fjournal.pone.0316916%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22In%20vivo%20mapping%20of%20sodium%20homeostasis%20disturbances%20in%20individual%20ALS%20patients%3A%20A%20brain%2023Na%20MRI%20study%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Aude-Marie%22%2C%22lastName%22%3A%22Grapperon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mohamed%20Mounir%22%2C%22lastName%22%3A%22El%20Mendili%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Adil%22%2C%22lastName%22%3A%22Maarouf%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Annie%22%2C%22lastName%22%3A%22Verschueren%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shahram%22%2C%22lastName%22%3A%22Attarian%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Wafaa%22%2C%22lastName%22%3A%22Zaaraoui%22%7D%5D%2C%22abstractNote%22%3A%22OBJECTIVE%3A%20Amyotrophic%20lateral%20sclerosis%20%28ALS%29%20is%20a%20neurodegenerative%20disease%20characterized%20by%20significant%20heterogeneity%20among%20patients.%2023Na%20MRI%20maps%20abnormal%20sodium%20homeostasis%20that%20reflects%20metabolic%20alterations%20and%20energetic%20failure%20contributing%20to%20the%20neurodegenerative%20process.%20In%20this%20study%2C%20we%20investigated%20disease%20severity%20at%20the%20individual%20level%20in%20ALS%20patients%20using%20brain%2023Na%20MRI.%5CnMETHODS%3A%201H%20and%2023Na%20brain%20MRI%20were%20collected%20prospectively%20from%2028%20ALS%20patients.%20Individual%20map%20of%20abnormal%20total%20sodium%20concentration%20%28TSC%29%20was%20computed%20using%20voxel-based%20statistical%20mapping%20for%20each%20patient%20compared%20to%20a%20local%20database%20of%2062%20healthy%20controls.%20Clinical%20data%20included%20the%20revised%20ALS%20functional%20rating%20scale%20%28ALSFRS-R%29%2C%20ALSFRS-R%20slope%2C%20ALSFRS-R%20at%206-month%20and%20survival%20time.%5CnRESULTS%3A%20Individual%20maps%20quantifying%20voxels%20with%20TSC%20increase%20evidenced%20a%20high%20heterogeneity%20between%20patients%20consistent%20with%20clinical%20presentation.%20The%20main%20areas%20involved%20were%20the%20corticospinal%20tracts.%20Half%20of%20patients%20showed%20abnormal%20TSC%20increase%20within%20more%20than%201%25%20of%20whole%20brain%20voxels.%20Patients%20with%20TSC%20increase%20had%20worse%20clinical%20severity%3A%20higher%20ALSFRS-R%20slope%20%28p%20%3D%200.02%29%2C%20lower%20ALSFRS-R%20at%206-month%20%28p%20%3D%200.04%29%2C%20and%20shorter%20survival%20%28p%20%3D%200.04%29.%20ALS%20patients%20with%20limited%20TSC%20increase%20had%20slower%20progression%20of%20disability%20or%20predominant%20lower%20motor%20neuron%20phenotype%20or%20shorter%20disease%20duration.%5CnDISCUSSION%3A%20This%20study%20mapping%20sodium%20homeostasis%20disturbances%20at%20the%20individual%20level%20in%20ALS%20patients%20through%2023Na%20MRI%20evidenced%20heterogeneity%20of%20TSC%20increase%20among%20patients%20associated%20with%20clinical%20presentation%20and%20disease%20severity.%20These%20findings%20suggest%20that%20TSC%20increase%20detected%20at%20the%20individual%20level%20by%2023Na%20MRI%20may%20be%20a%20useful%20marker%20of%20the%20clinical%20heterogeneity%20of%20ALS%20patients%2C%20a%20factor%20that%20is%20likely%20to%20greatly%20influence%20the%20results%20of%20therapeutic%20trials.%22%2C%22date%22%3A%222025%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1371%5C%2Fjournal.pone.0316916%22%2C%22ISSN%22%3A%221932-6203%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22KJQH9V8M%22%2C%22UP3H3ICX%22%2C%22P66W67T8%22%2C%22F2AGIUQU%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-11-19T13%3A59%3A26Z%22%7D%7D%2C%7B%22key%22%3A%22FYSDR7HI%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Fortanier%20et%20al.%22%2C%22parsedDate%22%3A%222025%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BFortanier%2C%20E.%2C%20Michel%2C%20C.P.%2C%20Hostin%2C%20M.A.%2C%20Delmont%2C%20E.%2C%20Verschueren%2C%20A.%2C%20Guye%2C%20M.%2C%20Bellemare%2C%20M.-E.%2C%20Bendahan%2C%20D.%20and%20Attarian%2C%20S.%20%282025%29%20%26%23x201C%3BQuantitative%20muscle%20MRI%20combined%20with%20AI-based%20segmentation%20as%20a%20follow-up%20biomarker%20for%20ATTRv%20patients%3A%20A%20longitudinal%20pilot%20study%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BEuropean%20Journal%20of%20Neurology%26lt%3B%5C%2Fi%26gt%3B%2C%2032%281%29%2C%20p.%20e16574.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1111%5C%2Fene.16574%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1111%5C%2Fene.16574%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Quantitative%20muscle%20MRI%20combined%20with%20AI-based%20segmentation%20as%20a%20follow-up%20biomarker%20for%20ATTRv%20patients%3A%20A%20longitudinal%20pilot%20study%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Etienne%22%2C%22lastName%22%3A%22Fortanier%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Constance%20P.%22%2C%22lastName%22%3A%22Michel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marc%20Adrien%22%2C%22lastName%22%3A%22Hostin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Emilien%22%2C%22lastName%22%3A%22Delmont%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Annie%22%2C%22lastName%22%3A%22Verschueren%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marc-Emmanuel%22%2C%22lastName%22%3A%22Bellemare%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Bendahan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shahram%22%2C%22lastName%22%3A%22Attarian%22%7D%5D%2C%22abstractNote%22%3A%22Background%20and%20Objectives%20Intramuscular%20fat%20fraction%20%28FF%29%2C%20assessed%20using%20quantitative%20MRI%20%28qMRI%29%2C%20has%20emerged%20as%20a%20promising%20biomarker%20for%20hereditary%20transthyretin%20amyloidosis%20%28ATTRv%29%20patients.%20Currently%2C%20the%20main%20drawbacks%20to%20its%20use%20in%20future%20therapeutic%20trials%20are%20its%20sensitivity%20to%20change%20over%20a%20short%20period%20of%20time%20and%20the%20time-consuming%20manual%20segmentation%20step%20to%20extract%20quantitative%20data.%20This%20pilot%20study%20aimed%20to%20demonstrate%20the%20suitability%20of%20an%20Artificial%20Intelligence-based%20%28AI%29%20segmentation%20technique%20to%20assess%20disease%20progression%20in%20a%20real-life%20cohort%20of%20ATTRv%20patients%20over%201%20year.%20Methods%20Fifteen%20ATTRv%20patients%20were%20included%20in%20this%20monocentric%2C%20observational%2C%20prospective%20study.%20FF%2C%20magnetization%20transfer%20ratio%20%28MTR%29%2C%20and%20quantitative%20T2%20were%20extracted%20from%20patients%26%23039%3B%20lower%20limb%20qMRI%20at%20two%20time%20points%2C%201%20year%20apart%2C%20at%20thigh%20and%20leg%20levels.%20qMRI%20parameters%20were%20correlated%20with%20clinical%20and%20electrophysiological%20parameters%20assessed%20at%20the%20same%20time.%20Results%20Global%20FF%20at%20leg%20level%20significantly%20progressed%20over%201%20year%3A%20%2B1.28%20%5Cu00b1%202.62%25%20%28p%20%3D%200.017%29.%20At%20thigh%20level%2C%20no%20significant%20change%20in%20global%20FF%2C%20MTR%2C%20or%20T2%20was%20measured.%20The%20leg%20FF%20was%20strongly%20correlated%20with%20the%20main%20clinical%20and%20electrophysiological%20scores.%20Conclusion%20AI-based%20CNN%20network%20segmentation%20combined%20with%20qMRI%20can%20be%20used%20to%20obtain%20quantitative%20metrics%20for%20longitudinal%20studies%20in%20ATTRv%20patients.%20Global%20FF%20at%20the%20leg%20level%20seems%20to%20be%20the%20most%20sensitive%20MRI%20biomarker%20to%20track%20disease%20progression%20in%20a%201-year%20period.%20Larger%20studies%20with%20treatment-specific%20groups%20will%20now%20be%20necessary%20to%20determine%20the%20place%20of%20qMRI%20markers%20compared%20to%20the%20current%20clinical%20and%20electrophysiological%20scores.%22%2C%22date%22%3A%222025%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.1111%5C%2Fene.16574%22%2C%22ISSN%22%3A%221468-1331%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fonlinelibrary.wiley.com%5C%2Fdoi%5C%2Fabs%5C%2F10.1111%5C%2Fene.16574%22%2C%22collections%22%3A%5B%22NW6SZQBR%22%5D%2C%22dateModified%22%3A%222025-11-19T13%3A59%3A00Z%22%7D%7D%2C%7B%22key%22%3A%22LTY9CDDK%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Kassinopoulos%20et%20al.%22%2C%22parsedDate%22%3A%222025%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BKassinopoulos%2C%20M.%2C%20Rolandi%2C%20N.%2C%20Alphan%2C%20L.%2C%20Harper%2C%20R.M.%2C%20Oliveira%2C%20J.%2C%20Scott%2C%20C.%2C%20Koz%26%23xE1%3Bk%2C%20L.R.%2C%20Guye%2C%20M.%2C%20Lemieux%2C%20L.%20and%20Diehl%2C%20B.%20%282025%29%20%26%23x201C%3BBrain%20connectivity%20correlates%20of%20breathing%20and%20cardiac%20patterns%20in%20epilepsy%3A%20A%20study%20including%20SUDEP%20cases%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BImaging%20Neuroscience%20%28Cambridge%2C%20Mass.%29%26lt%3B%5C%2Fi%26gt%3B%2C%203%2C%20p.%20IMAG.a.918.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1162%5C%2FIMAG.a.918%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1162%5C%2FIMAG.a.918%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Brain%20connectivity%20correlates%20of%20breathing%20and%20cardiac%20patterns%20in%20epilepsy%3A%20A%20study%20including%20SUDEP%20cases%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Michalis%22%2C%22lastName%22%3A%22Kassinopoulos%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nicolo%22%2C%22lastName%22%3A%22Rolandi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Laren%22%2C%22lastName%22%3A%22Alphan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ronald%20M.%22%2C%22lastName%22%3A%22Harper%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Joana%22%2C%22lastName%22%3A%22Oliveira%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Catherine%22%2C%22lastName%22%3A%22Scott%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lajos%20R.%22%2C%22lastName%22%3A%22Koz%5Cu00e1k%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Louis%22%2C%22lastName%22%3A%22Lemieux%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Beate%22%2C%22lastName%22%3A%22Diehl%22%7D%5D%2C%22abstractNote%22%3A%22Sudden%20unexpected%20death%20in%20epilepsy%20%28SUDEP%29%20is%20the%20leading%20cause%20of%20premature%20mortality%20among%20people%20with%20epilepsy.%20Evidence%20from%20witnessed%20and%20monitored%20SUDEP%20cases%20indicates%20seizure-induced%20cardiovascular%20and%20respiratory%20failures%3B%20yet%2C%20the%20underlying%20mechanisms%20remain%20obscure.%20SUDEP%20occurs%20often%20during%20the%20night%20and%20early%20morning%20hours%2C%20suggesting%20that%20sleep%20or%20circadian%20rhythm-induced%20changes%20in%20physiology%20contribute%20to%20the%20fatal%20event.%20Resting-state%20functional%20MRI%20%28fMRI%29%20studies%20have%20found%20altered%20functional%20connectivity%20between%20brain%20structures%20involved%20in%20cardiorespiratory%20regulation%20in%20later%20SUDEP%20cases%20and%20in%20individuals%20at%20high%20risk%20of%20SUDEP.%20However%2C%20those%20connectivity%20findings%20have%20not%20been%20related%20to%20changes%20in%20cardiovascular%20or%20respiratory%20patterns.%20Here%2C%20we%20compared%20fMRI%20patterns%20of%20brain%20connectivity%20associated%20with%20regular%20and%20irregular%20cardiorespiratory%20rhythms%20in%20SUDEP%20cases%20with%20those%20of%20living%20epilepsy%20patients%20of%20varying%20SUDEP%20risk%20and%20healthy%20controls.%20We%20analysed%20resting-state%20fMRI%20data%20from%2098%20patients%20with%20epilepsy%20%289%20who%20subsequently%20succumbed%20to%20SUDEP%2C%2043%20categorized%20as%20low%20SUDEP%20risk%20%28no%20tonic-clonic%20seizures%20%28TCS%29%20in%20the%20year%20preceding%20the%20fMRI%20scan%29%2C%20and%2046%20as%20high%20SUDEP%20risk%20%28%26gt%3B3%20TCS%20in%20the%20year%20preceding%20the%20scan%29%29%2C%20and%2025%20healthy%20controls.%20The%20global%20signal%20amplitude%20%28GSA%29%2C%20defined%20as%20the%20moving%20standard%20deviation%20of%20the%20fMRI%20global%20signal%2C%20was%20used%20to%20identify%20periods%20with%20regular%20%28%26quot%3Blow%20state%26quot%3B%29%20and%20irregular%20%28%26quot%3Bhigh%20state%26quot%3B%29%20cardiorespiratory%20rhythms.%20Correlation%20maps%20were%20derived%20from%20seeds%20in%2012%20regions%20with%20a%20key%20role%20in%20autonomic%20or%20respiratory%20regulation%20for%20the%20low%20and%20high%20states.%20Following%20principal%20component%20analysis%2C%20component%20weights%20were%20compared%20between%20the%20groups.%20We%20found%20widespread%20alterations%20in%20connectivity%20of%20precuneus%5C%2Fposterior%20cingulate%20cortex%20in%20epilepsy%20compared%20with%20controls%20in%20the%20low%20state%20%28regular%20cardiorespiratory%20activity%29.%20In%20the%20low%20state%2C%20and%20to%20a%20lesser%20degree%20in%20the%20high%20state%2C%20reduced%20anterior%20insula%20connectivity%20%28mainly%20with%20anterior%20and%20posterior%20cingulate%20cortex%29%20in%20epilepsy%20appeared%2C%20relative%20to%20healthy%20controls.%20For%20SUDEP%20cases%2C%20the%20insula%20connectivity%20differences%20were%20inversely%20related%20to%20the%20interval%20between%20the%20fMRI%20scan%20and%20death.%20The%20findings%20suggest%20that%20anterior%20insula%20connectivity%20measures%20may%20provide%20a%20biomarker%20of%20SUDEP%20risk.%20The%20neural%20correlates%20of%20autonomic%20brain%20structural%20activity%20associated%20with%20different%20cardiorespiratory%20rhythms%20may%20shed%20light%20on%20the%20mechanisms%20underlying%20the%20fatal%20event%20in%20SUDEP.%22%2C%22date%22%3A%222025%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1162%5C%2FIMAG.a.918%22%2C%22ISSN%22%3A%222837-6056%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-10-30T10%3A30%3A33Z%22%7D%7D%2C%7B%22key%22%3A%22ITHXP2FK%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Testud%20et%20al.%22%2C%22parsedDate%22%3A%222024-11-27%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BTestud%2C%20B.%2C%20Guye%2C%20M.%2C%20Witjas%2C%20T.%20and%20Grimaldi%2C%20S.%20%282024%29%20%26%23x201C%3BIron%20overload%20revealing%20the%20cytoarchitecture%20of%20the%20red%20nucleus%3A%20A%20case%20study%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BRevue%20Neurologique%26lt%3B%5C%2Fi%26gt%3B%2C%20pp.%20S0035-3787%2824%2900660-X.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.neurol.2024.11.001%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.neurol.2024.11.001%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Iron%20overload%20revealing%20the%20cytoarchitecture%20of%20the%20red%20nucleus%3A%20A%20case%20study%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22B.%22%2C%22lastName%22%3A%22Testud%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22M.%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22T.%22%2C%22lastName%22%3A%22Witjas%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22S.%22%2C%22lastName%22%3A%22Grimaldi%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222024-11-27%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.neurol.2024.11.001%22%2C%22ISSN%22%3A%220035-3787%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22PCMV2W5C%22%2C%22H8UPCNQI%22%5D%2C%22dateModified%22%3A%222025-09-19T07%3A45%3A51Z%22%7D%7D%2C%7B%22key%22%3A%22XWY2NCND%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Joppin%20et%20al.%22%2C%22parsedDate%22%3A%222024-11-20%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BJoppin%2C%20V.%2C%20Jourdan%2C%20A.%2C%20Bendahan%2C%20D.%2C%20Soucasse%2C%20A.%2C%20Guye%2C%20M.%2C%20Masson%2C%20C.%20and%20B%26%23xE8%3Bge%2C%20T.%20%282024%29%20%26%23x201C%3BTowards%20a%20better%20understanding%20of%20abdominal%20wall%20biomechanics%3A%20In%20vivo%20relationship%20between%20dynamic%20intra-abdominal%20pressure%20and%20magnetic%20resonance%20imaging%20measurements%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BClinical%20Biomechanics%20%28Bristol%2C%20Avon%29%26lt%3B%5C%2Fi%26gt%3B%2C%20121%2C%20p.%20106396.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.clinbiomech.2024.106396%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.clinbiomech.2024.106396%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Towards%20a%20better%20understanding%20of%20abdominal%20wall%20biomechanics%3A%20In%20vivo%20relationship%20between%20dynamic%20intra-abdominal%20pressure%20and%20magnetic%20resonance%20imaging%20measurements%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Victoria%22%2C%22lastName%22%3A%22Joppin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Arthur%22%2C%22lastName%22%3A%22Jourdan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Bendahan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Andr%5Cu00e9a%22%2C%22lastName%22%3A%22Soucasse%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Catherine%22%2C%22lastName%22%3A%22Masson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thierry%22%2C%22lastName%22%3A%22B%5Cu00e8ge%22%7D%5D%2C%22abstractNote%22%3A%22BACKGROUND%3A%20In%20vivo%20mechanical%20behaviour%20of%20the%20abdominal%20wall%20has%20been%20poorly%20characterised%20and%20important%20details%20are%20missing%20regarding%20the%20occurrence%20and%20post-operative%20recurrence%20rate%20of%20hernias%20which%20can%20be%20as%20high%20as%2030%5Cu00a0%25.%20This%20study%20aimed%20to%20assess%20the%20correlation%20between%20abdominal%20wall%20displacement%20and%20intra-abdominal%20pressure%2C%20as%20well%20as%20abdominal%20compliance.%5CnMETHODS%3A%20Eighteen%20healthy%20participants%20performed%20audio-guided%20passive%20%28breathing%29%20and%20active%20%28coughing%2C%20Valsalva%20maneuver%29%20exercises.%20Axial%20dynamic%20changes%20of%20abdominal%20muscles%20and%20visceral%20area%20were%20measured%20using%20MRI%2C%20and%20intra-abdominal%20pressure%20with%20ingested%20pressure%20sensor.%5CnFINDINGS%3A%20Correlations%20between%20abdominal%20wall%20displacement%20and%20intra-abdominal%20pressure%20were%20specific%20to%20participant%2C%20exercise%2C%20and%20varying%20between%20rectus%20abdominis%20and%20lateral%20muscles.%20Strong%20correlations%20were%20found%20between%20rectus%20abdominis%20displacement%20and%20intra-abdominal%20pressure%20during%20breathing%20%28r%5Cu00a0%3D%5Cu00a00.92%5Cu00a0%5Cu00b1%5Cu00a00.06%29%2C%20as%20well%20as%20lateral%20muscles%20displacement%20with%20intra-abdominal%20pressure%20during%20coughing%20and%20Valsalva%20maneuver%20%28r%5Cu00a0%3D%5Cu00a0-0.98%5Cu00a0%5Cu00b1%5Cu00a00.03%20and%5Cu00a0-%5Cu00a00.94%5Cu00a0%5Cu00b1%5Cu00a00.05%20respectively%29.%20The%20abdominal%20pseudo-compliance%20varied%20greatly%20among%20participants%20during%20muscular%20contraction%2C%20the%20coefficient%20of%20variation%20reaching%20up%20to%2070%5Cu00a0%25.%5CnINTERPRETATION%3A%20The%20combination%20of%20intra-abdominal%20pressure%20and%20dynamic%20MRI%20measurements%20enables%20the%20identification%20of%20participant-specific%20behaviour%20pattern.%20Intra-abdominal%20pressure%20and%20abdominal%20wall%20dynamic%20undergo%20consistent%20and%20predictable%20interactions.%20However%2C%20this%20relationship%20is%20subject-specific%20and%20may%20not%20be%20extrapolated%20to%20other%20individuals.%20Therefore%2C%20both%20intra-abdominal%20pressure%20and%20abdominal%20wall%20motion%20must%20be%20measured%20in%20the%20same%20participant%20in%20order%20to%20accurately%20characterise%20the%20abdominal%20wall%20behaviour.%20These%20results%20are%20of%20great%20importance%20for%20mesh%20design%2C%20surgical%20decision-making%2C%20and%20personalised%20healthcare.%22%2C%22date%22%3A%222024-11-20%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.clinbiomech.2024.106396%22%2C%22ISSN%22%3A%221879-1271%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22NW6SZQBR%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-09-19T07%3A44%3A11Z%22%7D%7D%2C%7B%22key%22%3A%22CHX847WV%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Durozard%20et%20al.%22%2C%22parsedDate%22%3A%222024-11%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BDurozard%2C%20P.%2C%20Maarouf%2C%20A.%2C%20Zaaraoui%2C%20W.%2C%20Stellmann%2C%20J.-P.%2C%20Bouti%26%23xE8%3Bre%2C%20C.%2C%20Rico%2C%20A.%2C%20Demorti%26%23xE8%3Bre%2C%20S.%2C%20Guye%2C%20M.%2C%20Le%20Troter%2C%20A.%2C%20Dary%2C%20H.%2C%20Ranjeva%2C%20J.-P.%2C%20Audoin%2C%20B.%20and%20Pelletier%2C%20J.%20%282024%29%20%26%23x201C%3BCortical%20Lesions%20as%20an%20Early%20Hallmark%20of%20Multiple%20Sclerosis%3A%20Visualization%20by%207%20T%20MRI%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BInvestigative%20Radiology%26lt%3B%5C%2Fi%26gt%3B%2C%2059%2811%29%2C%20p.%20747.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1097%5C%2FRLI.0000000000001082%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1097%5C%2FRLI.0000000000001082%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Cortical%20Lesions%20as%20an%20Early%20Hallmark%20of%20Multiple%20Sclerosis%3A%20Visualization%20by%207%20T%20MRI%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Pierre%22%2C%22lastName%22%3A%22Durozard%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Adil%22%2C%22lastName%22%3A%22Maarouf%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Wafaa%22%2C%22lastName%22%3A%22Zaaraoui%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan-Patrick%22%2C%22lastName%22%3A%22Stellmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Cl%5Cu00e9mence%22%2C%22lastName%22%3A%22Bouti%5Cu00e8re%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Audrey%22%2C%22lastName%22%3A%22Rico%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sarah%22%2C%22lastName%22%3A%22Demorti%5Cu00e8re%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Arnaud%22%2C%22lastName%22%3A%22Le%20Troter%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hugo%22%2C%22lastName%22%3A%22Dary%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Bertrand%22%2C%22lastName%22%3A%22Audoin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean%22%2C%22lastName%22%3A%22Pelletier%22%7D%5D%2C%22abstractNote%22%3A%22Objectives%5Cu00a0%5Cn%20%20%20%20%20%20%20%20%20%20Compelling%20evidence%20indicates%20a%20significant%20involvement%20of%20cortical%20lesions%20in%20the%20progressive%20phase%20of%20multiple%20sclerosis%20%28MS%29%2C%20significantly%20contributing%20to%20late-stage%20disability.%20Despite%20the%20promise%20of%20ultra-high-field%20magnetic%20resonance%20imaging%20%28MRI%29%20in%20detecting%20cortical%20lesions%2C%20current%20evidence%20falls%20short%20in%20providing%20insights%20into%20the%20existence%20of%20such%20lesions%20during%20the%20early%20stages%20of%20MS%20or%20their%20underlying%20cause.%20This%20study%20delineated%2C%20at%20the%20early%20stage%20of%20MS%2C%20%281%29%20the%20prevalence%20and%20spatial%20distribution%20of%20cortical%20lesions%20identified%20by%207%20T%20MRI%2C%20%282%29%20their%20relationship%20with%20white%20matter%20lesions%2C%20and%20%283%29%20their%20clinical%20implications.%5Cn%20%20%20%20%20%20%20%20%20%20Materials%20and%20Methods%5Cu00a0%5Cn%20%20%20%20%20%20%20%20%20%20Twenty%20individuals%20with%20early-stage%20relapsing-remitting%20MS%20%28disease%20duration%20%26lt%3B1%20year%29%20underwent%20a%207%20T%20MRI%20session%20involving%20T1-weighted%20MP2RAGE%2C%20T2%2A-weighted%20multiGRE%2C%20and%20T2-weighted%20FLAIR%20sequences%20for%20cortical%20and%20white%20matter%20segmentation.%20Disability%20assessments%20included%20the%20Expanded%20Disability%20Status%20Scale%2C%20the%20Multiple%20Sclerosis%20Functional%20Composite%2C%20and%20an%20extensive%20evaluation%20of%20cognitive%20function.%5Cn%20%20%20%20%20%20%20%20%20%20Results%5Cu00a0%5Cn%20%20%20%20%20%20%20%20%20%20Cortical%20lesions%20were%20detected%20in%2015%20of%2020%20patients%20%2875%25%29.%20MP2RAGE%20revealed%20a%20total%20of%20190%20intracortical%20lesions%20%28median%2C%204%20lesions%5C%2Fcase%20%5Brange%2C%200%5Cu201344%5D%29%20and%20216%20leukocortical%20lesions%20%28median%2C%202%20lesions%5C%2Fcase%20%5Brange%2C%200%5Cu201375%5D%29.%20Although%20the%20number%20of%20white%20matter%20lesions%20correlated%20with%20the%20total%20number%20of%20leukocortical%20lesions%20%28r%20%3D%200.91%2C%20P%20%26lt%3B%200.001%29%2C%20no%20correlation%20was%20observed%20between%20the%20number%20of%20white%20matter%20or%20leukocortical%20lesions%20and%20the%20number%20of%20intracortical%20lesions.%20Furthermore%2C%20the%20number%20of%20leukocortical%20lesions%20but%20not%20intracortical%20or%20white-matter%20lesions%20was%20significantly%20correlated%20with%20cognitive%20impairment%20%28r%20%3D%200.63%2C%20P%20%3D%200.04%2C%20corrected%20for%20multiple%20comparisons%29.%5Cn%20%20%20%20%20%20%20%20%20%20Conclusions%5Cu00a0%5Cn%20%20%20%20%20%20%20%20%20%20This%20study%20highlights%20the%20notable%20prevalence%20of%20cortical%20lesions%20at%20the%20early%20stage%20of%20MS%20identified%20by%207%20T%20MRI.%20There%20may%20be%20a%20potential%20divergence%20in%20the%20underlying%20pathophysiological%20mechanisms%20driving%20distinct%20lesion%20types%2C%20notably%20between%20intracortical%20lesions%20and%20white%20matter%5C%2Fleukocortical%20lesions.%20Moreover%2C%20during%20the%20early%20disease%20phase%2C%20leukocortical%20lesions%20more%20effectively%20accounted%20for%20cognitive%20deficits.%22%2C%22date%22%3A%22November%202024%22%2C%22language%22%3A%22en-US%22%2C%22DOI%22%3A%2210.1097%5C%2FRLI.0000000000001082%22%2C%22ISSN%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fjournals.lww.com%5C%2Finvestigativeradiology%5C%2Fabstract%5C%2F2024%5C%2F11000%5C%2Fcortical_lesions_as_an_early_hallmark_of_multiple.1.aspx%22%2C%22collections%22%3A%5B%22KJQH9V8M%22%2C%22UP3H3ICX%22%2C%22B4EWFM7E%22%2C%225P5FWCR9%22%2C%226KPLZTET%22%2C%229L2KHJ5X%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-09-12T07%3A59%3A03Z%22%7D%7D%2C%7B%22key%22%3A%22Q3YEF387%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22K%5Cu00f6ksal-Ers%5Cu00f6z%20et%20al.%22%2C%22parsedDate%22%3A%222024-07-18%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BK%26%23xF6%3Bksal-Ers%26%23xF6%3Bz%2C%20E.%2C%20Makhalova%2C%20J.%2C%20Yochum%2C%20M.%2C%20B%26%23xE9%3Bnar%2C%20C.-G.%2C%20Guye%2C%20M.%2C%20Bartolomei%2C%20F.%2C%20Wendling%2C%20F.%20and%20Merlet%2C%20I.%20%282024%29%20%26%23x201C%3BWhole-brain%20simulation%20of%20interictal%20epileptic%20discharges%20for%20patient-specific%20interpretation%20of%20interictal%20SEEG%20data%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BNeurophysiologie%20Clinique%20%3D%20Clinical%20Neurophysiology%26lt%3B%5C%2Fi%26gt%3B%2C%2054%285%29%2C%20p.%20103005.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.neucli.2024.103005%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.neucli.2024.103005%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Whole-brain%20simulation%20of%20interictal%20epileptic%20discharges%20for%20patient-specific%20interpretation%20of%20interictal%20SEEG%20data%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Elif%22%2C%22lastName%22%3A%22K%5Cu00f6ksal-Ers%5Cu00f6z%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Julia%22%2C%22lastName%22%3A%22Makhalova%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Yochum%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christian-G.%22%2C%22lastName%22%3A%22B%5Cu00e9nar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabrice%22%2C%22lastName%22%3A%22Bartolomei%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabrice%22%2C%22lastName%22%3A%22Wendling%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Isabelle%22%2C%22lastName%22%3A%22Merlet%22%7D%5D%2C%22abstractNote%22%3A%22In%20patients%20with%20refractory%20epilepsy%2C%20the%20clinical%20interpretation%20of%20stereoelectroencephalographic%20%28SEEG%29%20signals%20is%20crucial%20to%20delineate%20the%20epileptogenic%20network%20that%20should%20be%20targeted%20by%20surgery.%20We%20propose%20a%20pipeline%20of%20patient-specific%20computational%20modeling%20of%20interictal%20epileptic%20activity%20to%20improve%20the%20definition%20of%20regions%20of%20interest.%20Comparison%20between%20the%20computationally%20defined%20regions%20of%20interest%20and%20the%20resected%20region%20confirmed%20the%20efficiency%20of%20the%20pipeline.%20This%20result%20suggests%20that%20computational%20modeling%20can%20be%20used%20to%20reconstruct%20signals%20and%20aid%20clinical%20interpretation.%22%2C%22date%22%3A%222024-07-18%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.neucli.2024.103005%22%2C%22ISSN%22%3A%221769-7131%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22XTA6KS7L%22%2C%229RMECNPE%22%5D%2C%22dateModified%22%3A%222025-09-12T07%3A59%3A19Z%22%7D%7D%2C%7B%22key%22%3A%22VLBWEWJY%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Fortanier%20et%20al.%22%2C%22parsedDate%22%3A%222024-05-14%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BFortanier%2C%20E.%2C%20Hostin%2C%20M.A.%2C%20Michel%2C%20C.%2C%20Delmont%2C%20E.%2C%20Bellemare%2C%20M.-E.%2C%20Guye%2C%20M.%2C%20Bendahan%2C%20D.%20and%20Attarian%2C%20S.%20%282024%29%20%26%23x201C%3BOne-Year%20Longitudinal%20Assessment%20of%20Patients%20With%20CMT1A%20Using%20Quantitative%20MRI%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BNeurology%26lt%3B%5C%2Fi%26gt%3B%2C%20102%289%29%2C%20p.%20e209277.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1212%5C%2FWNL.0000000000209277%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1212%5C%2FWNL.0000000000209277%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22One-Year%20Longitudinal%20Assessment%20of%20Patients%20With%20CMT1A%20Using%20Quantitative%20MRI%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Etienne%22%2C%22lastName%22%3A%22Fortanier%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marc%20Adrien%22%2C%22lastName%22%3A%22Hostin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Constance%22%2C%22lastName%22%3A%22Michel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Emilien%22%2C%22lastName%22%3A%22Delmont%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marc-Emmanuel%22%2C%22lastName%22%3A%22Bellemare%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Bendahan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shahram%22%2C%22lastName%22%3A%22Attarian%22%7D%5D%2C%22abstractNote%22%3A%22Background%20and%20Objectives%5CnIntramuscular%20fat%20fraction%20%28FF%29%20assessed%20using%20quantitative%20MRI%20%28qMRI%29%20has%20emerged%20as%20one%20of%20the%20few%20responsive%20outcome%20measures%20in%20CMT1A%20suitable%20for%20future%20clinical%20trials.%20This%20study%20aimed%20to%20identify%20the%20relevance%20of%20multiple%20qMRI%20biomarkers%20for%20tracking%20longitudinal%20changes%20in%20CMT1A%20and%20to%20assess%20correlations%20between%20MRI%20metrics%20and%20clinical%20parameters.%5CnMethods%5CnqMRI%20was%20performed%20in%20CMT1A%20patients%20at%202%20time%20points%2C%20a%20year%20apart%2C%20and%20various%20metrics%20were%20extracted%20from%203-dimensional%20volumes%20of%20interest%20at%20thigh%20and%20leg%20levels.%20A%20semiautomated%20segmentation%20technique%20was%20used%2C%20enabling%20the%20analysis%20of%20central%20slices%20and%20a%20larger%203D%20muscle%20volume.%20Metrics%20included%20proton%20density%20%28PD%29%2C%20magnetization%20transfer%20ratio%20%28MTR%29%2C%20and%20intramuscular%20FF.%20The%20sciatic%20and%20tibial%20nerves%20were%20also%20assessed.%20Disease%20severity%20was%20gauged%20using%20Charcot%20Marie%20Tooth%20Neurologic%20Score%20%28CMTNSv2%29%2C%20Charcot%20Marie%20Tooth%20Examination%20Score%2C%20Overall%20Neuropathy%20Limitation%20Scale%20scores%2C%20and%20Medical%20Research%20Council%20%28MRC%29%20muscle%20strength.%5CnResults%5CnTwenty-four%20patients%20were%20included.%20FF%20significantly%20rose%20in%20the%203D%20volume%20at%20both%20thigh%20%28%2B1.04%25%20%5Cu00b1%202.19%25%2C%20p%20%3D%200.041%29%20and%20leg%20%28%2B1.36%25%20%5Cu00b1%201.87%25%2C%20p%20%3D%200.045%29%20levels.%20The%203D%20analyses%20unveiled%20a%20length-dependent%20gradient%20in%20FF%2C%20ranging%20from%2022.61%25%20%5Cu00b1%2010.17%25%20to%2026.17%25%20%5Cu00b1%2010.79%25%20at%20the%20leg%20level.%20There%20was%20noticeable%20variance%20in%20longitudinal%20changes%20between%20muscles%3A%20%2B3.17%25%20%5Cu00b1%206.86%25%20%28p%20%3D%200.028%29%20in%20the%20tibialis%20anterior%20compared%20with%200.37%25%20%5Cu00b1%204.97%25%20%28p%20%3D%200.893%29%20in%20the%20gastrocnemius%20medialis.%20MTR%20across%20the%20entire%20thigh%20volume%20showed%20a%20significant%20decline%20between%20the%202%20time%20points%20%5Cu22122.75%20%5Cu00b1%206.58%20%28p%20%3D%200.049%29%2C%20whereas%20no%20significant%20differences%20were%20noted%20for%20the%203D%20muscle%20volume%20and%20PD.%20No%20longitudinal%20changes%20were%20observed%20in%20any%20nerve%20metric.%20Potent%20correlations%20were%20identified%20between%20FF%20and%20primary%20clinical%20measures%3A%20CMTNSv2%20%28%5Cu03c1%20%3D%200.656%3B%20p%20%3D%200.001%29%20and%20MRC%20in%20the%20lower%20limbs%20%28%5Cu03c1%20%3D%20%5Cu22120.877%3B%20p%20%26lt%3B%200.001%29.%5CnDiscussion%5CnOur%20results%20further%20support%20that%20qMRI%20is%20a%20promising%20tool%20for%20following%20up%20longitudinal%20changes%20in%20CMT1A%20patients%2C%20FF%20being%20the%20paramount%20MRI%20metric%20for%20both%20thigh%20and%20leg%20regions.%20It%20is%20crucial%20to%20scrutinize%20the%20postimaging%20data%20extraction%20methods%20considering%20that%20annual%20changes%20are%20minimal%20%28around%20%2B1.5%25%29.%20Given%20the%20varied%20FF%20distribution%2C%20the%20existence%20of%20a%20length-dependent%20gradient%2C%20and%20the%20differential%20fatty%20involution%20across%20muscles%2C%203D%20volume%20analysis%20appeared%20more%20suitable%20than%20single%20slice%20analysis.%22%2C%22date%22%3A%222024-05-14%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.1212%5C%2FWNL.0000000000209277%22%2C%22ISSN%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.neurology.org%5C%2Fdoi%5C%2F10.1212%5C%2FWNL.0000000000209277%22%2C%22collections%22%3A%5B%22NW6SZQBR%22%2C%22ZP8JD3DQ%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-09-12T07%3A59%3A04Z%22%7D%7D%2C%7B%22key%22%3A%22ADQBEBSB%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Grimaldi%20et%20al.%22%2C%22parsedDate%22%3A%222024-05-06%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BGrimaldi%2C%20S.%2C%20Le%20Troter%2C%20A.%2C%20El%20Mendili%2C%20M.M.%2C%20Dary%2C%20H.%2C%20Azulay%2C%20J.-P.%2C%20Zaaraoui%2C%20W.%2C%20Ranjeva%2C%20J.-P.%2C%20Eusebio%2C%20A.%2C%20de%20Rochefort%2C%20L.%20and%20Guye%2C%20M.%20%282024%29%20%26%23x201C%3BEnergetic%20dysfunction%20and%20iron%20overload%20in%20early%20Parkinson%26%23x2019%3Bs%20disease%3A%20Two%20distinct%20mechanisms%3F%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BParkinsonism%20%26amp%3B%20Related%20Disorders%26lt%3B%5C%2Fi%26gt%3B%2C%20124%2C%20p.%20106996.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.parkreldis.2024.106996%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.parkreldis.2024.106996%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Energetic%20dysfunction%20and%20iron%20overload%20in%20early%20Parkinson%27s%20disease%3A%20Two%20distinct%20mechanisms%3F%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stephan%22%2C%22lastName%22%3A%22Grimaldi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Arnaud%22%2C%22lastName%22%3A%22Le%20Troter%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mohamed%20Mounir%22%2C%22lastName%22%3A%22El%20Mendili%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hugo%22%2C%22lastName%22%3A%22Dary%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Azulay%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Wafaa%22%2C%22lastName%22%3A%22Zaaraoui%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexandre%22%2C%22lastName%22%3A%22Eusebio%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ludovic%22%2C%22lastName%22%3A%22de%20Rochefort%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%5D%2C%22abstractNote%22%3A%22INTRODUCTION%3A%20Identifying%20biomarkers%20reflecting%20cellular%20dysfunctions%20in%20early%20Parkinson%26%23039%3Bs%20disease%20patients%20%28ePD%29%20is%20needed%20to%20develop%20targeted%20therapeutic%20strategies.%20We%20aimed%20to%20determine%20if%20cellular%20energetic%20dysfunction%20related%20to%20increased%20brain%20sodium%20concentration%20would%20be%20co-located%20to%20microstructural%20alterations%20and%20iron%20deposition%20in%20ePD.%5CnMETHODS%3A%20We%20prospectively%20included%2012%20ePD%20%28mean%20disease%20duration%2020.0%5Cu00a0%5Cu00b1%5Cu00a010.2%20months%29%20and%2013%20healthy%20controls%20%28HC%29%2C%20scanned%20with%20a%207%5Cu00a0T%201H%20and%2023Na%20MRI.%20Complementary%20voxel-based%20and%20region-based%20assessments%20were%20performed%2C%20the%20latter%20utilizing%20a%20high-resolution%20multimodal%20template%20we%20created%20%28combining%20quantitative%20T1%20maps%20%28qT1%29%2C%20transverse%20relaxation%20rate%20%28R2%2A%29%2C%20quantitative%20magnetic%20susceptibility%20mapping%20%28QSM%29%20images%29%20from%20200%20subjects.%20This%20template%20allowed%20a%20precise%20multiparametric%20assessment%20of%20sodium%20concentration%2C%20QSM%2C%20R2%2A%2C%20qT1%2C%20mean%20diffusivity%2C%20and%20fractional%20anisotropy%20values.%20A%20two-sided%20p-value%26lt%3B0.05%20was%20considered%20statistically%20significant%20after%20the%20Bonferroni%20correction.%5CnRESULTS%3A%20Relative%20to%20HC%2C%20ePD%20showed%20significantly%20higher%20sodium%20concentration%20in%20left%20Substantia%20nigra%20%28SN%29%20pars%20reticulata%20%2846.13%5Cu00a0mM%5Cu00a0%5Cu00b1%5Cu00a03.52%20vs%2038.60%5Cu00a0mM%5Cu00a0%5Cu00b1%5Cu00a06.10%2C%20p%5Cu00a0%3D%5Cu00a00.038%29%2C%20a%20subpart%20of%20the%20SN%20pars%20compacta%20%28SNc%29%20and%20ventral%20tegmental%20area%2C%20Putamen%2C%20Globus%20Pallidum%20external%2C%20accumbens%20nucleus%20and%20claustrum.%20Significantly%20increased%20QSM%20and%20R2%2A%20values%2C%20and%20decreased%20T1%20values%2C%20were%20limited%20to%20the%20Nigrosomes%201%20%28Nig%29%20and%20right%20SNc%20%28all%20p%5Cu00a0%26lt%3B%5Cu00a00.05%29.%20QSM%20values%20in%20the%20Nig%20were%20significantly%20correlated%20to%20UPDRS-III%20scores%20%28r%5Cu00a0%3D%5Cu00a00.91%2Cp%5Cu00a0%26lt%3B%5Cu00a00.001%29.%5CnCONCLUSION%3A%20In%20ePD%2C%20brain%20sodium%20accumulation%20was%20broad%20and%20dissociated%20from%20iron%20accumulation.%20As%20with%20iron%20accumulation%2C%20a%20sodium-related%20pathophysiological%20approach%20could%20lead%20to%20identifying%20potential%20new%20therapeutic%20agents%20and%20deserves%20further%20investigation.%22%2C%22date%22%3A%222024-05-06%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.parkreldis.2024.106996%22%2C%22ISSN%22%3A%221873-5126%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22UP3H3ICX%22%2C%22P66W67T8%22%2C%22DNKN89WD%22%2C%225P5FWCR9%22%2C%22F2AGIUQU%22%2C%22XTA6KS7L%22%2C%22H8UPCNQI%22%5D%2C%22dateModified%22%3A%222025-09-12T07%3A59%3A25Z%22%7D%7D%2C%7B%22key%22%3A%22GFN8IANH%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Tilsley%20et%20al.%22%2C%22parsedDate%22%3A%222024-04-01%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BTilsley%2C%20P.%2C%20Moutiez%2C%20A.%2C%20Brodovitch%2C%20A.%2C%20Mendili%2C%20M.M.E.%2C%20Testud%2C%20B.%2C%20Zaaraoui%2C%20W.%2C%20Verschueren%2C%20A.%2C%20Attarian%2C%20S.%2C%20Guye%2C%20M.%2C%20Boucraut%2C%20J.%2C%20Grapperon%2C%20A.-M.%20and%20Stellmann%2C%20J.-P.%20%282024%29%20%26%23x201C%3BNeurofilament%20Light%20Chain%20Levels%20Interact%20with%20Neurodegenerative%20Patterns%20and%20Motor%20Neuron%20Dysfunction%20in%20Amyotrophic%20Lateral%20Sclerosis%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BAmerican%20Journal%20of%20Neuroradiology%26lt%3B%5C%2Fi%26gt%3B%2C%2045%284%29%2C%20pp.%20494%26%23x2013%3B503.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3174%5C%2Fajnr.A8154%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3174%5C%2Fajnr.A8154%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Neurofilament%20Light%20Chain%20Levels%20Interact%20with%20Neurodegenerative%20Patterns%20and%20Motor%20Neuron%20Dysfunction%20in%20Amyotrophic%20Lateral%20Sclerosis%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Penelope%22%2C%22lastName%22%3A%22Tilsley%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Antoine%22%2C%22lastName%22%3A%22Moutiez%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexandre%22%2C%22lastName%22%3A%22Brodovitch%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mohamed%20Mounir%20El%22%2C%22lastName%22%3A%22Mendili%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Benoit%22%2C%22lastName%22%3A%22Testud%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Wafaa%22%2C%22lastName%22%3A%22Zaaraoui%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Annie%22%2C%22lastName%22%3A%22Verschueren%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shahram%22%2C%22lastName%22%3A%22Attarian%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jos%5Cu00e9%22%2C%22lastName%22%3A%22Boucraut%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Aude-Marie%22%2C%22lastName%22%3A%22Grapperon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan-Patrick%22%2C%22lastName%22%3A%22Stellmann%22%7D%5D%2C%22abstractNote%22%3A%22BACKGROUND%20AND%20PURPOSE%3A%20Amyotrophic%20lateral%20sclerosis%20%28ALS%29%20is%20a%20neurodegenerative%20disease%20involving%20rapid%20motor%20neuron%20degeneration%20leading%20to%20brain%2C%20primarily%20precentral%2C%20atrophy.%20Neurofilament%20light%20chains%20are%20a%20robust%20prognostic%20biomarker%20highly%20specific%20to%20ALS%2C%20yet%20associations%20between%20neurofilament%20light%20chains%20and%20MR%20imaging%20outcomes%20are%20not%20well-understood.%20We%20investigated%20the%20role%20of%20neurofilament%20light%20chains%20as%20mediators%20among%20neuroradiologic%20assessments%2C%20precentral%20neurodegeneration%2C%20and%20disability%20in%20ALS.%5CnMATERIALS%20AND%20METHODS%3A%20We%20retrospectively%20analyzed%20a%20prospective%20cohort%20of%2029%20patients%20with%20ALS%20%28mean%20age%2C%2056%20%5BSD%2C%2012%5D%20years%3B%2018%20men%29%20and%2036%20controls%20%28mean%20age%2C%2049%20%5BSD%2C%2011%5D%20years%3B%2018%20men%29.%20Patients%20underwent%203T%20%28n%20%3D%2019%29%20or%207T%20%28n%20%3D%2010%29%20MR%20imaging%2C%20serum%20%28n%20%3D%2023%29%20and%20CSF%20%28n%20%3D%2015%29%20neurofilament%20light%20chains%2C%20and%20clinical%20%28n%20%3D%2029%29%20and%20electrophysiologic%20%28n%20%3D%2027%29%20assessments.%20The%20control%20group%20had%20equivalent%203T%20%28n%20%3D%2025%29%20or%207T%20%28n%20%3D%2011%29%20MR%20imaging.%20Two%20trained%20neuroradiologists%20performed%20blinded%20qualitative%20assessments%20of%20MR%20imaging%20anomalies%20%28n%20%3D%2029%20patients%2C%20n%20%3D%2036%20controls%29.%20Associations%20between%20precentral%20cortical%20thickness%20and%20neurofilament%20light%20chains%20and%20clinical%20and%20electrophysiologic%20data%20were%20analyzed.%5CnRESULTS%3A%20We%20observed%20extensive%20cortical%20thinning%20in%20patients%20compared%20with%20controls.%20MR%20imaging%20analyses%20showed%20significant%20associations%20between%20precentral%20cortical%20thickness%20and%20bulbar%20or%20arm%20impairment%20following%20distributions%20corresponding%20to%20the%20motor%20homunculus.%20Finally%2C%20uncorrected%20results%20showed%20positive%20interactions%20among%20precentral%20cortical%20thickness%2C%20serum%20neurofilament%20light%20chains%2C%20and%20electrophysiologic%20outcomes.%20Qualitative%20MR%20imaging%20anomalies%20including%20global%20atrophy%20%28P%20%3D%20.003%29%20and%20FLAIR%20corticospinal%20tract%20hypersignal%20anomalies%20%28P%20%3D%20.033%29%2C%20correlated%20positively%20with%20serum%20neurofilament%20light%20chains.%5CnCONCLUSIONS%3A%20Serum%20neurofilament%20light%20chains%20may%20be%20an%20important%20mediator%20between%20clinical%20symptoms%20and%20neuronal%20loss%20according%20to%20cortical%20thickness.%20Furthermore%2C%20MR%20imaging%20anomalies%20might%20have%20underestimated%20prognostic%20value%20because%20they%20seem%20to%20indicate%20higher%20serum%20neurofilament%20light%20chain%20levels.%22%2C%22date%22%3A%222024%5C%2F04%5C%2F01%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.3174%5C%2Fajnr.A8154%22%2C%22ISSN%22%3A%220195-6108%2C%201936-959X%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.ajnr.org%5C%2Fcontent%5C%2F45%5C%2F4%5C%2F494%22%2C%22collections%22%3A%5B%22P66W67T8%22%2C%229L2KHJ5X%22%2C%22F2AGIUQU%22%2C%22XTA6KS7L%22%2C%22PCMV2W5C%22%2C%22S58TGFSV%22%5D%2C%22dateModified%22%3A%222025-09-19T07%3A45%3A54Z%22%7D%7D%2C%7B%22key%22%3A%22S67XSDCJ%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Testud%20et%20al.%22%2C%22parsedDate%22%3A%222024-03%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BTestud%2C%20B.%2C%20Carle%2C%20X.%2C%20Costes%2C%20C.%2C%20Hak%2C%20J.-F.%20and%20Guye%2C%20M.%20%282024%29%20%26%23x201C%3BAdded%20Value%20of%20Ultrahigh-Resolution%207T%20MRI%20in%20Dural%20Arteriovenous%20Fistulas%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BStroke%26lt%3B%5C%2Fi%26gt%3B%2C%2055%283%29%2C%20pp.%20e46%26%23x2013%3Be47.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1161%5C%2FSTROKEAHA.123.045930%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1161%5C%2FSTROKEAHA.123.045930%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Added%20Value%20of%20Ultrahigh-Resolution%207T%20MRI%20in%20Dural%20Arteriovenous%20Fistulas%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Benoit%22%2C%22lastName%22%3A%22Testud%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Xavier%22%2C%22lastName%22%3A%22Carle%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Claire%22%2C%22lastName%22%3A%22Costes%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Fran%5Cu00e7ois%22%2C%22lastName%22%3A%22Hak%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222024-03%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.1161%5C%2FSTROKEAHA.123.045930%22%2C%22ISSN%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.ahajournals.org%5C%2Fdoi%5C%2F10.1161%5C%2FSTROKEAHA.123.045930%22%2C%22collections%22%3A%5B%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-09-19T07%3A45%3A52Z%22%7D%7D%2C%7B%22key%22%3A%22G3L3VG3S%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Soustelle%20et%20al.%22%2C%22parsedDate%22%3A%222024%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BSoustelle%2C%20L.%2C%20Mchinda%2C%20S.%2C%20Hertanu%2C%20A.%2C%20Gherib%2C%20S.%2C%20Pini%2C%20L.%2C%20Guye%2C%20M.%2C%20Ranjeva%2C%20J.-P.%2C%20Varma%2C%20G.%2C%20Alsop%2C%20D.C.%2C%20Pelletier%2C%20J.%2C%20Girard%2C%20O.M.%20and%20Duhamel%2C%20G.%20%282024%29%20%26%23x201C%3BInhomogeneous%20magnetization%20transfer%20%28ihMT%29%20imaging%20reveals%20variable%20recovery%20profiles%20of%20active%20MS%20lesions%20according%20to%20size%20and%20localization%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BImaging%20Neuroscience%20%28Cambridge%2C%20Mass.%29%26lt%3B%5C%2Fi%26gt%3B%2C%202%2C%20p.%20imag%26%23x2013%3B2%26%23x2013%3B00235.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1162%5C%2Fimag_a_00235%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1162%5C%2Fimag_a_00235%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Inhomogeneous%20magnetization%20transfer%20%28ihMT%29%20imaging%20reveals%20variable%20recovery%20profiles%20of%20active%20MS%20lesions%20according%20to%20size%20and%20localization%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lucas%22%2C%22lastName%22%3A%22Soustelle%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Samira%22%2C%22lastName%22%3A%22Mchinda%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Andreea%22%2C%22lastName%22%3A%22Hertanu%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Soraya%22%2C%22lastName%22%3A%22Gherib%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lauriane%22%2C%22lastName%22%3A%22Pini%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Gopal%22%2C%22lastName%22%3A%22Varma%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%20C.%22%2C%22lastName%22%3A%22Alsop%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean%22%2C%22lastName%22%3A%22Pelletier%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Olivier%20M.%22%2C%22lastName%22%3A%22Girard%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Guillaume%22%2C%22lastName%22%3A%22Duhamel%22%7D%5D%2C%22abstractNote%22%3A%22This%20work%20aims%20at%20exploiting%20the%20unique%20myelin%20specificity%20of%20the%20inhomogeneous%20magnetization%20transfer%20%28ihMT%29%20technique%20to%20characterize%20the%20recovery%20dynamics%20of%20active%20multiple%20sclerosis%20%28MS%29%20lesions.%20IhMT%20and%20three%20other%20myelin-sensitive%20techniques%2C%20conventional%20MT%2C%20T1-weighted%2C%20and%20diffusion%20tensor%20imaging%2C%20were%20applied%20in%20a%2012-month%20longitudinal%20study%20performed%20on%20relapsing-remitting%20MS%20patients.%20An%20exponential%20recovery%20model%20was%20used%20to%20fit%20the%20variations%20over%20time%20of%20the%20metrics%20derived%20from%20each%20MR%20technique%20within%20new%20active%20lesions.%20A%20principal%20component%20analysis%20was%20performed%20on%20the%20model%20parameters%20obtained%20for%20all%20MR%20myelin-sensitive%20techniques%20across%20all%20active%20lesions%20of%20all%20patients%20to%20identify%20specific%20recovery%20profiles.%20The%20results%20show%20that%20the%20recovery%20profiles%20of%20myelin-sensitive%20MR%20metrics%20in%20active%20MS%20lesions%20vary%20according%20to%20the%20localization%20and%20size%20of%20lesions.%20The%20distance%20of%20lesions%20from%20the%20ventricles%20is%20positively%20associated%20with%20the%20recovery%20rates%20of%20ihMTR%20and%20T1w-MPRAGE%3A%20the%20further%20the%20lesion%20is%20from%20the%20ventricles%2C%20the%20higher%20the%20recovery%20rate%20of%20these%20metrics.%20Lesion%20size%20is%20positively%20associated%20with%20initial%20loss%20and%20negatively%20associated%20with%20final%20recovery%20of%20ihMTR%20and%20other%20MR%20metrics%3A%20small%20lesions%20have%20lower%20initial%20loss%20and%20greater%20final%20recovery%20of%20MR%20metrics%20than%20large%20lesions.%20Thanks%20to%20the%20specificity%20of%20the%20ihMT%20technique%20for%20myelin%2C%20these%20features%20can%20be%20interpreted%20in%20terms%20of%20remyelination.%20This%20study%20thus%20provides%20longitudinal%20in%20vivo%20support%20for%20the%20pathological%20observations%20of%20higher%20remyelination%20in%20small%20lesions%20compared%20with%20large%20ones%20and%20faster%20remyelination%20in%20lesions%20away%20from%20the%20ventricles.%20These%20results%20support%20the%20use%20of%20ihMT%20and%20other%20measures%20for%20quantifying%20remyelination%20rates%20in%20clinical%20studies%20of%20remyelination%20therapies.%22%2C%22date%22%3A%222024%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1162%5C%2Fimag_a_00235%22%2C%22ISSN%22%3A%222837-6056%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%2274RX9758%22%2C%224U7D3E9U%22%2C%22UP3H3ICX%22%2C%22B4EWFM7E%22%2C%22YXS7B6S7%22%2C%22M2AY8I5W%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-11-27T09%3A21%3A05Z%22%7D%7D%2C%7B%22key%22%3A%226WAQBTQL%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Lemar%5Cu00e9chal%20et%20al.%22%2C%22parsedDate%22%3A%222024%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BLemar%26%23xE9%3Bchal%2C%20J.-D.%2C%20Triebkorn%2C%20P.%2C%20Vattikonda%2C%20A.N.%2C%20Hashemi%2C%20M.%2C%20Woodman%2C%20M.%2C%20Guye%2C%20M.%2C%20Bartolomei%2C%20F.%2C%20Wang%2C%20H.E.%20and%20Jirsa%2C%20V.%20%282024%29%20%26%23x201C%3BEffects%20of%20the%20spatial%20resolution%20of%20the%20Virtual%20Epileptic%20Patient%20on%20the%20identification%20of%20epileptogenic%20networks%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BImaging%20Neuroscience%20%28Cambridge%2C%20Mass.%29%26lt%3B%5C%2Fi%26gt%3B%2C%202%2C%20p.%20imag%26%23x2013%3B2%26%23x2013%3B00153.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1162%5C%2Fimag_a_00153%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1162%5C%2Fimag_a_00153%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Effects%20of%20the%20spatial%20resolution%20of%20the%20Virtual%20Epileptic%20Patient%20on%20the%20identification%20of%20epileptogenic%20networks%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Didier%22%2C%22lastName%22%3A%22Lemar%5Cu00e9chal%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Paul%22%2C%22lastName%22%3A%22Triebkorn%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anirudh%20Nihalani%22%2C%22lastName%22%3A%22Vattikonda%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Meysam%22%2C%22lastName%22%3A%22Hashemi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marmaduke%22%2C%22lastName%22%3A%22Woodman%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabrice%22%2C%22lastName%22%3A%22Bartolomei%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Huifang%20E.%22%2C%22lastName%22%3A%22Wang%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Viktor%22%2C%22lastName%22%3A%22Jirsa%22%7D%5D%2C%22abstractNote%22%3A%22Digital%20twins%20play%20an%20increasing%20role%20in%20clinical%20decision%20making.%20This%20study%20evaluates%20a%20digital%20brain%20twin%20approach%20in%20presurgical%20evaluation%2C%20the%20Virtual%20Epileptic%20Patient%20%28VEP%29%2C%20which%20estimates%20the%20epileptogenic%20zone%20in%20patients%20with%20drug-resistant%20epilepsy.%20We%20built%20the%20personalized%20digital%20brain%20twins%20of%2014%20patients%20and%20a%20series%20of%20synthetic%20dataset%20by%20considering%20different%20spatial%20configurations%20of%20the%20epileptogenic%20and%5C%2For%20propagation%20zone%20networks%20%28EZN%20and%20PZN%2C%20respectively%29.%20Brain%20source%20signals%20were%20simulated%20with%20a%20high%20spatial%20resolution%20neural%20field%20model%20%28NFM%29%20composed%20of%2081942%20nodes%2C%20embedding%20both%20long-range%20%28between%20brain%20regions%29%20and%20short-range%20%28within%20brain%20regions%29%20coupling.%20Brain%20signals%20were%20then%20projected%20to%20stereotactic%20electroencephalographic%20%28SEEG%29%20contacts%20with%20an%20accurate%20forward%20solution.%20An%20inversion%20procedure%20based%20on%20a%20low%20spatial%20resolution%20neural%20mass%20model%20%28NMM%29%20composed%20of%20162%20nodes%20was%20applied%20to%20estimate%20the%20excitability%20of%20each%20region%20in%20each%20simulation.%20The%20ensuing%20estimated%20EZN%5C%2FPZN%20was%20compared%20to%20the%20simulated%20ground%20truth%20by%20means%20of%20classification%20metrics.%20Overall%2C%20we%20observed%20correct%20but%20degraded%20performance%20when%20using%20an%20NMM%20to%20estimate%20the%20EZN%20from%20data%20simulated%20with%20an%20NFM%2C%20which%20was%20significant%20for%20the%20simplest%20spatial%20configurations.%20We%20quantified%20the%20reduced%20performance%20and%20demonstrated%20that%20the%20oversimplification%20of%20the%20forward%20problem%20is%20its%20principal%20cause.%20We%20showed%20that%20the%20absence%20of%20local%20coupling%20in%20the%20NMM%20affects%20the%20inversion%20process%20by%20an%20overestimation%20of%20the%20excitability%2C%20representing%20a%20significant%20clinical%20impact%20when%20using%20this%20procedure%20in%20the%20context%20of%20presurgical%20planning.%20In%20conclusion%2C%20this%20study%20highlighted%20the%20importance%20to%20shift%20from%20an%20NMM%20towards%20a%20full%20NFM%20modeling%20approach%20for%20the%20estimation%20of%20EZN%2C%20with%20a%20particularly%20relevant%20need%20when%20considering%20the%20most%20complex%20clinical%20cases.%22%2C%22date%22%3A%222024%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1162%5C%2Fimag_a_00153%22%2C%22ISSN%22%3A%222837-6056%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-11-21T09%3A20%3A41Z%22%7D%7D%2C%7B%22key%22%3A%22KM8PBXBP%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Licht%20et%20al.%22%2C%22parsedDate%22%3A%222024%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BLicht%2C%20C.%2C%20Reichert%2C%20S.%2C%20Bydder%2C%20M.%2C%20Zapp%2C%20J.%2C%20Corella%2C%20S.%2C%20Guye%2C%20M.%2C%20Z%26%23xF6%3Bllner%2C%20F.G.%2C%20Schad%2C%20L.R.%20and%20Rapacchi%2C%20S.%20%282024%29%20%26%23x201C%3BLow-rank%20reconstruction%20for%20simultaneous%20double%20half-echo%2023Na%20and%20undersampled%2023Na%20multi-quantum%20coherences%20MRI%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BMagnetic%20Resonance%20in%20Medicine%26lt%3B%5C%2Fi%26gt%3B%2C%2092%284%29%2C%20pp.%201440%26%23x2013%3B1455.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fmrm.30132%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fmrm.30132%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Low-rank%20reconstruction%20for%20simultaneous%20double%20half-echo%2023Na%20and%20undersampled%2023Na%20multi-quantum%20coherences%20MRI%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christian%22%2C%22lastName%22%3A%22Licht%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Simon%22%2C%22lastName%22%3A%22Reichert%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mark%22%2C%22lastName%22%3A%22Bydder%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jascha%22%2C%22lastName%22%3A%22Zapp%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shirley%22%2C%22lastName%22%3A%22Corella%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Frank%20G.%22%2C%22lastName%22%3A%22Z%5Cu00f6llner%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lothar%20R.%22%2C%22lastName%22%3A%22Schad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stanislas%22%2C%22lastName%22%3A%22Rapacchi%22%7D%5D%2C%22abstractNote%22%3A%22Purpose%20To%20develop%20a%20new%20sequence%20to%20simultaneously%20acquire%20Cartesian%20sodium%20%2823Na%29%20MRI%20and%20accelerated%20Cartesian%20single%20%28SQ%29%20and%20triple%20quantum%20%28TQ%29%20sodium%20MRI%20of%20in%20vivo%20human%20brain%20at%207%20T%20by%20leveraging%20two%20dedicated%20low-rank%20reconstruction%20frameworks.%20Theory%20and%20Methods%20The%20Double%20Half-Echo%20technique%20enables%20short%20echo%20time%20Cartesian%2023Na%20MRI%20and%20acquires%20two%20k-space%20halves%2C%20reconstructed%20by%20a%20low-rank%20coupling%20constraint.%20Additionally%2C%20three-dimensional%20%283D%29%2023Na%20Multi-Quantum%20Coherences%20%28MQC%29%20MRI%20requires%20multi-echo%20sampling%20paired%20with%20phase-cycling%2C%20exhibiting%20a%20redundant%20multidimensional%20space.%20Simultaneous%20Autocalibrating%20and%20k-Space%20Estimation%20%28SAKE%29%20were%20used%20to%20reconstruct%20highly%20undersampled%2023Na%20MQC%20MRI.%20Reconstruction%20performance%20was%20assessed%20against%20five-dimensional%20%285D%29%20CS%2C%20evaluating%20structural%20similarity%20index%20%28SSIM%29%2C%20root%20mean%20squared%20error%20%28RMSE%29%2C%20signal-to-noise%20ratio%20%28SNR%29%2C%20and%20quantification%20of%20tissue%20sodium%20concentration%20and%20TQ%5C%2FSQ%20ratio%20in%20silico%2C%20in%20vitro%2C%20and%20in%20vivo.%20Results%20The%20proposed%20sequence%20enabled%20the%20simultaneous%20acquisition%20of%20fully%20sampled%2023Na%20MRI%20while%20leveraging%20prospective%20undersampling%20for%2023Na%20MQC%20MRI.%20SAKE%20improved%20TQ%20image%20reconstruction%20regarding%20SSIM%20by%206%25%20and%20reduced%20RMSE%20by%2035%25%20compared%20to%205D%20CS%20in%20vivo.%20Thanks%20to%20prospective%20undersampling%2C%20the%20spatial%20resolution%20of%2023Na%20MQC%20MRI%20was%20enhanced%20from%208%5Cu00d78%5Cu00d715%5C%5C%208%5C%5Ctimes%208%5C%5Ctimes%2015%20%5C%5C%20mm3%20to%208%5Cu00d78%5Cu00d78%5C%5C%208%5C%5Ctimes%208%5C%5Ctimes%208%20%5C%5C%20mm3%20while%20reducing%20acquisition%20time%20from%202%5Cu00d731%5C%5C%202%5C%5Ctimes%2031%20%5C%5C%20min%20to%202%5Cu00d723%5C%5C%202%5C%5Ctimes%2023%20%5C%5C%20min.%20Conclusion%20The%20proposed%20sequence%2C%20coupled%20with%20low-rank%20reconstructions%2C%20provides%20an%20efficient%20framework%20for%20comprehensive%20whole-brain%20sodium%20MRI%2C%20combining%20TSC%2C%20T2%2A%2C%20and%20TQ%5C%2FSQ%20ratio%20estimations.%20Additionally%2C%20low-rank%20matrix%20completion%20enables%20the%20reconstruction%20of%20highly%20undersampled%2023Na%20MQC%20MRI%2C%20allowing%20for%20accelerated%20acquisition%20or%20enhanced%20spatial%20resolution.%22%2C%22date%22%3A%222024%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.1002%5C%2Fmrm.30132%22%2C%22ISSN%22%3A%221522-2594%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fonlinelibrary.wiley.com%5C%2Fdoi%5C%2Fabs%5C%2F10.1002%5C%2Fmrm.30132%22%2C%22collections%22%3A%5B%22SK6VWU7K%22%5D%2C%22dateModified%22%3A%222025-09-12T07%3A59%3A38Z%22%7D%7D%2C%7B%22key%22%3A%22Q3KH8WBU%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Licht%20et%20al.%22%2C%22parsedDate%22%3A%222024%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BLicht%2C%20C.%2C%20Reichert%2C%20S.%2C%20Guye%2C%20M.%2C%20Schad%2C%20L.R.%20and%20Rapacchi%2C%20S.%20%282024%29%20%26%23x201C%3BMultidimensional%20compressed%20sensing%20to%20advance%2023Na%20multi-quantum%20coherences%20MRI%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BMagnetic%20Resonance%20in%20Medicine%26lt%3B%5C%2Fi%26gt%3B%2C%2091%283%29%2C%20pp.%20926%26%23x2013%3B941.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fmrm.29902%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fmrm.29902%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Multidimensional%20compressed%20sensing%20to%20advance%2023Na%20multi-quantum%20coherences%20MRI%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christian%22%2C%22lastName%22%3A%22Licht%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Simon%22%2C%22lastName%22%3A%22Reichert%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lothar%20R.%22%2C%22lastName%22%3A%22Schad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stanislas%22%2C%22lastName%22%3A%22Rapacchi%22%7D%5D%2C%22abstractNote%22%3A%22Purpose%20Sodium%20%2823Na%29%20multi-quantum%20coherences%20%28MQC%29%20MRI%20was%20accelerated%20using%20three-dimensional%20%283D%29%20and%20a%20dedicated%20five-dimensional%20%285D%29%20compressed%20sensing%20%28CS%29%20framework%20for%20simultaneous%20Cartesian%20single%20%28SQ%29%20and%20triple%20quantum%20%28TQ%29%20sodium%20imaging%20of%20in%20vivo%20human%20brain%20at%203.0%20and%207.0%20T.%20Theory%20and%20Methods%203D%2023Na%20MQC%20MRI%20requires%20multi-echo%20paired%20with%20phase-cycling%20and%20exhibits%20thus%20a%20multidimensional%20space.%20A%20joint%20reconstruction%20framework%20to%20exploit%20the%20sparsity%20in%20all%20imaging%20dimensions%20by%20extending%20the%20conventional%203D%20CS%20framework%20to%205D%20was%20developed.%203D%20MQC%20images%20of%20simulated%20brain%2C%20phantom%20and%20healthy%20brain%20volunteers%20obtained%20from%203.0%20T%20and%207.0%20T%20were%20retrospectively%20and%20prospectively%20undersampled.%20Performance%20of%20the%20CS%20models%20were%20analyzed%20by%20means%20of%20structural%20similarity%20index%20%28SSIM%29%2C%20root%20mean%20squared%20error%20%28RMSE%29%2C%20signal-to-noise%20ratio%20%28SNR%29%20and%20signal%20quantification%20of%20tissue%20sodium%20concentration%20and%20TQ%5C%2FSQ%20ratio.%20Results%20It%20was%20shown%20that%20an%20acceleration%20of%20three-fold%2C%20leading%20to%20less%20than%202%5Cu00d710%5C%5C%202%5C%5Ctimes%2010%20%5C%5C%20min%20of%20scan%20time%20with%20a%20resolution%20of%208%5Cu00d78%5Cu00d720%20mm3%5C%5C%208%5C%5Ctimes%208%5C%5Ctimes%2020%5C%5C%3B%5C%5Cmathrmmm%5E3%20%5C%5C%20at%203.0%20T%2C%20are%20possible.%205D%20CS%20improved%20SSIM%20by%203%25%2C%205%25%2C%201%25%20and%20reduced%20RMSE%20by%2050%25%2C%2030%25%2C%208%25%20for%20in%20vivo%20SQ%2C%20TQ%2C%20and%20TQ%5C%2FSQ%20ratio%20maps%2C%20respectively.%20Furthermore%2C%20for%20the%20first%20time%20prospective%20undersampling%20enabled%20unprecedented%20high%20resolution%20from%208%5Cu00d78%5Cu00d720%20mm3%5C%5C%208%5C%5Ctimes%208%5C%5Ctimes%2020%5C%5C%3B%5C%5Cmathrmmm%5E3%20%5C%5C%20to%206%5Cu00d76%5Cu00d710%20mm3%5C%5C%206%5C%5Ctimes%206%5C%5Ctimes%2010%5C%5C%3B%5C%5Cmathrmmm%5E3%20%5C%5C%20MQC%20images%20of%20in%20vivo%20human%20brain%20at%207.0%20T%20without%20extending%20acquisition%20time.%20Conclusion%205D%20CS%20proved%20to%20allow%20up%20to%20three-fold%20acceleration%20retrospectively%20on%203.0%20T%20data.%202-fold%20acceleration%20was%20demonstrated%20prospectively%20at%207.0%20T%20to%20reach%20higher%20spatial%20resolution%20of%2023Na%20MQC%20MRI.%22%2C%22date%22%3A%222024%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.1002%5C%2Fmrm.29902%22%2C%22ISSN%22%3A%221522-2594%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fonlinelibrary.wiley.com%5C%2Fdoi%5C%2Fabs%5C%2F10.1002%5C%2Fmrm.29902%22%2C%22collections%22%3A%5B%22SK6VWU7K%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-09-12T07%3A59%3A37Z%22%7D%7D%2C%7B%22key%22%3A%227SBFFHCG%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Azilinon%20et%20al.%22%2C%22parsedDate%22%3A%222024%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BAzilinon%2C%20M.%2C%20Wang%2C%20H.E.%2C%20Makhalova%2C%20J.%2C%20Zaaraoui%2C%20W.%2C%20Ranjeva%2C%20J.-P.%2C%20Bartolomei%2C%20F.%2C%20Guye%2C%20M.%20and%20Jirsa%2C%20V.%20%282024%29%20%26%23x201C%3BBrain%20sodium%20MRI-derived%20priors%20support%20the%20estimation%20of%20epileptogenic%20zones%20using%20personalized%20model-based%20methods%20in%20epilepsy%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BNetwork%20Neuroscience%20%28Cambridge%2C%20Mass.%29%26lt%3B%5C%2Fi%26gt%3B%2C%208%283%29%2C%20pp.%20673%26%23x2013%3B696.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1162%5C%2Fnetn_a_00371%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1162%5C%2Fnetn_a_00371%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Brain%20sodium%20MRI-derived%20priors%20support%20the%20estimation%20of%20epileptogenic%20zones%20using%20personalized%20model-based%20methods%20in%20epilepsy%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mikhael%22%2C%22lastName%22%3A%22Azilinon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Huifang%20E.%22%2C%22lastName%22%3A%22Wang%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Julia%22%2C%22lastName%22%3A%22Makhalova%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Wafaa%22%2C%22lastName%22%3A%22Zaaraoui%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabrice%22%2C%22lastName%22%3A%22Bartolomei%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Viktor%22%2C%22lastName%22%3A%22Jirsa%22%7D%5D%2C%22abstractNote%22%3A%22Patients%20presenting%20with%20drug-resistant%20epilepsy%20are%20eligible%20for%20surgery%20aiming%20to%20remove%20the%20regions%20involved%20in%20the%20production%20of%20seizure%20activities%2C%20the%20so-called%20epileptogenic%20zone%20network%20%28EZN%29.%20Thus%20the%20accurate%20estimation%20of%20the%20EZN%20is%20crucial.%20Data-driven%2C%20personalized%20virtual%20brain%20models%20derived%20from%20patient-specific%20anatomical%20and%20functional%20data%20are%20used%20in%20Virtual%20Epileptic%20Patient%20%28VEP%29%20to%20estimate%20the%20EZN%20via%20optimization%20methods%20from%20Bayesian%20inference.%20The%20Bayesian%20inference%20approach%20used%20in%20previous%20VEP%20integrates%20priors%2C%20based%20on%20the%20features%20of%20stereotactic-electroencephalography%20%28SEEG%29%20seizures%26%23039%3B%20recordings.%20Here%2C%20we%20propose%20new%20priors%2C%20based%20on%20quantitative%2023Na-MRI.%20The%2023Na-MRI%20data%20were%20acquired%20at%207T%20and%20provided%20several%20features%20characterizing%20the%20sodium%20signal%20decay.%20The%20hypothesis%20is%20that%20the%20sodium%20features%20are%20biomarkers%20of%20neuronal%20excitability%20related%20to%20the%20EZN%20and%20will%20add%20additional%20information%20to%20VEP%20estimation.%20In%20this%20paper%2C%20we%20first%20proposed%20the%20mapping%20from%2023Na-MRI%20features%20to%20predict%20the%20EZN%20via%20a%20machine%20learning%20approach.%20Then%2C%20we%20exploited%20these%20predictions%20as%20priors%20in%20the%20VEP%20pipeline.%20The%20statistical%20results%20demonstrated%20that%20compared%20with%20the%20results%20from%20current%20VEP%2C%20the%20result%20from%20VEP%20based%20on%2023Na-MRI%20prior%20has%20better%20balanced%20accuracy%2C%20and%20the%20similar%20weighted%20harmonic%20mean%20of%20the%20precision%20and%20recall.%22%2C%22date%22%3A%222024%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1162%5C%2Fnetn_a_00371%22%2C%22ISSN%22%3A%222472-1751%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22UP3H3ICX%22%2C%22P66W67T8%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-09-12T07%3A59%3A21Z%22%7D%7D%2C%7B%22key%22%3A%226URKI6GE%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Wirsich%20et%20al.%22%2C%22parsedDate%22%3A%222024%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BWirsich%2C%20J.%2C%20Iannotti%2C%20G.R.%2C%20Ridley%2C%20B.%2C%20Shamshiri%2C%20E.A.%2C%20Sheybani%2C%20L.%2C%20Grouiller%2C%20F.%2C%20Bartolomei%2C%20F.%2C%20Seeck%2C%20M.%2C%20Lazeyras%2C%20F.%2C%20Ranjeva%2C%20J.-P.%2C%20Guye%2C%20M.%20and%20Vulliemoz%2C%20S.%20%282024%29%20%26%23x201C%3BAltered%20correlation%20of%20concurrently%20recorded%20EEG-fMRI%20connectomes%20in%20temporal%20lobe%20epilepsy%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BNetwork%20Neuroscience%20%28Cambridge%2C%20Mass.%29%26lt%3B%5C%2Fi%26gt%3B%2C%208%282%29%2C%20pp.%20466%26%23x2013%3B485.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1162%5C%2Fnetn_a_00362%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1162%5C%2Fnetn_a_00362%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Altered%20correlation%20of%20concurrently%20recorded%20EEG-fMRI%20connectomes%20in%20temporal%20lobe%20epilepsy%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jonathan%22%2C%22lastName%22%3A%22Wirsich%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Giannina%20Rita%22%2C%22lastName%22%3A%22Iannotti%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ben%22%2C%22lastName%22%3A%22Ridley%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Elhum%20A.%22%2C%22lastName%22%3A%22Shamshiri%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Laurent%22%2C%22lastName%22%3A%22Sheybani%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fr%5Cu00e9d%5Cu00e9ric%22%2C%22lastName%22%3A%22Grouiller%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabrice%22%2C%22lastName%22%3A%22Bartolomei%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Margitta%22%2C%22lastName%22%3A%22Seeck%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fran%5Cu00e7ois%22%2C%22lastName%22%3A%22Lazeyras%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Serge%22%2C%22lastName%22%3A%22Vulliemoz%22%7D%5D%2C%22abstractNote%22%3A%22Whole-brain%20functional%20connectivity%20networks%20%28connectomes%29%20have%20been%20characterized%20at%20different%20scales%20in%20humans%20using%20EEG%20and%20fMRI.%20Multimodal%20epileptic%20networks%20have%20also%20been%20investigated%2C%20but%20the%20relationship%20between%20EEG%20and%20fMRI%20defined%20networks%20on%20a%20whole-brain%20scale%20is%20unclear.%20A%20unified%20multimodal%20connectome%20description%2C%20mapping%20healthy%20and%20pathological%20networks%20would%20close%20this%20knowledge%20gap.%20Here%2C%20we%20characterize%20the%20spatial%20correlation%20between%20the%20EEG%20and%20fMRI%20connectomes%20in%20right%20and%20left%20temporal%20lobe%20epilepsy%20%28rTLE%5C%2FlTLE%29.%20From%20two%20centers%2C%20we%20acquired%20resting-state%20concurrent%20EEG-fMRI%20of%2035%20healthy%20controls%20and%2034%20TLE%20patients.%20EEG-fMRI%20data%20was%20projected%20into%20the%20Desikan%20brain%20atlas%2C%20and%20functional%20connectomes%20from%20both%20modalities%20were%20correlated.%20EEG%20and%20fMRI%20connectomes%20were%20moderately%20correlated.%20This%20correlation%20was%20increased%20in%20rTLE%20when%20compared%20to%20controls%20for%20EEG-delta%5C%2Ftheta%5C%2Falpha%5C%2Fbeta.%20Conversely%2C%20multimodal%20correlation%20in%20lTLE%20was%20decreased%20in%20respect%20to%20controls%20for%20EEG-beta.%20While%20the%20alteration%20was%20global%20in%20rTLE%2C%20in%20lTLE%20it%20was%20locally%20linked%20to%20the%20default%20mode%20network.%20The%20increased%20multimodal%20correlation%20in%20rTLE%20and%20decreased%20correlation%20in%20lTLE%20suggests%20a%20modality-specific%20lateralized%20differential%20reorganization%20in%20TLE%2C%20which%20needs%20to%20be%20considered%20when%20comparing%20results%20from%20different%20modalities.%20Each%20modality%20provides%20distinct%20information%2C%20highlighting%20the%20benefit%20of%20multimodal%20assessment%20in%20epilepsy.%22%2C%22date%22%3A%222024%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1162%5C%2Fnetn_a_00362%22%2C%22ISSN%22%3A%222472-1751%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22UP3H3ICX%22%2C%22HVJZKIZG%22%2C%22NF6MTH8W%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-09-12T07%3A59%3A18Z%22%7D%7D%2C%7B%22key%22%3A%223U764DN9%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Daud%5Cu00e9%20et%20al.%22%2C%22parsedDate%22%3A%222024%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BDaud%26%23xE9%3B%2C%20P.%2C%20Roussel%2C%20T.%2C%20Troalen%2C%20T.%2C%20Viout%2C%20P.%2C%20Hernando%2C%20D.%2C%20Guye%2C%20M.%2C%20Kober%2C%20F.%2C%20Confort%20Gouny%2C%20S.%2C%20Bernard%2C%20M.%20and%20Rapacchi%2C%20S.%20%282024%29%20%26%23x201C%3BComparative%20review%20of%20algorithms%20and%20methods%20for%20chemical-shift-encoded%20quantitative%20fat-water%20imaging%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BMagnetic%20Resonance%20in%20Medicine%26lt%3B%5C%2Fi%26gt%3B%2C%2091%282%29%2C%20pp.%20741%26%23x2013%3B759.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fmrm.29860%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fmrm.29860%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Comparative%20review%20of%20algorithms%20and%20methods%20for%20chemical-shift-encoded%20quantitative%20fat-water%20imaging%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Pierre%22%2C%22lastName%22%3A%22Daud%5Cu00e9%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tangi%22%2C%22lastName%22%3A%22Roussel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Troalen%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Patrick%22%2C%22lastName%22%3A%22Viout%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Diego%22%2C%22lastName%22%3A%22Hernando%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Frank%22%2C%22lastName%22%3A%22Kober%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sylviane%22%2C%22lastName%22%3A%22Confort%20Gouny%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Monique%22%2C%22lastName%22%3A%22Bernard%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stanislas%22%2C%22lastName%22%3A%22Rapacchi%22%7D%5D%2C%22abstractNote%22%3A%22Purpose%20To%20propose%20a%20standardized%20comparison%20between%20state-of-the-art%20open-source%20fat-water%20separation%20algorithms%20for%20proton%20density%20fat%20fraction%20%28PDFF%29%20and%20R2%2A%5C%5C%20R_2%5E%5C%5Cast%20%5C%5C%20quantification%20using%20an%20open-source%20multi-language%20toolbox.%20Methods%20Eight%20recent%20open-source%20fat-water%20separation%20algorithms%20were%20compared%20in%20silico%2C%20in%20vitro%2C%20and%20in%20vivo.%20Multi-echo%20data%20were%20synthesized%20with%20varying%20fat-fractions%2C%20B0%20off-resonance%2C%20SNR%20and%20TEs.%20Experimental%20evaluation%20was%20conducted%20using%20calibrated%20fat-water%20phantoms%20acquired%20at%203T%20and%20multi-site%20open-source%20phantoms%20data.%20Algorithms%26%23039%3B%20performances%20were%20observed%20on%20challenging%20in%20vivo%20datasets%20at%203T.%20Finally%2C%20reconstruction%20algorithms%20were%20investigated%20with%20different%20fat%20spectra%20to%20evaluate%20the%20importance%20of%20the%20fat%20model.%20Results%20In%20silico%20and%20in%20vitro%20results%20proved%20most%20algorithms%20to%20be%20not%20sensitive%20to%20fat-water%20swaps%20and%20B0%5C%5C%20%5C%5CmathrmB_0%20%5C%5C%20offsets%20with%20five%20or%20more%20echoes.%20However%2C%20two%20methods%20remained%20inaccurate%20even%20with%20seven%20echoes%20and%20SNR%20%3D%2050%2C%20and%20two%20other%20algorithms%26%23039%3B%20precision%20depended%20on%20the%20echo%20spacing%20scheme%20%28p%20%26lt%3B%200.05%29.%20The%20remaining%20four%20algorithms%20provided%20reliable%20performances%20with%20limits%20of%20agreement%20under%202%25%20for%20PDFF%20and%206%20s%5Cu22121%20for%20R2%2A%5C%5C%20R_2%5E%5C%5Cast%20%5C%5C.%20The%20choice%20of%20fat%20spectrum%20model%20influenced%20quantification%20of%20PDFF%20mildly%20%28%26lt%3B2%25%20bias%29%20and%20of%20R2%2A%5C%5C%20R_2%5E%5C%5Cast%20%5C%5C%20more%20severely%2C%20with%20errors%20up%20to%2020%20s%5Cu22121.%20Conclusion%20In%20promoting%20standardized%20comparisons%20of%20MRI-based%20fat%20and%20iron%20quantification%20using%20chemical-shift%20encoded%20multi-echo%20methods%2C%20this%20benchmark%20work%20has%20revealed%20some%20discrepancies%20between%20recent%20approaches%20for%20PDFF%20and%20R2%2A%5C%5C%20R_2%5E%5C%5Cast%20%5C%5C%20mapping.%20Explicit%20choices%20and%20parameterization%20of%20the%20fat-water%20algorithm%20appear%20necessary%20for%20reproducibility.%20This%20open-source%20toolbox%20further%20enables%20the%20user%20to%20optimize%20acquisition%20parameters%20by%20predicting%20algorithms%26%23039%3B%20margins%20of%20errors.%22%2C%22date%22%3A%222024%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.1002%5C%2Fmrm.29860%22%2C%22ISSN%22%3A%221522-2594%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fonlinelibrary.wiley.com%5C%2Fdoi%5C%2Fabs%5C%2F10.1002%5C%2Fmrm.29860%22%2C%22collections%22%3A%5B%227JR7EDKF%22%2C%226GBQDAVI%22%2C%225Z6CVJGB%22%2C%22SK6VWU7K%22%2C%22ACGLJ26R%22%2C%22XTA6KS7L%22%2C%22BR9D2SS4%22%5D%2C%22dateModified%22%3A%222025-09-12T07%3A59%3A14Z%22%7D%7D%2C%7B%22key%22%3A%22KDS6NM3P%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22El%20Mendili%20et%20al.%22%2C%22parsedDate%22%3A%222023-09-01%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BEl%20Mendili%2C%20M.M.%2C%20Verschueren%2C%20A.%2C%20Ranjeva%2C%20J.-P.%2C%20Guye%2C%20M.%2C%20Attarian%2C%20S.%2C%20Zaaraoui%2C%20W.%20and%20Grapperon%2C%20A.-M.%20%282023%29%20%26%23x201C%3BAssociation%20between%20brain%20and%20upper%20cervical%20spinal%20cord%20atrophy%20assessed%20by%20MRI%20and%20disease%20aggressiveness%20in%20amyotrophic%20lateral%20sclerosis%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BNeuroradiology%26lt%3B%5C%2Fi%26gt%3B%2C%2065%289%29%2C%20pp.%201395%26%23x2013%3B1403.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-ItemURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs00234-023-03191-0%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs00234-023-03191-0%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Association%20between%20brain%20and%20upper%20cervical%20spinal%20cord%20atrophy%20assessed%20by%20MRI%20and%20disease%20aggressiveness%20in%20amyotrophic%20lateral%20sclerosis%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mohamed%20Mounir%22%2C%22lastName%22%3A%22El%20Mendili%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Annie%22%2C%22lastName%22%3A%22Verschueren%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shahram%22%2C%22lastName%22%3A%22Attarian%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Wafaa%22%2C%22lastName%22%3A%22Zaaraoui%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Aude-Marie%22%2C%22lastName%22%3A%22Grapperon%22%7D%5D%2C%22abstractNote%22%3A%22To%20study%20the%20relative%20contributions%20of%20brain%20and%20upper%20cervical%20spinal%20cord%20compartmental%20atrophy%20to%20disease%20aggressiveness%20in%20amyotrophic%20lateral%20sclerosis%20%28ALS%29.%22%2C%22date%22%3A%222023-09-01%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.1007%5C%2Fs00234-023-03191-0%22%2C%22ISSN%22%3A%221432-1920%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs00234-023-03191-0%22%2C%22collections%22%3A%5B%22UP3H3ICX%22%2C%22P66W67T8%22%2C%22F2AGIUQU%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222024-10-15T14%3A44%3A33Z%22%7D%7D%2C%7B%22key%22%3A%22HL5B8A5J%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Testud%20et%20al.%22%2C%22parsedDate%22%3A%222023-09%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BTestud%2C%20B.%2C%20Fabiani%2C%20N.%2C%20Demorti%26%23xE8%3Bre%2C%20S.%2C%20Mchinda%2C%20S.%2C%20Medina%2C%20N.L.%2C%20Pelletier%2C%20J.%2C%20Guye%2C%20M.%2C%20Audoin%2C%20B.%2C%20Stellmann%2C%20J.P.%20and%20Callot%2C%20V.%20%282023%29%20%26%23x201C%3BContribution%20of%20the%20MP2RAGE%207T%20Sequence%20in%20MS%20Lesions%20of%20the%20Cervical%20Spinal%20Cord%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BAJNR.%20American%20journal%20of%20neuroradiology%26lt%3B%5C%2Fi%26gt%3B%2C%2044%289%29%2C%20pp.%201101%26%23x2013%3B1107.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3174%5C%2Fajnr.A7964%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3174%5C%2Fajnr.A7964%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Contribution%20of%20the%20MP2RAGE%207T%20Sequence%20in%20MS%20Lesions%20of%20the%20Cervical%20Spinal%20Cord%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22B.%22%2C%22lastName%22%3A%22Testud%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22N.%22%2C%22lastName%22%3A%22Fabiani%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22S.%22%2C%22lastName%22%3A%22Demorti%5Cu00e8re%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22S.%22%2C%22lastName%22%3A%22Mchinda%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22N.%20L.%22%2C%22lastName%22%3A%22Medina%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22J.%22%2C%22lastName%22%3A%22Pelletier%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22M.%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22B.%22%2C%22lastName%22%3A%22Audoin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22J.%20P.%22%2C%22lastName%22%3A%22Stellmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22V.%22%2C%22lastName%22%3A%22Callot%22%7D%5D%2C%22abstractNote%22%3A%22BACKGROUND%20AND%20PURPOSE%3A%20The%20detection%20of%20spinal%20cord%20lesions%20in%20patients%20with%20MS%20is%20challenging.%20Recently%2C%20the%203D%20MP2RAGE%20sequence%20demonstrated%20its%20usefulness%20at%203T.%20Benefiting%20from%20the%20high%20spatial%20resolution%20provided%20by%20ultra-high-field%20MR%20imaging%20systems%2C%20we%20aimed%20to%20evaluate%20the%20contribution%20of%20the%203D%20MP2RAGE%20sequence%20acquired%20at%207T%20for%20the%20detection%20of%20MS%20lesions%20in%20the%20cervical%20spine.%5CnMATERIALS%20AND%20METHODS%3A%20Seventeen%20patients%20with%20MS%20participated%20in%20this%20study.%20They%20were%20examined%20at%20both%203T%20and%207T.%20The%20MR%20imaging%20examination%20included%20a%20Magnetic%20Imaging%20in%20MS%20%28MAGNIMS%29%20protocol%20with%20an%20axial%20T2%2A-WI%20gradient%20recalled-echo%20sequence%20%28%26quot%3Boptimized%20MAGNIMS%20protocol%26quot%3B%29%20and%20a%200.9-mm%20isotropic%203D%20MP2RAGE%20sequence%20at%203T%2C%20as%20well%20as%20a%200.7-mm%20isotropic%20and%200.3-mm%20in-plane-resolution%20anisotropic%203D%20MP2RAGE%20sequences%20at%207T.%20Each%20data%20set%20was%20read%20by%20a%20consensus%20of%20radiologists%2C%20neurologists%2C%20and%20neuroscientists.%20The%20number%20of%20lesions%20and%20their%20topography%2C%20as%20well%20as%20the%20visibility%20of%20the%20lesions%20from%20one%20set%20to%20another%2C%20were%20carefully%20analyzed.%5CnRESULTS%3A%20A%20total%20of%2055%20lesions%20were%20detected.%20The%20absolute%20number%20of%20visible%20lesions%20differed%20among%20the%204%20sequences%20%28linear%20mixed%20effect%20ANOVA%2C%20P%20%3D%20.020%29.%20The%20highest%20detection%20was%20observed%20for%20the%20two%207T%20sequences%20with%2051%20lesions%20each%20%2892.7%25%20of%20the%20total%29.%20The%20optimized%203T%20MAGNIMS%20protocol%20and%20the%203T%20MP2RAGE%20isotropic%20sequence%20detected%2041%20%2874.5%25%29%20and%2035%20lesions%20%2863.6%25%29%2C%20respectively.%5CnCONCLUSIONS%3A%20The%207T%20MP2RAGE%20sequences%20detected%20more%20lesions%20than%20the%203T%20sets.%20Isotropic%20and%20anisotropic%20acquisitions%20performed%20comparably.%20Ultra-high-resolution%20sequences%20obtained%20at%207T%20improve%20the%20identification%20and%20delineation%20of%20lesions%20of%20the%20cervical%20spinal%20cord%20in%20MS.%22%2C%22date%22%3A%222023-09%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.3174%5C%2Fajnr.A7964%22%2C%22ISSN%22%3A%221936-959X%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22ZFC2Q648%22%2C%22B4EWFM7E%22%2C%226KPLZTET%22%2C%229L2KHJ5X%22%2C%22XTA6KS7L%22%2C%22PCMV2W5C%22%5D%2C%22dateModified%22%3A%222025-11-27T09%3A21%3A04Z%22%7D%7D%2C%7B%22key%22%3A%22VLDP9D4T%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Soustelle%20et%20al.%22%2C%22parsedDate%22%3A%222023-09%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BSoustelle%2C%20L.%2C%20Troalen%2C%20T.%2C%20Hertanu%2C%20A.%2C%20Ranjeva%2C%20J.-P.%2C%20Guye%2C%20M.%2C%20Varma%2C%20G.%2C%20Alsop%2C%20D.C.%2C%20Duhamel%2C%20G.%20and%20Girard%2C%20O.M.%20%282023%29%20%26%23x201C%3BQuantitative%20magnetization%20transfer%20MRI%20unbiased%20by%20on-resonance%20saturation%20and%20dipolar%20order%20contributions%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BMagnetic%20Resonance%20in%20Medicine%26lt%3B%5C%2Fi%26gt%3B%2C%2090%283%29%2C%20pp.%20875%26%23x2013%3B893.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fmrm.29678%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fmrm.29678%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Quantitative%20magnetization%20transfer%20MRI%20unbiased%20by%20on-resonance%20saturation%20and%20dipolar%20order%20contributions%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lucas%22%2C%22lastName%22%3A%22Soustelle%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Troalen%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Andreea%22%2C%22lastName%22%3A%22Hertanu%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Gopal%22%2C%22lastName%22%3A%22Varma%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%20C.%22%2C%22lastName%22%3A%22Alsop%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Guillaume%22%2C%22lastName%22%3A%22Duhamel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Olivier%20M.%22%2C%22lastName%22%3A%22Girard%22%7D%5D%2C%22abstractNote%22%3A%22PURPOSE%3A%20To%20demonstrate%20the%20bias%20in%20quantitative%20MT%20%28qMT%29%20measures%20introduced%20by%20the%20presence%20of%20dipolar%20order%20and%20on-resonance%20saturation%20%28ONRS%29%20effects%20using%20magnetization%20transfer%20%28MT%29%20spoiled%20gradient-recalled%20%28SPGR%29%20acquisitions%2C%20and%20propose%20changes%20to%20the%20acquisition%20and%20analysis%20strategies%20to%20remove%20these%20biases.%5CnMETHODS%3A%20The%20proposed%20framework%20consists%20of%20SPGR%20sequences%20prepared%20with%20simultaneous%20dual-offset%20frequency-saturation%20pulses%20to%20cancel%20out%20dipolar%20order%20and%20associated%20relaxation%20%28T1D%20%29%20effects%20in%20Z-spectrum%20acquisitions%2C%20and%20a%20matched%20quantitative%20MT%20%28qMT%29%20mathematical%20model%20that%20includes%20ONRS%20effects%20of%20readout%20pulses.%20Variable%20flip%20angle%20and%20MT%20data%20were%20fitted%20jointly%20to%20simultaneously%20estimate%20qMT%20parameters%20%28macromolecular%20proton%20fraction%20%5BMPF%5D%2C%20T2%2Cf%20%2C%20T2%2Cb%20%2C%20R%2C%20and%20free%20pool%20T1%20%29.%20This%20framework%20is%20compared%20with%20standard%20qMT%20and%20investigated%20in%20terms%20of%20reproducibility%2C%20and%20then%20further%20developed%20to%20follow%20a%20joint%20single-point%20qMT%20methodology%20for%20combined%20estimation%20of%20MPF%20and%20T1%20.%5CnRESULTS%3A%20Bland-Altman%20analyses%20demonstrated%20a%20systematic%20underestimation%20of%20MPF%20%28-2.5%25%20and%20-1.3%25%2C%20on%20average%2C%20in%20white%20and%20gray%20matter%2C%20respectively%29%20and%20overestimation%20of%20T1%20%2847.1%5Cu2009ms%20and%2038.6%5Cu2009ms%2C%20on%20average%2C%20in%20white%20and%20gray%20matter%2C%20respectively%29%20if%20both%20ONRS%20and%20dipolar%20order%20effects%20are%20ignored.%20Reproducibility%20of%20the%20proposed%20framework%20is%20excellent%20%28%5Cu0394MPF%5Cu2009%3D%5Cu2009-0.03%25%20and%20%5Cu0394T1%20%5Cu2009%3D%5Cu2009-19.0%5Cu2009ms%29.%20The%20single-point%20methodology%20yielded%20consistent%20MPF%20and%20T1%20values%20with%20respective%20maximum%20relative%20average%20bias%20of%20-0.15%25%20and%5Cu2009-3.5%5Cu2009ms%20found%20in%20white%20matter.%5CnCONCLUSION%3A%20The%20influence%20of%20acquisition%20strategy%20and%20matched%20mathematical%20model%20with%20regard%20to%20ONRS%20and%20dipolar%20order%20effects%20in%20qMT-SPGR%20frameworks%20has%20been%20investigated.%20The%20proposed%20framework%20holds%20promise%20for%20improved%20accuracy%20with%20reproducibility.%22%2C%22date%22%3A%222023-09%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1002%5C%2Fmrm.29678%22%2C%22ISSN%22%3A%221522-2594%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%2274RX9758%22%2C%224U7D3E9U%22%2C%226GBQDAVI%22%2C%22UP3H3ICX%22%2C%22M2AY8I5W%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222024-06-14T08%3A29%3A09Z%22%7D%7D%2C%7B%22key%22%3A%22DEPFSJYH%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Lee%20et%20al.%22%2C%22parsedDate%22%3A%222023-08-01%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BLee%2C%20H.M.%2C%20Hong%2C%20S.-J.%2C%20Gill%2C%20R.%2C%20Caldairou%2C%20B.%2C%20Wang%2C%20I.%2C%20Zhang%2C%20J.%2C%20Deleo%2C%20F.%2C%20Schrader%2C%20D.%2C%20Bartolomei%2C%20F.%2C%20Guye%2C%20M.%2C%20Cho%2C%20K.H.%2C%20Barba%2C%20C.%2C%20Sisodiya%2C%20S.%2C%20Jackson%2C%20G.%2C%20Hogan%2C%20R.E.%2C%20Wong-Kisiel%2C%20L.%2C%20Cascino%2C%20G.D.%2C%20Schulze-Bonhage%2C%20A.%2C%20Lopes-Cendes%2C%20I.%2C%20Cendes%2C%20F.%2C%20Guerrini%2C%20R.%2C%20Bernhardt%2C%20B.%2C%20Bernasconi%2C%20N.%20and%20Bernasconi%2C%20A.%20%282023%29%20%26%23x201C%3BMultimodal%20mapping%20of%20regional%20brain%20vulnerability%20to%20focal%20cortical%20dysplasia%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BBrain%26lt%3B%5C%2Fi%26gt%3B%2C%20146%288%29%2C%20pp.%203404%26%23x2013%3B3415.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-ItemURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1093%5C%2Fbrain%5C%2Fawad060%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1093%5C%2Fbrain%5C%2Fawad060%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Multimodal%20mapping%20of%20regional%20brain%20vulnerability%20to%20focal%20cortical%20dysplasia%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hyo%20M%22%2C%22lastName%22%3A%22Lee%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Seok-Jun%22%2C%22lastName%22%3A%22Hong%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ravnoor%22%2C%22lastName%22%3A%22Gill%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Benoit%22%2C%22lastName%22%3A%22Caldairou%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Irene%22%2C%22lastName%22%3A%22Wang%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jian-guo%22%2C%22lastName%22%3A%22Zhang%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Francesco%22%2C%22lastName%22%3A%22Deleo%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Dewi%22%2C%22lastName%22%3A%22Schrader%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabrice%22%2C%22lastName%22%3A%22Bartolomei%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Kyoo%20Ho%22%2C%22lastName%22%3A%22Cho%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Carmen%22%2C%22lastName%22%3A%22Barba%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sanjay%22%2C%22lastName%22%3A%22Sisodiya%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Graeme%22%2C%22lastName%22%3A%22Jackson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22R%20Edward%22%2C%22lastName%22%3A%22Hogan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lily%22%2C%22lastName%22%3A%22Wong-Kisiel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Gregory%20D%22%2C%22lastName%22%3A%22Cascino%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Andreas%22%2C%22lastName%22%3A%22Schulze-Bonhage%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Iscia%22%2C%22lastName%22%3A%22Lopes-Cendes%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fernando%22%2C%22lastName%22%3A%22Cendes%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Renzo%22%2C%22lastName%22%3A%22Guerrini%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Boris%22%2C%22lastName%22%3A%22Bernhardt%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Neda%22%2C%22lastName%22%3A%22Bernasconi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Andrea%22%2C%22lastName%22%3A%22Bernasconi%22%7D%5D%2C%22abstractNote%22%3A%22Focal%20cortical%20dysplasia%20%28FCD%29%20type%20II%20is%20a%20highly%20epileptogenic%20developmental%20malformation%20and%20a%20common%20cause%20of%20surgically%20treated%20drug-resistant%20epilepsy.%20While%20clinical%20observations%20suggest%20frequent%20occurrence%20in%20the%20frontal%20lobe%2C%20mechanisms%20for%20such%20propensity%20remain%20unexplored.%20Here%2C%20we%20hypothesized%20that%20cortex-wide%20spatial%20associations%20of%20FCD%20distribution%20with%20cortical%20cytoarchitecture%2C%20gene%20expression%20and%20organizational%20axes%20may%20offer%20complementary%20insights%20into%20processes%20that%20predispose%20given%20cortical%20regions%20to%20harbour%20FCD.We%20mapped%20the%20cortex-wide%20MRI%20distribution%20of%20FCDs%20in%20337%20patients%20collected%20from%2013%20sites%20worldwide.%20We%20then%20determined%20its%20associations%20with%20%28i%29%20cytoarchitectural%20features%20using%20histological%20atlases%20by%20Von%20Economo%20and%20Koskinas%20and%20BigBrain%3B%20%28ii%29%20whole-brain%20gene%20expression%20and%20spatiotemporal%20dynamics%20from%20prenatal%20to%20adulthood%20stages%20using%20the%20Allen%20Human%20Brain%20Atlas%20and%20PsychENCODE%20BrainSpan%3B%20and%20%28iii%29%20macroscale%20developmental%20axes%20of%20cortical%20organization.FCD%20lesions%20were%20preferentially%20located%20in%20the%20prefrontal%20and%20fronto-limbic%20cortices%20typified%20by%20low%20neuron%20density%2C%20large%20soma%20and%20thick%20grey%20matter.%20Transcriptomic%20associations%20with%20FCD%20distribution%20uncovered%20a%20prenatal%20component%20related%20to%20neuroglial%20proliferation%20and%20differentiation%2C%20likely%20accounting%20for%20the%20dysplastic%20makeup%2C%20and%20a%20postnatal%20component%20related%20to%20synaptogenesis%20and%20circuit%20organization%2C%20possibly%20contributing%20to%20circuit-level%20hyperexcitability.%20FCD%20distribution%20showed%20a%20strong%20association%20with%20the%20anterior%20region%20of%20the%20antero-posterior%20axis%20derived%20from%20heritability%20analysis%20of%20interregional%20structural%20covariance%20of%20cortical%20thickness%2C%20but%20not%20with%20structural%20and%20functional%20hierarchical%20axes.%20Reliability%20of%20all%20results%20was%20confirmed%20through%20resampling%20techniques.Multimodal%20associations%20with%20cytoarchitecture%2C%20gene%20expression%20and%20axes%20of%20cortical%20organization%20indicate%20that%20prenatal%20neurogenesis%20and%20postnatal%20synaptogenesis%20may%20be%20key%20points%20of%20developmental%20vulnerability%20of%20the%20frontal%20lobe%20to%20FCD.%20Concordant%20with%20a%20causal%20role%20of%20atypical%20neuroglial%20proliferation%20and%20growth%2C%20our%20results%20indicate%20that%20FCD-vulnerable%20cortices%20display%20properties%20indicative%20of%20earlier%20termination%20of%20neurogenesis%20and%20initiation%20of%20cell%20growth.%20They%20also%20suggest%20a%20potential%20contribution%20of%20aberrant%20postnatal%20synaptogenesis%20and%20circuit%20development%20to%20FCD%20epileptogenicity.%22%2C%22date%22%3A%222023-08-01%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.1093%5C%2Fbrain%5C%2Fawad060%22%2C%22ISSN%22%3A%220006-8950%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1093%5C%2Fbrain%5C%2Fawad060%22%2C%22collections%22%3A%5B%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222025-03-21T14%3A53%3A11Z%22%7D%7D%2C%7B%22key%22%3A%227FHVK5PB%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Guenoun%20et%20al.%22%2C%22parsedDate%22%3A%222023-08-01%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BGuenoun%2C%20D.%2C%20Wirth%2C%20T.%2C%20Roche%2C%20D.%2C%20Michel%2C%20C.P.%2C%20Daud%26%23xE9%3B%2C%20P.%2C%20Ogier%2C%20A.C.%2C%20Chagnaud%2C%20C.%2C%20Mattei%2C%20J.P.%2C%20Pini%2C%20L.%2C%20Guye%2C%20M.%2C%20Ollivier%2C%20M.%2C%20Bendahan%2C%20D.%20and%20Guis%2C%20S.%20%282023%29%20%26%23x201C%3BUltra-high%20field%20magnetic%20resonance%20imaging%20of%20the%20quadriceps%20tendon%20enthesis%20in%20healthy%20subjects%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BSurgical%20and%20Radiologic%20Anatomy%26lt%3B%5C%2Fi%26gt%3B%2C%2045%288%29%2C%20pp.%201049%26%23x2013%3B1054.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-ItemURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs00276-023-03175-y%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs00276-023-03175-y%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Ultra-high%20field%20magnetic%20resonance%20imaging%20of%20the%20quadriceps%20tendon%20enthesis%20in%20healthy%20subjects%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Daphne%22%2C%22lastName%22%3A%22Guenoun%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Theo%22%2C%22lastName%22%3A%22Wirth%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Damien%22%2C%22lastName%22%3A%22Roche%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Constance%20P.%22%2C%22lastName%22%3A%22Michel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Pierre%22%2C%22lastName%22%3A%22Daud%5Cu00e9%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Augustin%20C.%22%2C%22lastName%22%3A%22Ogier%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christophe%22%2C%22lastName%22%3A%22Chagnaud%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean%20Pierre%22%2C%22lastName%22%3A%22Mattei%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lauriane%22%2C%22lastName%22%3A%22Pini%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Matthieu%22%2C%22lastName%22%3A%22Ollivier%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Bendahan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sandrine%22%2C%22lastName%22%3A%22Guis%22%7D%5D%2C%22abstractNote%22%3A%22Although%20enthesitis%20is%20a%20hallmark%20of%20several%20rheumatologic%20conditions%2C%20current%20imaging%20methods%20are%20still%20unable%20to%20characterize%20entheses%20changes%20because%20of%20the%20corresponding%20short%20transverse%20relaxation%20times%20%28T2%29.%20A%20growing%20number%20of%20MR%20studies%20have%20used%20Ultra-High%20Field%20%28UHF%29%20MRI%20in%20order%20to%20assess%20low-T2%20tissues%20e.g.%2C%20tendon%20but%20never%20in%20humans.%20The%20purpose%20of%20the%20present%20study%20was%20to%20assess%20in%20vivo%20the%20enthesis%20of%20the%20quadriceps%20tendon%20in%20healthy%20subjects%20using%20UHF%20MRI.%22%2C%22date%22%3A%222023-08-01%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.1007%5C%2Fs00276-023-03175-y%22%2C%22ISSN%22%3A%221279-8517%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs00276-023-03175-y%22%2C%22collections%22%3A%5B%22NW6SZQBR%22%2C%226BEMAGEW%22%2C%2248SZ2I24%22%2C%22ZP8JD3DQ%22%2C%22ACGLJ26R%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222024-12-05T16%3A12%3A38Z%22%7D%7D%2C%7B%22key%22%3A%225BC5UBFM%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Graber%20et%20al.%22%2C%22parsedDate%22%3A%222023-07-20%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BGraber%2C%20M.%2C%20Cadour%2C%20F.%2C%20El%20Ahmadi%2C%20A.A.%2C%20Khati%2C%20I.%2C%20Del%20Grande%2C%20J.%2C%20Chagnaud%2C%20C.%2C%20Fakhry%2C%20N.%2C%20Guye%2C%20M.%20and%20Varoquaux%2C%20A.%20%282023%29%20%26%23x201C%3BAdding%20automated%20decision-tree%20models%20to%20multiparametric%20MRI%20for%20parotid%20tumours%20improves%20clinical%20performance%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BEuropean%20Journal%20of%20Radiology%26lt%3B%5C%2Fi%26gt%3B%2C%20166%2C%20p.%20110999.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.ejrad.2023.110999%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.ejrad.2023.110999%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Adding%20automated%20decision-tree%20models%20to%20multiparametric%20MRI%20for%20parotid%20tumours%20improves%20clinical%20performance%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Matthieu%22%2C%22lastName%22%3A%22Graber%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Farah%22%2C%22lastName%22%3A%22Cadour%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ahmed%20Ali%22%2C%22lastName%22%3A%22El%20Ahmadi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Idir%22%2C%22lastName%22%3A%22Khati%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean%22%2C%22lastName%22%3A%22Del%20Grande%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christophe%22%2C%22lastName%22%3A%22Chagnaud%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nicolas%22%2C%22lastName%22%3A%22Fakhry%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Arthur%22%2C%22lastName%22%3A%22Varoquaux%22%7D%5D%2C%22abstractNote%22%3A%22PURPOSE%3A%20Therapeutic%20management%20of%20parotid%20gland%20tumours%20depends%20on%20their%20histological%20type.%20To%20aid%20its%20characterisation%2C%20we%20sought%20to%20develop%20automated%20decision-tree%20models%20based%20on%20multiparametric%20magnetic%20resonance%20imaging%20%28MRI%29%20parameters%20and%20to%20evaluate%20their%20added%20diagnostic%20value%20compared%20with%20morphological%20sequences.%5CnMETHODS%3A%20206%20MRIs%20from%20206%20patients%20with%20histologically%20proven%20parotid%20gland%20tumours%20were%20included%20from%20January%202009%20to%20January%202018.%20Multiparametric%20MRI%20findings%20%28including%20parameters%20derived%20from%20diffusion-weighted%20imaging%20%5BDWI%5D%20and%20dynamic%20contrast-enhanced%20%5BDCE%5D%29%20were%20used%20to%20build%20predictive%20classification%20and%20regression%20tree%20%28CART%29%20models%20for%20each%20histological%20type.%20All%20MRIs%20were%20read%20twice%3A%20first%2C%20based%20on%20morphological%20sequence%20findings%20only%2C%20and%20second%2C%20with%20the%20addition%20of%20multiparametric%20sequences%20and%20CART%20findings.%20The%20diagnostic%20performance%20between%20these%20two%20readings%20was%20compared%20using%20ROC%20curves.%5CnRESULTS%3A%20Compared%20to%20morphological%20sequences%20alone%2C%20the%20addition%20of%20multiparametric%20analysis%20significantly%20increased%20the%20diagnostic%20performance%20for%20all%20histological%20types%20%28p%5Cu00a0%26lt%3B%5Cu00a00.001%20to%20p%5Cu00a0%3D%5Cu00a00.011%29%2C%20except%20for%20lymphomas%2C%20where%20the%20increase%20was%20not%20significant%20%28AUC%201.00%20vs.%200.99%2C%20p%5Cu00a0%3D%5Cu00a00.066%29.%20ADCmean%20was%20the%20best%20parameter%20to%20identify%20pleomorphic%20adenomas%2C%20carcinomas%20and%20lymphomas%20with%20respective%20cut-offs%20of%201.292%5Cu00a0%5Cu00d7%5Cu00a010-3%5Cu00a0mm2%5C%2Fs%2C%201.181%5Cu00a0%5Cu00d7%5Cu00a010-3%5Cu00a0mm2%5C%2Fs%20and%200.611%5Cu00a0%5Cu00d7%5Cu00a010-3%5Cu00a0mm2%5C%2Fs%2C%20respectively.%5Cu00a0%5Cu00d7%5Cu00a010-3%5Cu00a0mm2%5C%2Fs.%20The%20mean%20extracellular-extravascular%20space%20coefficient%20was%20the%20best%20parameter%20to%20Warthin%20tumours%20from%20the%20others%2C%20with%20a%20cut-off%20of%200.07.%5CnCONCLUSIONS%3A%20The%20addition%20of%20decision%20tree%20prediction%20models%20based%20on%20multiparametric%20sequences%20improves%20the%20non-invasive%20diagnostic%20performance%20of%20parotid%20gland%20tumours.%20ADC%20and%20extracellular-extravascular%20space%20coefficient%20are%20the%20two%20best%20parameters%20for%20decision%20making.%22%2C%22date%22%3A%222023-07-20%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.ejrad.2023.110999%22%2C%22ISSN%22%3A%221872-7727%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22XTA6KS7L%22%2C%22KBIRKXGV%22%5D%2C%22dateModified%22%3A%222025-03-21T14%3A55%3A10Z%22%7D%7D%2C%7B%22key%22%3A%229Y63LXT8%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Cadour%20et%20al.%22%2C%22parsedDate%22%3A%222023-02-06%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BCadour%2C%20F.%2C%20Quemeneur%2C%20M.%2C%20Biere%2C%20L.%2C%20Donal%2C%20E.%2C%20Bentatou%2C%20Z.%2C%20Eicher%2C%20J.-C.%2C%20Roubille%2C%20F.%2C%20Lalande%2C%20A.%2C%20Giorgi%2C%20R.%2C%20Rapacchi%2C%20S.%2C%20Cortaredona%2C%20S.%2C%20Tradi%2C%20F.%2C%20Bartoli%2C%20A.%2C%20Willoteaux%2C%20S.%2C%20Delahaye%2C%20F.%2C%20Biene%2C%20S.M.%2C%20Mangin%2C%20L.%2C%20Ferrier%2C%20N.%2C%20Dacher%2C%20J.-N.%2C%20Bauer%2C%20F.%2C%20Leurent%2C%20G.%2C%20Lentz%2C%20P.-A.%2C%20Kovacsik%2C%20H.%2C%20Croisille%2C%20P.%2C%20Thuny%2C%20F.%2C%20Bernard%2C%20M.%2C%20Guye%2C%20M.%2C%20Furber%2C%20A.%2C%20Habib%2C%20G.%20and%20Jacquier%2C%20A.%20%282023%29%20%26%23x201C%3BPrognostic%20value%20of%20cardiovascular%20magnetic%20resonance%20T1%20mapping%20and%20extracellular%20volume%20fraction%20in%20nonischemic%20dilated%20cardiomyopathy%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BJournal%20of%20Cardiovascular%20Magnetic%20Resonance%3A%20Official%20Journal%20of%20the%20Society%20for%20Cardiovascular%20Magnetic%20Resonance%26lt%3B%5C%2Fi%26gt%3B%2C%2025%281%29%2C%20p.%207.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1186%5C%2Fs12968-023-00919-y%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1186%5C%2Fs12968-023-00919-y%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Prognostic%20value%20of%20cardiovascular%20magnetic%20resonance%20T1%20mapping%20and%20extracellular%20volume%20fraction%20in%20nonischemic%20dilated%20cardiomyopathy%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Farah%22%2C%22lastName%22%3A%22Cadour%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Morgane%22%2C%22lastName%22%3A%22Quemeneur%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Loic%22%2C%22lastName%22%3A%22Biere%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Erwan%22%2C%22lastName%22%3A%22Donal%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Zakarya%22%2C%22lastName%22%3A%22Bentatou%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Christophe%22%2C%22lastName%22%3A%22Eicher%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fran%5Cu00e7ois%22%2C%22lastName%22%3A%22Roubille%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alain%22%2C%22lastName%22%3A%22Lalande%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Roch%22%2C%22lastName%22%3A%22Giorgi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stanislas%22%2C%22lastName%22%3A%22Rapacchi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22S%5Cu00e9bastien%22%2C%22lastName%22%3A%22Cortaredona%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Farouk%22%2C%22lastName%22%3A%22Tradi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Axel%22%2C%22lastName%22%3A%22Bartoli%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Serge%22%2C%22lastName%22%3A%22Willoteaux%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fran%5Cu00e7ois%22%2C%22lastName%22%3A%22Delahaye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stephanie%20M.%22%2C%22lastName%22%3A%22Biene%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lionel%22%2C%22lastName%22%3A%22Mangin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nadine%22%2C%22lastName%22%3A%22Ferrier%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Nicolas%22%2C%22lastName%22%3A%22Dacher%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabrice%22%2C%22lastName%22%3A%22Bauer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Guillaume%22%2C%22lastName%22%3A%22Leurent%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Pierre-Axel%22%2C%22lastName%22%3A%22Lentz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22H%5Cu00e9l%5Cu00e8ne%22%2C%22lastName%22%3A%22Kovacsik%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Pierre%22%2C%22lastName%22%3A%22Croisille%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Franck%22%2C%22lastName%22%3A%22Thuny%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Monique%22%2C%22lastName%22%3A%22Bernard%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alain%22%2C%22lastName%22%3A%22Furber%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Gilbert%22%2C%22lastName%22%3A%22Habib%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexis%22%2C%22lastName%22%3A%22Jacquier%22%7D%5D%2C%22abstractNote%22%3A%22BACKGROUND%3A%20Heart%20failure-%20%28HF%29%20and%20arrhythmia-related%20complications%20are%20the%20main%20causes%20of%20morbidity%20and%20mortality%20in%20patients%20with%20nonischemic%20dilated%20cardiomyopathy%20%28NIDCM%29.%20Cardiovascular%20magnetic%20resonance%20%28CMR%29%20imaging%20is%20a%20noninvasive%20tool%20for%20risk%20stratification%20based%20on%20fibrosis%20assessment.%20Diffuse%20interstitial%20fibrosis%20in%20NIDCM%20may%20be%20a%20limitation%20for%20fibrosis%20assessment%20through%20late%20gadolinium%20enhancement%20%28LGE%29%2C%20which%20might%20be%20overcome%20through%20quantitative%20T1%20and%20extracellular%20volume%20%28ECV%29%20assessment.%20T1%20and%20ECV%20prognostic%20value%20for%20arrhythmia-related%20events%20remain%20poorly%20investigated.%20We%20asked%20whether%20T1%20and%20ECV%20have%20a%20prognostic%20value%20in%20NIDCM%20patients.%5CnMETHODS%3A%20This%20prospective%20multicenter%20study%20analyzed%20225%20patients%20with%20NIDCM%20confirmed%20by%20CMR%20who%20were%20followed%20up%20for%202%5Cu00a0years.%20CMR%20evaluation%20included%20LGE%2C%20native%20T1%20mapping%20and%20ECV%20values.%20The%20primary%20endpoint%20was%20the%20occurrence%20of%20a%20major%20adverse%20cardiovascular%20event%20%28MACE%29%20which%20was%20divided%20in%20two%20groups%3A%20HF-related%20events%20and%20arrhythmia-related%20events.%20Optimal%20cutoffs%20for%20prediction%20of%20MACE%20occurrence%20were%20calculated%20for%20all%20CMR%20quantitative%20values.%5CnRESULTS%3A%20Fifty-eight%20patients%20%2826%25%29%20developed%20a%20MACE%20during%20follow-up%2C%2042%20patients%20%2819%25%29%20with%20HF-related%20events%20and%2016%20patients%20%287%25%29%20arrhythmia-related%20events.%20T1%20Z-score%20%28p%5Cu2009%3D%5Cu20090.008%29%20and%20global%20ECV%20%28p%5Cu2009%3D%5Cu20090.001%29%20were%20associated%20with%20HF-related%20events%20occurrence%2C%20in%20addition%20to%20left%20ventricular%20ejection%20fraction%20%28p%5Cu2009%26lt%3B%5Cu20090.001%29.%20ECV%5Cu2009%26gt%3B%5Cu200932.1%25%20%28optimal%20cutoff%29%20remained%20the%20only%20CMR%20independent%20predictor%20of%20HF-related%20events%20occurrence%20%28HR%202.15%20%5B1.14-4.07%5D%2C%20p%5Cu2009%3D%5Cu20090.018%29.%20In%20the%20arrhythmia-related%20events%20group%2C%20patients%20had%20increased%20native%20T1%20Z-score%20and%20ECV%20values%2C%20with%20both%20T1%20Z-score%5Cu2009%26gt%3B%5Cu20094.2%20and%20ECV%5Cu2009%26gt%3B%5Cu200930.5%25%20%28optimal%20cutoffs%29%20being%20independent%20predictors%20of%20arrhythmia-related%20events%20occurrence%20%28respectively%2C%20HR%202.86%20%5B1.06-7.68%5D%2C%20p%5Cu2009%3D%5Cu20090.037%20and%20HR%202.72%20%5B1.01-7.36%5D%2C%20p%5Cu2009%3D%5Cu20090.049%29.%5CnCONCLUSIONS%3A%20ECV%20was%20the%20sole%20independent%20predictive%20factor%20for%20both%20HF-%20and%20arrhythmia-related%20events%20in%20NIDCM%20patients.%20Native%20T1%20was%20also%20an%20independent%20predictor%20in%20arrhythmia-related%20events%20occurrence.%20The%20addition%20of%20ECV%20and%20more%20importantly%20native%20T1%20in%20the%20decision-making%20algorithm%20may%20improve%20arrhythmia%20risk%20stratification%20in%20NIDCM%20patients.%20Trial%20registration%20NCT02352129.%20Registered%202nd%20February%202015-Retrospectively%20registered%2C%20https%3A%5C%2F%5C%2Fclinicaltrials.gov%5C%2Fct2%5C%2Fshow%5C%2FNCT02352129.%22%2C%22date%22%3A%222023-02-06%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1186%5C%2Fs12968-023-00919-y%22%2C%22ISSN%22%3A%221532-429X%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%225Z6CVJGB%22%2C%22KFZ6H27M%22%2C%22SK6VWU7K%22%2C%22B4FUISBZ%22%2C%22XTA6KS7L%22%2C%22CXAMISN8%22%5D%2C%22dateModified%22%3A%222024-06-14T08%3A30%3A10Z%22%7D%7D%2C%7B%22key%22%3A%22T459RGQG%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Wang%20et%20al.%22%2C%22parsedDate%22%3A%222023-01-25%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BWang%2C%20H.E.%2C%20Woodman%2C%20M.%2C%20Triebkorn%2C%20P.%2C%20Lemarechal%2C%20J.-D.%2C%20Jha%2C%20J.%2C%20Dollomaja%2C%20B.%2C%20Vattikonda%2C%20A.N.%2C%20Sip%2C%20V.%2C%20Medina%20Villalon%2C%20S.%2C%20Hashemi%2C%20M.%2C%20Guye%2C%20M.%2C%20Makhalova%2C%20J.%2C%20Bartolomei%2C%20F.%20and%20Jirsa%2C%20V.%20%282023%29%20%26%23x201C%3BDelineating%20epileptogenic%20networks%20using%20brain%20imaging%20data%20and%20personalized%20modeling%20in%20drug-resistant%20epilepsy%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BScience%20Translational%20Medicine%26lt%3B%5C%2Fi%26gt%3B%2C%2015%28680%29%2C%20p.%20eabp8982.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1126%5C%2Fscitranslmed.abp8982%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1126%5C%2Fscitranslmed.abp8982%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Delineating%20epileptogenic%20networks%20using%20brain%20imaging%20data%20and%20personalized%20modeling%20in%20drug-resistant%20epilepsy%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Huifang%20E.%22%2C%22lastName%22%3A%22Wang%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marmaduke%22%2C%22lastName%22%3A%22Woodman%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Paul%22%2C%22lastName%22%3A%22Triebkorn%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Didier%22%2C%22lastName%22%3A%22Lemarechal%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jayant%22%2C%22lastName%22%3A%22Jha%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Borana%22%2C%22lastName%22%3A%22Dollomaja%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anirudh%20Nihalani%22%2C%22lastName%22%3A%22Vattikonda%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Viktor%22%2C%22lastName%22%3A%22Sip%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Samuel%22%2C%22lastName%22%3A%22Medina%20Villalon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Meysam%22%2C%22lastName%22%3A%22Hashemi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Julia%22%2C%22lastName%22%3A%22Makhalova%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabrice%22%2C%22lastName%22%3A%22Bartolomei%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Viktor%22%2C%22lastName%22%3A%22Jirsa%22%7D%5D%2C%22abstractNote%22%3A%22Precise%20estimates%20of%20epileptogenic%20zone%20networks%20%28EZNs%29%20are%20crucial%20for%20planning%20intervention%20strategies%20to%20treat%20drug-resistant%20focal%20epilepsy.%20Here%2C%20we%20present%20the%20virtual%20epileptic%20patient%20%28VEP%29%2C%20a%20workflow%20that%20uses%20personalized%20brain%20models%20and%20machine%20learning%20methods%20to%20estimate%20EZNs%20and%20to%20aid%20surgical%20strategies.%20The%20structural%20scaffold%20of%20the%20patient-specific%20whole-brain%20network%20model%20is%20constructed%20from%20anatomical%20T1%20and%20diffusion-weighted%20magnetic%20resonance%20imaging.%20Each%20network%20node%20is%20equipped%20with%20a%20mathematical%20dynamical%20model%20to%20simulate%20seizure%20activity.%20Bayesian%20inference%20methods%20sample%20and%20optimize%20key%20parameters%20of%20the%20personalized%20model%20using%20functional%20stereoelectroencephalography%20recordings%20of%20patients%26%23039%3B%20seizures.%20These%20key%20parameters%20together%20with%20their%20personalized%20model%20determine%20a%20given%20patient%26%23039%3Bs%20EZN.%20Personalized%20models%20were%20further%20used%20to%20predict%20the%20outcome%20of%20surgical%20intervention%20using%20virtual%20surgeries.%20We%20evaluated%20the%20VEP%20workflow%20retrospectively%20using%2053%20patients%20with%20drug-resistant%20focal%20epilepsy.%20VEPs%20reproduced%20the%20clinically%20defined%20EZNs%20with%20a%20precision%20of%200.6%2C%20where%20the%20physical%20distance%20between%20epileptogenic%20regions%20identified%20by%20VEP%20and%20the%20clinically%20defined%20EZNs%20was%20small.%20Compared%20with%20the%20resected%20brain%20regions%20of%2025%20patients%20who%20underwent%20surgery%2C%20VEP%20showed%20lower%20false%20discovery%20rates%20in%20seizure-free%20patients%20%28mean%2C%200.028%29%20than%20in%20non-seizure-free%20patients%20%28mean%2C%200.407%29.%20VEP%20is%20now%20being%20evaluated%20in%20an%20ongoing%20clinical%20trial%20%28EPINOV%29%20with%20an%20expected%20356%20prospective%20patients%20with%20epilepsy.%22%2C%22date%22%3A%222023-01-25%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1126%5C%2Fscitranslmed.abp8982%22%2C%22ISSN%22%3A%221946-6242%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22XTA6KS7L%22%2C%229RMECNPE%22%5D%2C%22dateModified%22%3A%222024-06-14T08%3A28%3A54Z%22%7D%7D%2C%7B%22key%22%3A%22GRXQFTBW%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Haast%20et%20al.%22%2C%22parsedDate%22%3A%222023%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BHaast%2C%20R.A.M.%2C%20Testud%2C%20B.%2C%20Makhalova%2C%20J.%2C%20Dary%2C%20H.%2C%20Cabane%2C%20A.%2C%20Le%20Troter%2C%20A.%2C%20Ranjeva%2C%20J.-P.%2C%20Bartolomei%2C%20F.%20and%20Guye%2C%20M.%20%282023%29%20%26%23x201C%3BMulti-scale%20structural%20alterations%20of%20the%20thalamus%20and%20basal%20ganglia%20in%20focal%20epilepsy%20using%207T%20MRI%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BHuman%20Brain%20Mapping%26lt%3B%5C%2Fi%26gt%3B%2C%2044%2813%29%2C%20pp.%204754%26%23x2013%3B4771.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fhbm.26414%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fhbm.26414%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Multi-scale%20structural%20alterations%20of%20the%20thalamus%20and%20basal%20ganglia%20in%20focal%20epilepsy%20using%207T%20MRI%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Roy%20A.%20M.%22%2C%22lastName%22%3A%22Haast%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Benoit%22%2C%22lastName%22%3A%22Testud%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Julia%22%2C%22lastName%22%3A%22Makhalova%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hugo%22%2C%22lastName%22%3A%22Dary%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexandre%22%2C%22lastName%22%3A%22Cabane%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Arnaud%22%2C%22lastName%22%3A%22Le%20Troter%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabrice%22%2C%22lastName%22%3A%22Bartolomei%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%5D%2C%22abstractNote%22%3A%22Focal%20epilepsy%20is%20characterized%20by%20repeated%20spontaneous%20seizures%20that%20originate%20from%20cortical%20epileptogenic%20zone%20networks%20%28EZN%29.%20Analysis%20of%20intracerebral%20recordings%20showed%20that%20subcortical%20structures%2C%20and%20in%20particular%20the%20thalamus%2C%20play%20an%20important%20role%20in%20seizure%20dynamics%20as%20well%2C%20supporting%20their%20structural%20alterations%20reported%20in%20the%20neuroimaging%20literature.%20Nonetheless%2C%20between-patient%20differences%20in%20EZN%20localization%20%28e.g.%2C%20temporal%20vs.%20non-temporal%20lobe%20epilepsy%29%20as%20well%20as%20extension%20%28i.e.%2C%20number%20of%20epileptogenic%20regions%29%20might%20impact%20the%20magnitude%20as%20well%20as%20spatial%20distribution%20of%20subcortical%20structural%20changes.%20Here%20we%20used%207%20Tesla%20MRI%20T1%20data%20to%20provide%20an%20unprecedented%20description%20of%20subcortical%20morphological%20%28volume%2C%20tissue%20deformation%2C%20and%20shape%29%20and%20longitudinal%20relaxation%20%28T1%29%20changes%20in%20focal%20epilepsy%20patients%20and%20evaluate%20the%20impact%20of%20the%20EZN%20and%20other%20patient-specific%20clinical%20features.%20Our%20results%20showed%20variable%20levels%20of%20atrophy%20across%20thalamic%20nuclei%20that%20appeared%20most%20prominent%20in%20the%20temporal%20lobe%20epilepsy%20group%20and%20the%20side%20ipsilateral%20to%20the%20EZN%2C%20while%20shortening%20of%20T1%20was%20especially%20observed%20for%20the%20lateral%20thalamus.%20Multivariate%20analyses%20across%20thalamic%20nuclei%20and%20basal%20ganglia%20showed%20that%20volume%20acted%20as%20the%20dominant%20discriminator%20between%20patients%20and%20controls%2C%20while%20%28posterolateral%29%20thalamic%20T1%20measures%20looked%20promising%20to%20further%20differentiate%20patients%20based%20on%20EZN%20localization.%20In%20particular%2C%20the%20observed%20differences%20in%20T1%20changes%20between%20thalamic%20nuclei%20indicated%20differential%20involvement%20based%20on%20EZN%20localization.%20Finally%2C%20EZN%20extension%20was%20found%20to%20best%20explain%20the%20observed%20variability%20between%20patients.%20To%20conclude%2C%20this%20work%20revealed%20multi-scale%20subcortical%20alterations%20in%20focal%20epilepsy%20as%20well%20as%20their%20dependence%20on%20several%20clinical%20characteristics.%22%2C%22date%22%3A%222023%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.1002%5C%2Fhbm.26414%22%2C%22ISSN%22%3A%221097-0193%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fonlinelibrary.wiley.com%5C%2Fdoi%5C%2Fabs%5C%2F10.1002%5C%2Fhbm.26414%22%2C%22collections%22%3A%5B%22UP3H3ICX%22%2C%225P5FWCR9%22%2C%22XTA6KS7L%22%2C%22FBQIKF54%22%2C%22PCMV2W5C%22%2C%229RMECNPE%22%5D%2C%22dateModified%22%3A%222025-09-19T07%3A46%3A00Z%22%7D%7D%2C%7B%22key%22%3A%22XZNG2JAZ%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Destruel%20et%20al.%22%2C%22parsedDate%22%3A%222023%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BDestruel%2C%20A.%2C%20Mauconduit%2C%20F.%2C%20Massire%2C%20A.%2C%20Abdeddaim%2C%20R.%2C%20Guye%2C%20M.%2C%20Gras%2C%20V.%20and%20Callot%2C%20V.%20%282023%29%20%26%23x201C%3BOptimized%20interferometric%20encoding%20of%20presaturated%20TurboFLASH%20B1%20mapping%20for%20parallel%20transmission%20MRI%20at%207%20T%3A%20Preliminary%20application%20for%20quantitative%20T1%20mapping%20in%20the%20spinal%20cord%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BMagnetic%20Resonance%20in%20Medicine%26lt%3B%5C%2Fi%26gt%3B%2C%2090%284%29%2C%20pp.%201328%26%23x2013%3B1344.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fmrm.29708%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fmrm.29708%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Optimized%20interferometric%20encoding%20of%20presaturated%20TurboFLASH%20B1%20mapping%20for%20parallel%20transmission%20MRI%20at%207%20T%3A%20Preliminary%20application%20for%20quantitative%20T1%20mapping%20in%20the%20spinal%20cord%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Aurelien%22%2C%22lastName%22%3A%22Destruel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Franck%22%2C%22lastName%22%3A%22Mauconduit%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Aur%5Cu00e9lien%22%2C%22lastName%22%3A%22Massire%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Redha%22%2C%22lastName%22%3A%22Abdeddaim%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Vincent%22%2C%22lastName%22%3A%22Gras%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Virginie%22%2C%22lastName%22%3A%22Callot%22%7D%5D%2C%22abstractNote%22%3A%22Purpose%20The%20acquisition%20of%20accurate%20B1%20maps%20is%20critical%20for%20parallel%20transmit%20techniques%20%28pTx%29.%20The%20presaturated%20turboFLASH%20%28satTFL%29%20method%20has%20been%20widely%20used%20in%20combination%20with%20interferometric%20encoding%20to%20provide%20robust%20and%20fast%20B1%20maps.%20However%2C%20typical%20encodings%2C%20mostly%20evaluated%20on%20brain%2C%20do%20not%20necessarily%20fit%20all%20coils%20and%20organs.%20In%20this%20work%2C%20we%20evaluated%20and%20improved%20the%20accuracy%20of%20the%20satTFL%20for%20cervical%20spine%20at%207%20T%2C%20proposing%20a%20novel%20interferometric%20encoding%20optimization.%20The%20benefits%20of%20such%20improvements%20were%20investigated%20in%20an%20exploratory%20study%20of%20quantitative%20T1%20mapping%20with%20pTx-MP2RAGE.%20Methods%20Global%20optimization%20of%20interferometric%20encoding%20was%20implemented%20by%20simulating%20the%20ability%20of%20the%20satTFL%20to%20reconstruct%20B1%20maps%2C%20with%20varying%20encoding%20and%20inclusion%20of%20complex%20noise%2C%20inside%20a%20region%20of%20interest%20covering%20the%20cervical%20spine.%20The%20performance%20of%20satTFL%20before%20and%20after%20optimization%20was%20compared%20to%20actual%20flip%20angle%20imaging.%20Optimized%20and%20non-optimized%20B1%20maps%20were%20then%20used%20to%20calculate%20pTx%20pulses%20for%20MP2RAGE%20T1%20mapping.%20Results%20Interferometric%20encoding%20optimization%20resulted%20in%20satTFL%20closer%20to%20actual%20flip%20angle%20imaging%2C%20with%20substantial%20gain%20of%20signal%20in%20regions%20where%20non-optimized%20satTFL%20could%20fail.%20T1%20maps%20measured%20with%20non-adiabatic%20pTx%20pulses%20were%20closer%20to%20standard%20non-pTx%20results%20%28which%20used%20adiabatic%20pulses%29%20when%20using%20optimized-satTFL%2C%20with%20substantially%20lower%20specific%20absorption%20rate.%20Conclusion%20Optimization%20of%20the%20satTFL%20interferometric%20encoding%20improves%20B1%20maps%20in%20the%20spinal%20cord%2C%20in%20particular%20in%20low%20SNR%20regions.%20A%20linear%20correction%20of%20the%20satTFL%20was%20additionally%20shown%20to%20be%20required.%20The%20method%20was%20successfully%20used%20for%20quantitative%20phantom%20and%20in%20vivo%20T1%20mapping%2C%20showing%20improved%20results%20compared%20to%20non-optimized%20satTFL%20thanks%20to%20improved%20pTx-pulse%20generation.%22%2C%22date%22%3A%222023%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.1002%5C%2Fmrm.29708%22%2C%22ISSN%22%3A%221522-2594%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fonlinelibrary.wiley.com%5C%2Fdoi%5C%2Fabs%5C%2F10.1002%5C%2Fmrm.29708%22%2C%22collections%22%3A%5B%22ZFC2Q648%22%2C%22UP3H3ICX%22%2C%22HHEPZHEJ%22%2C%22XTA6KS7L%22%2C%22R8ARNQR7%22%5D%2C%22dateModified%22%3A%222024-11-06T10%3A43%3A01Z%22%7D%7D%2C%7B%22key%22%3A%22QUUBG9E5%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Hostin%20et%20al.%22%2C%22parsedDate%22%3A%222023%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BHostin%2C%20M.-A.%2C%20Ogier%2C%20A.C.%2C%20Michel%2C%20C.P.%2C%20Le%20Fur%2C%20Y.%2C%20Guye%2C%20M.%2C%20Attarian%2C%20S.%2C%20Fortanier%2C%20E.%2C%20Bellemare%2C%20M.-E.%20and%20Bendahan%2C%20D.%20%282023%29%20%26%23x201C%3BThe%20Impact%20of%20Fatty%20Infiltration%20on%20MRI%20Segmentation%20of%20Lower%20Limb%20Muscles%20in%20Neuromuscular%20Diseases%3A%20A%20Comparative%20Study%20of%20Deep%20Learning%20Approaches%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BJournal%20of%20Magnetic%20Resonance%20Imaging%26lt%3B%5C%2Fi%26gt%3B%2C%2058%286%29%2C%20pp.%201826%26%23x2013%3B1835.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fjmri.28708%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fjmri.28708%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22The%20Impact%20of%20Fatty%20Infiltration%20on%20MRI%20Segmentation%20of%20Lower%20Limb%20Muscles%20in%20Neuromuscular%20Diseases%3A%20A%20Comparative%20Study%20of%20Deep%20Learning%20Approaches%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marc-Adrien%22%2C%22lastName%22%3A%22Hostin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Augustin%20C.%22%2C%22lastName%22%3A%22Ogier%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Constance%20P.%22%2C%22lastName%22%3A%22Michel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yann%22%2C%22lastName%22%3A%22Le%20Fur%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shahram%22%2C%22lastName%22%3A%22Attarian%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Etienne%22%2C%22lastName%22%3A%22Fortanier%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marc-Emmanuel%22%2C%22lastName%22%3A%22Bellemare%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Bendahan%22%7D%5D%2C%22abstractNote%22%3A%22Background%20Deep%20learning%20methods%20have%20been%20shown%20to%20be%20useful%20for%20segmentation%20of%20lower%20limb%20muscle%20MRIs%20of%20healthy%20subjects%20but%2C%20have%20not%20been%20sufficiently%20evaluated%20on%20neuromuscular%20disease%20%28NDM%29%20patients.%20Purpose%20Evaluate%20the%20influence%20of%20fat%20infiltration%20on%20convolutional%20neural%20network%20%28CNN%29%20segmentation%20of%20MRIs%20from%20NMD%20patients.%20Study%20Type%20Retrospective%20study.%20Subjects%20Data%20were%20collected%20from%20a%20hospital%20database%20of%2067%20patients%20with%20NMDs%20and%2014%20controls%20%28age%3A%2053%20%5Cu00b1%2017%20years%2C%20sex%3A%2048%20M%2C%2033%20F%29.%20Ten%20individual%20muscles%20were%20segmented%20from%20the%20thigh%20and%20six%20from%20the%20calf%20%2820%20slices%2C%20200%20cm%20section%29.%20Field%20Strength%5C%2FSequence%20A%201.5%20T.%20Sequences%3A%202D%20T1-weighted%20fast%20spin%20echo.%20Fat%20fraction%20%28FF%29%3A%20three-point%20Dixon%203D%20GRE%2C%20magnetization%20transfer%20ratio%20%28MTR%29%3A%203D%20MT-prepared%20GRE%2C%20T2%3A%202D%20multispin-echo%20sequence.%20Assessment%20U-Net%202D%2C%20U-Net%203D%2C%20TransUNet%2C%20and%20HRNet%20were%20trained%20to%20segment%20thigh%20and%20leg%20muscles%20%28101%5C%2F11%20and%2095%5C%2F11%20training%5C%2Fvalidation%20images%2C%2010-fold%20cross-validation%29.%20Automatic%20and%20manual%20segmentations%20were%20compared%20based%20on%20geometric%20criteria%20%28Dice%20coefficient%20%5BDSC%5D%2C%20outlier%20rate%2C%20absence%20rate%29%20and%20reliability%20of%20measured%20MRI%20quantities%20%28FF%2C%20MTR%2C%20T2%2C%20volume%29.%20Statistical%20Tests%20Bland%5Cu2013Altman%20plots%20were%20chosen%20to%20describe%20agreement%20between%20manual%20vs.%20automatic%20estimated%20FF%2C%20MTR%2C%20T2%20and%20volume.%20Comparisons%20were%20made%20between%20muscle%20populations%20with%20an%20FF%20greater%20than%2020%25%20%28G20%2B%29%20and%20lower%20than%2020%25%20%28G20%5Cu2212%29.%20Results%20The%20CNNs%20achieved%20equivalent%20results%2C%20yet%20only%20HRNet%20recognized%20every%20muscle%20in%20the%20database%2C%20with%20a%20DSC%20of%200.91%20%5Cu00b1%200.08%2C%20and%20measurement%20biases%20reaching%20%5Cu22120.32%25%20%5Cu00b1%200.92%25%20for%20FF%2C%200.19%20%5Cu00b1%200.77%20for%20MTR%2C%20%5Cu22120.55%20%5Cu00b1%201.95%20msec%20for%20T2%2C%20and%20%5Cu2212%200.38%20%5Cu00b1%203.67%20cm3%20for%20volume.%20The%20performances%20of%20HRNet%2C%20between%20G20%5Cu2212%20and%20G20%2B%20decreased%20significantly.%20Data%20Conclusion%20HRNet%20was%20the%20most%20appropriate%20network%2C%20as%20it%20did%20not%20omit%20any%20muscle.%20The%20accuracy%20obtained%20shows%20that%20CNNs%20could%20provide%20fully%20automated%20methods%20for%20studying%20NMDs.%20However%2C%20the%20accuracy%20of%20the%20methods%20may%20be%20degraded%20on%20the%20most%20infiltrated%20muscles%20%28%26gt%3B20%25%29.%20Evidence%20Level%204.%20Technical%20Efficacy%20Stage%201.%22%2C%22date%22%3A%222023%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.1002%5C%2Fjmri.28708%22%2C%22ISSN%22%3A%221522-2586%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fonlinelibrary.wiley.com%5C%2Fdoi%5C%2Fabs%5C%2F10.1002%5C%2Fjmri.28708%22%2C%22collections%22%3A%5B%22SVI8UJ6H%22%2C%22NW6SZQBR%22%2C%22ZP8JD3DQ%22%5D%2C%22dateModified%22%3A%222025-04-23T10%3A05%3A20Z%22%7D%7D%2C%7B%22key%22%3A%22L9GKRZGM%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Azilinon%20et%20al.%22%2C%22parsedDate%22%3A%222023%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BAzilinon%2C%20M.%2C%20Makhalova%2C%20J.%2C%20Zaaraoui%2C%20W.%2C%20Medina%20Villalon%2C%20S.%2C%20Viout%2C%20P.%2C%20Roussel%2C%20T.%2C%20El%20Mendili%2C%20M.M.%2C%20Ridley%2C%20B.%2C%20Ranjeva%2C%20J.-P.%2C%20Bartolomei%2C%20F.%2C%20Jirsa%2C%20V.%20and%20Guye%2C%20M.%20%282023%29%20%26%23x201C%3BCombining%20sodium%20MRI%2C%20proton%20MR%20spectroscopic%20imaging%2C%20and%20intracerebral%20EEG%20in%20epilepsy%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BHuman%20Brain%20Mapping%26lt%3B%5C%2Fi%26gt%3B%2C%2044%282%29%2C%20pp.%20825%26%23x2013%3B840.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fhbm.26102%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fhbm.26102%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Combining%20sodium%20MRI%2C%20proton%20MR%20spectroscopic%20imaging%2C%20and%20intracerebral%20EEG%20in%20epilepsy%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mikhael%22%2C%22lastName%22%3A%22Azilinon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Julia%22%2C%22lastName%22%3A%22Makhalova%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Wafaa%22%2C%22lastName%22%3A%22Zaaraoui%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Samuel%22%2C%22lastName%22%3A%22Medina%20Villalon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Patrick%22%2C%22lastName%22%3A%22Viout%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tangi%22%2C%22lastName%22%3A%22Roussel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mohamed%20M.%22%2C%22lastName%22%3A%22El%20Mendili%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ben%22%2C%22lastName%22%3A%22Ridley%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabrice%22%2C%22lastName%22%3A%22Bartolomei%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Viktor%22%2C%22lastName%22%3A%22Jirsa%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%5D%2C%22abstractNote%22%3A%22Whole%20brain%20ionic%20and%20metabolic%20imaging%20has%20potential%20as%20a%20powerful%20tool%20for%20the%20characterization%20of%20brain%20diseases.%20We%20combined%20sodium%20MRI%20%2823Na%20MRI%29%20and%201H-MR%20Spectroscopic%20Imaging%20%281H-MRSI%29%2C%20assessing%20changes%20within%20epileptogenic%20networks%20in%20comparison%20with%20electrophysiologically%20normal%20networks%20as%20defined%20by%20stereotactic%20EEG%20%28SEEG%29%20recordings%20analysis.%20We%20applied%20a%20multi-echo%20density%20adapted%203D%20projection%20reconstruction%20pulse%20sequence%20at%207%20T%20%2823Na-MRI%29%20and%20a%203D%20echo-planar%20spectroscopic%20imaging%20sequence%20at%203%20T%20%281H-MRSI%29%20in%2019%20patients%20suffering%20from%20drug-resistant%20focal%20epilepsy%20who%20underwent%20presurgical%20SEEG.%20We%20investigated%2023Na%20MRI%20parameters%20including%20total%20sodium%20concentration%20%28TSC%29%20and%20the%20sodium%20signal%20fraction%20associated%20with%20the%20short%20component%20of%20T2%2A%20decay%20%28f%29%2C%20alongside%20the%20level%20of%20metabolites%20N-acetyl%20aspartate%20%28NAA%29%2C%20choline%20compounds%20%28Cho%29%2C%20and%20total%20creatine%20%28tCr%29.%20All%20measures%20were%20extracted%20from%20spherical%20regions%20of%20interest%20%28ROIs%29%20centered%20between%20two%20adjacent%20SEEG%20electrode%20contacts%20and%20z-scored%20against%20the%20same%20ROI%20in%20controls.%20Group%20comparison%20showed%20a%20significant%20increase%20in%20f%20only%20in%20the%20epileptogenic%20zone%20%28EZ%29%20compared%20to%20controls%20and%20compared%20to%20patients%26%23039%3B%20propagation%20zone%20%28PZ%29%20and%20non-involved%20zone%20%28NIZ%29.%20TSC%20was%20significantly%20increased%20in%20all%20patients%26%23039%3B%20regions%20compared%20to%20controls.%20Conversely%2C%20NAA%20levels%20were%20significantly%20lower%20in%20patients%20compared%20to%20controls%2C%20and%20lower%20in%20the%20EZ%20compared%20to%20PZ%20and%20NIZ.%20Multiple%20regression%20analyzing%20the%20relationship%20between%20sodium%20and%20metabolites%20levels%20revealed%20significant%20relations%20in%20PZ%20and%20in%20NIZ%20but%20not%20in%20EZ.%20Our%20results%20are%20in%20agreement%20with%20the%20energetic%20failure%20hypothesis%20in%20epileptic%20regions%20associated%20with%20widespread%20tissue%20reorganization.%22%2C%22date%22%3A%222023%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.1002%5C%2Fhbm.26102%22%2C%22ISSN%22%3A%221097-0193%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fonlinelibrary.wiley.com%5C%2Fdoi%5C%2Fabs%5C%2F10.1002%5C%2Fhbm.26102%22%2C%22collections%22%3A%5B%22QU2QXBVV%22%2C%22UP3H3ICX%22%2C%22HVJZKIZG%22%2C%22P66W67T8%22%2C%22F2AGIUQU%22%2C%22XTA6KS7L%22%2C%229RMECNPE%22%5D%2C%22dateModified%22%3A%222024-11-14T14%3A22%3A11Z%22%7D%7D%2C%7B%22key%22%3A%2298VSUMC3%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Scholly%20et%20al.%22%2C%22parsedDate%22%3A%222022-11-01%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BScholly%2C%20J.%2C%20Gras%2C%20A.%2C%20Guye%2C%20M.%2C%20Bilger%2C%20M.%2C%20Valenti%20Hirsch%2C%20M.P.%2C%20Hirsch%2C%20E.%2C%20Timofeev%2C%20A.%2C%20Vidailhet%2C%20P.%2C%20B%26%23xE9%3Bnar%2C%20C.G.%20and%20Bartolomei%2C%20F.%20%282022%29%20%26%23x201C%3BConnectivity%20Alterations%20in%20Emotional%20and%20Cognitive%20Networks%20During%20a%20Manic%20State%20Induced%20by%20Direct%20Electrical%20Stimulation%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BBrain%20Topography%26lt%3B%5C%2Fi%26gt%3B%2C%2035%285%29%2C%20pp.%20627%26%23x2013%3B635.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-ItemURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs10548-022-00913-0%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs10548-022-00913-0%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Connectivity%20Alterations%20in%20Emotional%20and%20Cognitive%20Networks%20During%20a%20Manic%20State%20Induced%20by%20Direct%20Electrical%20Stimulation%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Julia%22%2C%22lastName%22%3A%22Scholly%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Adrien%22%2C%22lastName%22%3A%22Gras%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mathias%22%2C%22lastName%22%3A%22Bilger%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maria%20Paola%22%2C%22lastName%22%3A%22Valenti%20Hirsch%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Edouard%22%2C%22lastName%22%3A%22Hirsch%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexander%22%2C%22lastName%22%3A%22Timofeev%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Pierre%22%2C%22lastName%22%3A%22Vidailhet%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christian%20G.%22%2C%22lastName%22%3A%22B%5Cu00e9nar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabrice%22%2C%22lastName%22%3A%22Bartolomei%22%7D%5D%2C%22abstractNote%22%3A%22Mania%20is%20characterized%20by%20affective%20and%20cognitive%20alterations%2C%20with%20heightened%20external%20and%20self-awareness%20that%20are%20opposite%20to%20the%20alteration%20of%20awareness%20during%20epileptic%20seizures.%20Electrical%20stimulations%20carried%20out%20routinely%20during%20stereotactic%20intracerebral%20EEG%20%28SEEG%29%20recordings%20for%20presurgical%20evaluation%20of%20epilepsy%20may%20represent%20a%20unique%20opportunity%20to%20study%20the%20pathophysiology%20of%20such%20complex%20emotional-behavioral%20phenomenon%2C%20particularly%20difficult%20to%20reproduce%20in%20experimental%20setting.%20We%20investigated%20SEEG%20signals-based%20functional%20connectivity%20between%20different%20brain%20regions%20involved%20in%20emotions%20and%20in%20consciousness%20processing%20during%20a%20manic%20state%20induced%20by%20electrical%20stimulation%20in%20a%20patient%20with%20drug-resistant%20focal%20epilepsy.%20The%20stimulation%20inducing%20manic%20state%20and%20an%20asymptomatic%20stimulation%20of%20the%20same%20site%2C%20as%20well%20as%20a%20seizure%20with%20alteration%20of%20awareness%20%28AOA%29%20were%20analyzed.%20Functional%20connectivity%20analysis%20was%20performed%20by%20measuring%20interdependencies%20%28nonlinear%20regression%20analysis%20based%20on%20the%20h2%20coefficient%29%20between%20broadband%20SEEG%20signals%20and%20within%20typical%20sub-bands%2C%20before%20and%20after%20stimulation%2C%20or%20before%20and%20during%20the%20seizure%20with%20AOA%2C%20respectively.%20Stimulation%20of%20the%20right%20lateral%20prefrontal%20cortex%20induced%20a%20manic%20state%20lasting%20several%20hours.%20Its%20onset%20was%20associated%20with%20significant%20increase%20of%20broadband-signal%20functional%20coupling%20between%20the%20right%20hemispheric%20limbic%20nodes%2C%20the%20temporal%20pole%20and%20the%20claustrum%2C%20whereas%20significant%20decorrelation%20between%20the%20right%20lateral%20prefrontal%20and%20the%20anterior%20cingulate%20cortex%20was%20observed%20in%20theta-band.%20In%20contrast%2C%20ictal%20alteration%20of%20awareness%20was%20associated%20with%20increased%20broadband%20and%20sub-bands%20synchronization%20within%20and%20between%20the%20internal%20and%20external%20awareness%20networks%2C%20including%20the%20anterior%20and%20middle%20cingulate%2C%20the%20mesial%20and%20lateral%20prefrontal%2C%20the%20inferior%20parietal%20and%20the%20temporopolar%20cortex.%20Our%20data%20suggest%20the%20existence%20of%20network-%20and%20frequency-specific%20functional%20connectivity%20patterns%20during%20manic%20state.%20A%20transient%20desynchronization%20of%20theta%20activity%20between%20the%20external%20and%20internal%20awareness%20network%20hubs%20is%20likely%20to%20increase%20awareness%2C%20with%20potential%20therapeutic%20effect.%22%2C%22date%22%3A%222022-11-01%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.1007%5C%2Fs10548-022-00913-0%22%2C%22ISSN%22%3A%221573-6792%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs10548-022-00913-0%22%2C%22collections%22%3A%5B%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222023-12-15T10%3A47%3A47Z%22%7D%7D%2C%7B%22key%22%3A%226GQS6B3H%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Maarouf%20et%20al.%22%2C%22parsedDate%22%3A%222022-10-01%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BMaarouf%2C%20A.%2C%20Audoin%2C%20B.%2C%20Gherib%2C%20S.%2C%20El%20Mendili%2C%20M.M.%2C%20Viout%2C%20P.%2C%20Pariollaud%2C%20F.%2C%20Bouti%26%23xE8%3Bre%2C%20C.%2C%20Rico%2C%20A.%2C%20Guye%2C%20M.%2C%20Ranjeva%2C%20J.-P.%2C%20Zaaraoui%2C%20W.%20and%20Pelletier%2C%20J.%20%282022%29%20%26%23x201C%3BGrey-matter%20sodium%20concentration%20as%20an%20individual%20marker%20of%20multiple%20sclerosis%20severity%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BMultiple%20Sclerosis%20Journal%26lt%3B%5C%2Fi%26gt%3B%2C%2028%2812%29%2C%20pp.%201903%26%23x2013%3B1912.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-ItemURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1177%5C%2F13524585221102587%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1177%5C%2F13524585221102587%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Grey-matter%20sodium%20concentration%20as%20an%20individual%20marker%20of%20multiple%20sclerosis%20severity%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Adil%22%2C%22lastName%22%3A%22Maarouf%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Bertrand%22%2C%22lastName%22%3A%22Audoin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Soraya%22%2C%22lastName%22%3A%22Gherib%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mohamed%20Mounir%22%2C%22lastName%22%3A%22El%20Mendili%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Patrick%22%2C%22lastName%22%3A%22Viout%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fanelly%22%2C%22lastName%22%3A%22Pariollaud%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Cl%5Cu00e9mence%22%2C%22lastName%22%3A%22Bouti%5Cu00e8re%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Audrey%22%2C%22lastName%22%3A%22Rico%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Wafaa%22%2C%22lastName%22%3A%22Zaaraoui%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean%22%2C%22lastName%22%3A%22Pelletier%22%7D%5D%2C%22abstractNote%22%3A%22Objective%3AQuantification%20of%20brain%20injury%20in%20patients%20with%20variable%20disability%20despite%20similar%20disease%20duration%20may%20be%20relevant%20to%20identify%20the%20mechanisms%20underlying%20disability%20in%20multiple%20sclerosis%20%28MS%29.%20We%20aimed%20to%20compare%20grey-matter%20sodium%20abnormalities%20%28GMSAs%29%2C%20a%20parameter%20reflecting%20neuronal%20and%20astrocyte%20dysfunction%2C%20in%20MS%20patients%20with%20benign%20multiple%20sclerosis%20%28BMS%29%20and%20non-benign%20multiple%20sclerosis%20%28NBMS%29.Methods%3AWe%20identified%20never-treated%20BMS%20patients%20in%20our%20local%20MS%20database%20of%201352%20patients.%20A%20group%20with%20NBMS%20was%20identified%20with%20same%20disease%20duration.%20All%20participants%20underwent%2023Na%20magnetic%20resonance%20imaging%20%28MRI%29.%20The%20existence%20of%20GMSA%20was%20detected%20by%20statistical%20analysis.Results%3AIn%20total%2C%20102%20individuals%20were%20included%20%2821%20BMS%2C%2025%20NBMS%20and%2056%20controls%29.%20GMSA%20was%20detected%20in%2010%20BMS%20and%2019%20NBMS%20%2811%5C%2F16%20relapsing-remitting%20multiple%20sclerosis%20%28RRMS%29%20and%208%5C%2F9%20secondary%20progressive%20multiple%20sclerosis%20%28SPMS%29%20patients%29%20%28p%3F%3D%3F0.05%29.%20On%20logistic%20regression%20including%20the%20presence%20or%20absence%20of%20GMSA%2C%20thalamic%20volume%2C%20cortical%20grey-matter%20volume%20and%20T2-weighted%20lesion%20load%2C%20thalamic%20volume%20was%20independently%20associated%20with%20BMS%20status%20%28odds%20ratio%20%28OR%29%3F%3D%3F0.64%20for%20each%20unit%29.%20Nonetheless%2C%20the%20absence%20of%20GMSA%20was%20independently%20associated%20when%20excluding%20patients%20with%20significant%20cognitive%20alteration%20%28n%3F%3D%3F7%29%20from%20the%20BMS%20group%20%28OR%3F%3D%3F4.6%29.Conclusion%3ADetection%20of%20GMSA%20in%20individuals%20and%20thalamic%20volume%20are%20promising%20to%20differentiate%20BMS%20from%20NBMS%20as%20compared%20with%20cortical%20or%20whole%20grey-matter%20atrophy%20and%20T2-weighted%20lesions.%22%2C%22date%22%3A%222022-10-01%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.1177%5C%2F13524585221102587%22%2C%22ISSN%22%3A%221352-4585%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1177%5C%2F13524585221102587%22%2C%22collections%22%3A%5B%22KJQH9V8M%22%2C%22QU2QXBVV%22%2C%22UP3H3ICX%22%2C%22B4EWFM7E%22%2C%22P66W67T8%22%2C%226KPLZTET%22%2C%22F2AGIUQU%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222024-11-26T16%3A01%3A22Z%22%7D%7D%2C%7B%22key%22%3A%22HUL3F9QN%22%2C%22library%22%3A%7B%22id%22%3A180164%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Forodighasemabadi%20et%20al.%22%2C%22parsedDate%22%3A%222022-07-23%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BForodighasemabadi%2C%20A.%2C%20Baucher%2C%20G.%2C%20Soustelle%2C%20L.%2C%20Troalen%2C%20T.%2C%20Girard%2C%20O.M.%2C%20Guye%2C%20M.%2C%20Grisoli%2C%20J.-B.%2C%20Ranjeva%2C%20J.-P.%2C%20Duhamel%2C%20G.%20and%20Callot%2C%20V.%20%282022%29%20%26%23x201C%3BSpinal%20cord%20and%20brain%20tissue%20impairments%20as%20long-term%20effects%20of%20rugby%20practice%3F%20An%20exploratory%20study%20based%20on%20T1%20and%20ihMTsat%20measures%2C%26%23x201D%3B%20%26lt%3Bi%26gt%3BNeuroImage.%20Clinical%26lt%3B%5C%2Fi%26gt%3B%2C%2035%2C%20p.%20103124.%20Available%20at%3A%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.nicl.2022.103124%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.nicl.2022.103124%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Spinal%20cord%20and%20brain%20tissue%20impairments%20as%20long-term%20effects%20of%20rugby%20practice%3F%20An%20exploratory%20study%20based%20on%20T1%20and%20ihMTsat%20measures%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Arash%22%2C%22lastName%22%3A%22Forodighasemabadi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Guillaume%22%2C%22lastName%22%3A%22Baucher%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lucas%22%2C%22lastName%22%3A%22Soustelle%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Troalen%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Olivier%20M.%22%2C%22lastName%22%3A%22Girard%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maxime%22%2C%22lastName%22%3A%22Guye%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Baptiste%22%2C%22lastName%22%3A%22Grisoli%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Philippe%22%2C%22lastName%22%3A%22Ranjeva%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Guillaume%22%2C%22lastName%22%3A%22Duhamel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Virginie%22%2C%22lastName%22%3A%22Callot%22%7D%5D%2C%22abstractNote%22%3A%22Rugby%20players%20are%20subject%20to%20multiple%20impacts%20to%20their%20head%20and%20neck%20that%20could%20have%20adverse%20neurological%20effects%20and%20put%20them%20at%20increased%20risk%20of%20neurodegeneration.%20Previous%20studies%20demonstrated%20altered%20default%20mode%20network%20and%20diffusion%20metrics%20on%20brain%2C%20as%20well%20as%20more%20foraminal%20stenosis%2C%20disc%20protrusion%20and%20neck%20pain%20among%20players%20of%20contact%20sports%20as%20compared%20to%20healthy%20controls.%20However%2C%20the%20long-term%20effects%20of%20practice%20and%20repetitive%20impacts%20on%20brain%20and%20cervical%20spinal%20cord%20%28cSC%29%20of%20the%20rugby%20players%20have%20never%20been%20systematically%20investigated.%20In%20this%20study%2C%2015%20retired%20professional%20and%20amateur%20rugby%20players%20%28R%29%20and%2015%20age-matched%20healthy%20controls%20%28HC%29%20%28all%20males%3B%20mean%20age%20R%3A%2046.8%5Cu00a0%5Cu00b1%5Cu00a07.6%3B%20and%20HC%3A%2048.6%5Cu00a0%5Cu00b1%5Cu00a09.5%29%20were%20recruited%20both%20to%20investigate%20cord%20impairments%20and%20further%20characterize%20brain%20structure%20damage.%20Medical%20questionnaires%20including%20modified%20Japanese%20Orthopedic%20Association%20scale%20%28mJOA%29%20and%20Neck%20Disability%20Index%20%28NDI%29%20were%20filled%20by%20all%20participants.%20A%203%5Cu00a0T%20multi-parametric%20MR%20protocol%20including%20conventional%20qualitative%20techniques%20such%20as%20T1-%2C%20T2-%2C%20and%20T2%2A-weighted%20sequences%2C%20as%20well%20as%20state-of-the%20art%20quantitative%20techniques%20including%20MP2RAGE%20T1%20mapping%20and%203D%20ihMTRAGE%2C%20was%20used%20on%20both%20brain%20and%20cSC.%20Normalized%20brain%20WM%20and%20GM%20volumes%2C%20spine%20Overall%20Stenosis%20Score%2C%20cord%20cross-sectional%20area%20and%20regional%20T1%20and%20ihMT%20metrics%20were%20derived%20from%20these%20acquisitions.%20Rugby%20players%20showed%20significantly%20higher%20NDI%20scores%2C%20as%20well%20as%20a%20faster%20decline%20of%20normalized%20brain%20GM%20volume%20with%20age%20as%20compared%20to%20HC.%20Moreover%2C%20higher%20T1%20values%20on%20cSC%20suggestive%20of%20structural%20degeneration%2C%20together%20with%20higher%20T1%20and%20lower%20ihMTsat%20on%20brain%20WM%20suggestive%20of%20demyelination%2C%20were%20observed%20in%20retired%20rugby%20players%20as%20compared%20to%20age-matched%20controls%2C%20which%20may%20suggest%20cumulative%20effects%20of%20long-term%20impacts%20on%20the%20tissues.%20Metrics%20also%20suggest%20early%20aging%20and%20different%20aging%20processes%20on%20brain%20tissue%20in%20the%20players.%20These%20preliminary%20observations%20provide%20new%20insights%20in%20the%20domain%2C%20which%20should%20now%20be%20further%20investigated%20on%20larger%20cohorts%20and%20multicentric%20longitudinal%20studies%2C%20and%20further%20correlated%20to%20the%20likelihood%20of%20neurodegenerative%20diseases%20and%20risk%20factors.%22%2C%22date%22%3A%222022-07-23%22%2C%22language%22%3A%22eng%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.nicl.2022.103124%22%2C%22ISSN%22%3A%222213-1582%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%2274RX9758%22%2C%224U7D3E9U%22%2C%22ZFC2Q648%22%2C%226GBQDAVI%22%2C%22UP3H3ICX%22%2C%22M2AY8I5W%22%2C%22XTA6KS7L%22%5D%2C%22dateModified%22%3A%222023-12-15T10%3A47%3A48Z%22%7D%7D%5D%7D
Gauer, L., Haast, R.A.M., Azilinon, M., El Mendili, M.M., Makhalova, J., Dary, H., Dinkelacker, V., Ridley, B., Ranjeva, J.-P., Zaaraoui, W., Bartolomei, F. and Guye, M. (2025) “Investigating sodium homeostasis of structural brain hubs in focal epilepsy using 7 T MRI,” Brain: A Journal of Neurology, p. awaf409. Available at: https://doi.org/10.1093/brain/awaf409.
Stellmann, J.-P., Maarouf, A., Nicolescu, M., Boutiere, C., Rico, A., Zaaraoui, W., Guye, M., Pelletier, J., Ranjeva, J.-P. and Audoin, B. (2025) “Early structural hub disruption leads to premature functional adaption in multiple sclerosis,” Brain Structure & Function, 230(9), p. 172. Available at: https://doi.org/10.1007/s00429-025-03023-2.
Martin, S., Trabelsi, A., Guye, M., Dubois, M., Abdeddaim, R., Bendahan, D. and André, R. (2025) “Optimized reconstruction of undersampled Dixon sequences using new memory-efficient unrolled deep neural networks: HalfVarNet and HalfDIRCN,” Magnetic Resonance in Medicine [Preprint]. Available at: https://doi.org/10.1002/mrm.70070.
Nimje, S., Artières, T., Guye, M. and de Rochefort, L. (2025) “Insights on Scan-Specific Deep-Learning Strategies for Brain MRI Parallel Imaging Reconstruction,” NMR in biomedicine, 38(8), p. e70079. Available at: https://doi.org/10.1002/nbm.70079.
Mostame, P., Wirsich, J., Alderson, T., Ridley, B., Giraud, A.-L., Carmichael, D.W., Vulliemoz, S., Guye, M., Lemieux, L. and Sadaghiani, S. (2025) “A multiplex of connectome trajectories enables several connectivity patterns in parallel,” eLife, 13, p. RP98777. Available at: https://doi.org/10.7554/eLife.98777.
Mourre, H., Makhalova, J., Soncin, L., Garnier, E., Dary, H., Le Troter, A., Haast, R.A.M., Testud, B., Arthuis, M., Villalon, S.M., Lagarde, S., Pizzo, F., Bénar, C., Ranjeva, J.-P., Guye, M. and Bartolomei, F. (2025) “Nuclei-Specific Amygdala Enlargement Is Linked to Psychiatric Comorbidities in Drug-Resistant Focal Epilepsy,” Annals of Clinical and Translational Neurology [Preprint]. Available at: https://doi.org/10.1002/acn3.70071.
Cotinat, M., Messaoudi, N., Robinet, E., Suissa, L., Doche, E., Guye, M., Audoin, B., Bensoussan, L., Ranjeva, J.-P. and Zaaraoui, W. (2025) “Dynamics of Ionic and Cytotoxic Edema During Acute and Subacute Stages of Patients With Ischemic Stroke: Complementarity of 23Na MRI and Diffusion MRI,” NMR in biomedicine, 38(5), p. e70028. Available at: https://doi.org/10.1002/nbm.70028.
Dollomaja, B., Wang, H.E., Guye, M., Makhalova, J., Bartolomei, F. and Jirsa, V.K. (2025) “Virtual epilepsy patient cohort: Generation and evaluation,” PLoS computational biology, 21(4), p. e1012911. Available at: https://doi.org/10.1371/journal.pcbi.1012911.
Cotinat, M., Robinet, E., Messaoudi, N., Suissa, L., Doche, E., Guye, M., Bensoussan, L., Zaaraoui, W. and Ranjeva, J.-P. (2025) “Added Value of Sodium MR Imaging and Proton MR Spectroscopy to Conventional MR Imaging for a Better Characterization of the Ischemic Stroke: A Narrative Review,” Magnetic resonance in medical sciences: MRMS: an official journal of Japan Society of Magnetic Resonance in Medicine [Preprint]. Available at: https://doi.org/10.2463/mrms.rev.2025-0002.
Roger, C., Lasbleiz, A., Dary, H., Pini, L., Ancel, P., Kovarova, A., Ranjeva, M.-P., Darmon, P., Gaborit, B., Fu, Y., Cozzone, P.J., Guye, M., Dutour, A. and Ranjeva, J.-P. (2025) “Structural alterations of individual hypothalamic nuclei in young females with obesity and anorexia nervosa: an in vivo 7-T MRI study,” The American Journal of Clinical Nutrition, pp. S0002-9165(25)00071–1. Available at: https://doi.org/10.1016/j.ajcnut.2025.02.003.
Testud, B., Destruel, A., Troalen, T., Ranjeva, J.-P. and Guye, M. (2025) “Review of 7T MRI imaging of pituitary microadenomas: are we there yet?,” Neuroradiology [Preprint]. Available at: https://doi.org/10.1007/s00234-025-03554-9.
Licht, C., Ilicak, E., Boada, F.E., Guye, M., Zöllner, F.G., Schad, L.R. and Rapacchi, S. (2025) “A noise-robust post-processing pipeline for accelerated phase-cycled 23Na Multi-Quantum Coherences MRI,” Zeitschrift Fur Medizinische Physik, pp. S0939-3889(24)00117-X. Available at: https://doi.org/10.1016/j.zemedi.2024.12.004.
Martin, S., André, R., Trabelsi, A., Michel, C.P., Fortanier, E., Attarian, S., Guye, M., Dubois, M., Abdeddaim, R. and Bendahan, D. (2025) “Importance of neural network complexity for the automatic segmentation of individual thigh muscles in MRI images from patients with neuromuscular diseases,” Magma (New York, N.Y.) [Preprint]. Available at: https://doi.org/10.1007/s10334-024-01221-3.
Appukuttan, S., Grapperon, A.-M., El Mendili, M.M., Dary, H., Guye, M., Verschueren, A., Ranjeva, J.-P., Attarian, S., Zaaraoui, W. and Gilson, M. (2025) “Evaluating machine learning pipelines for multimodal neuroimaging in small cohorts: an ALS case study,” Frontiers in Neuroinformatics, 19, p. 1568116. Available at: https://doi.org/10.3389/fninf.2025.1568116.
Grapperon, A.-M., El Mendili, M.M., Maarouf, A., Ranjeva, J.-P., Guye, M., Verschueren, A., Attarian, S. and Zaaraoui, W. (2025) “In vivo mapping of sodium homeostasis disturbances in individual ALS patients: A brain 23Na MRI study,” PloS One, 20(1), p. e0316916. Available at: https://doi.org/10.1371/journal.pone.0316916.
Fortanier, E., Michel, C.P., Hostin, M.A., Delmont, E., Verschueren, A., Guye, M., Bellemare, M.-E., Bendahan, D. and Attarian, S. (2025) “Quantitative muscle MRI combined with AI-based segmentation as a follow-up biomarker for ATTRv patients: A longitudinal pilot study,” European Journal of Neurology, 32(1), p. e16574. Available at: https://doi.org/10.1111/ene.16574.
Kassinopoulos, M., Rolandi, N., Alphan, L., Harper, R.M., Oliveira, J., Scott, C., Kozák, L.R., Guye, M., Lemieux, L. and Diehl, B. (2025) “Brain connectivity correlates of breathing and cardiac patterns in epilepsy: A study including SUDEP cases,” Imaging Neuroscience (Cambridge, Mass.), 3, p. IMAG.a.918. Available at: https://doi.org/10.1162/IMAG.a.918.
Testud, B., Guye, M., Witjas, T. and Grimaldi, S. (2024) “Iron overload revealing the cytoarchitecture of the red nucleus: A case study,” Revue Neurologique, pp. S0035-3787(24)00660-X. Available at: https://doi.org/10.1016/j.neurol.2024.11.001.
Joppin, V., Jourdan, A., Bendahan, D., Soucasse, A., Guye, M., Masson, C. and Bège, T. (2024) “Towards a better understanding of abdominal wall biomechanics: In vivo relationship between dynamic intra-abdominal pressure and magnetic resonance imaging measurements,” Clinical Biomechanics (Bristol, Avon), 121, p. 106396. Available at: https://doi.org/10.1016/j.clinbiomech.2024.106396.
Durozard, P., Maarouf, A., Zaaraoui, W., Stellmann, J.-P., Boutière, C., Rico, A., Demortière, S., Guye, M., Le Troter, A., Dary, H., Ranjeva, J.-P., Audoin, B. and Pelletier, J. (2024) “Cortical Lesions as an Early Hallmark of Multiple Sclerosis: Visualization by 7 T MRI,” Investigative Radiology, 59(11), p. 747. Available at: https://doi.org/10.1097/RLI.0000000000001082.
Köksal-Ersöz, E., Makhalova, J., Yochum, M., Bénar, C.-G., Guye, M., Bartolomei, F., Wendling, F. and Merlet, I. (2024) “Whole-brain simulation of interictal epileptic discharges for patient-specific interpretation of interictal SEEG data,” Neurophysiologie Clinique = Clinical Neurophysiology, 54(5), p. 103005. Available at: https://doi.org/10.1016/j.neucli.2024.103005.
Fortanier, E., Hostin, M.A., Michel, C., Delmont, E., Bellemare, M.-E., Guye, M., Bendahan, D. and Attarian, S. (2024) “One-Year Longitudinal Assessment of Patients With CMT1A Using Quantitative MRI,” Neurology, 102(9), p. e209277. Available at: https://doi.org/10.1212/WNL.0000000000209277.
Grimaldi, S., Le Troter, A., El Mendili, M.M., Dary, H., Azulay, J.-P., Zaaraoui, W., Ranjeva, J.-P., Eusebio, A., de Rochefort, L. and Guye, M. (2024) “Energetic dysfunction and iron overload in early Parkinson’s disease: Two distinct mechanisms?,” Parkinsonism & Related Disorders, 124, p. 106996. Available at: https://doi.org/10.1016/j.parkreldis.2024.106996.
Tilsley, P., Moutiez, A., Brodovitch, A., Mendili, M.M.E., Testud, B., Zaaraoui, W., Verschueren, A., Attarian, S., Guye, M., Boucraut, J., Grapperon, A.-M. and Stellmann, J.-P. (2024) “Neurofilament Light Chain Levels Interact with Neurodegenerative Patterns and Motor Neuron Dysfunction in Amyotrophic Lateral Sclerosis,” American Journal of Neuroradiology, 45(4), pp. 494–503. Available at: https://doi.org/10.3174/ajnr.A8154.
Testud, B., Carle, X., Costes, C., Hak, J.-F. and Guye, M. (2024) “Added Value of Ultrahigh-Resolution 7T MRI in Dural Arteriovenous Fistulas,” Stroke, 55(3), pp. e46–e47. Available at: https://doi.org/10.1161/STROKEAHA.123.045930.
Soustelle, L., Mchinda, S., Hertanu, A., Gherib, S., Pini, L., Guye, M., Ranjeva, J.-P., Varma, G., Alsop, D.C., Pelletier, J., Girard, O.M. and Duhamel, G. (2024) “Inhomogeneous magnetization transfer (ihMT) imaging reveals variable recovery profiles of active MS lesions according to size and localization,” Imaging Neuroscience (Cambridge, Mass.), 2, p. imag–2–00235. Available at: https://doi.org/10.1162/imag_a_00235.
Lemaréchal, J.-D., Triebkorn, P., Vattikonda, A.N., Hashemi, M., Woodman, M., Guye, M., Bartolomei, F., Wang, H.E. and Jirsa, V. (2024) “Effects of the spatial resolution of the Virtual Epileptic Patient on the identification of epileptogenic networks,” Imaging Neuroscience (Cambridge, Mass.), 2, p. imag–2–00153. Available at: https://doi.org/10.1162/imag_a_00153.
Licht, C., Reichert, S., Bydder, M., Zapp, J., Corella, S., Guye, M., Zöllner, F.G., Schad, L.R. and Rapacchi, S. (2024) “Low-rank reconstruction for simultaneous double half-echo 23Na and undersampled 23Na multi-quantum coherences MRI,” Magnetic Resonance in Medicine, 92(4), pp. 1440–1455. Available at: https://doi.org/10.1002/mrm.30132.
Licht, C., Reichert, S., Guye, M., Schad, L.R. and Rapacchi, S. (2024) “Multidimensional compressed sensing to advance 23Na multi-quantum coherences MRI,” Magnetic Resonance in Medicine, 91(3), pp. 926–941. Available at: https://doi.org/10.1002/mrm.29902.
Azilinon, M., Wang, H.E., Makhalova, J., Zaaraoui, W., Ranjeva, J.-P., Bartolomei, F., Guye, M. and Jirsa, V. (2024) “Brain sodium MRI-derived priors support the estimation of epileptogenic zones using personalized model-based methods in epilepsy,” Network Neuroscience (Cambridge, Mass.), 8(3), pp. 673–696. Available at: https://doi.org/10.1162/netn_a_00371.
Wirsich, J., Iannotti, G.R., Ridley, B., Shamshiri, E.A., Sheybani, L., Grouiller, F., Bartolomei, F., Seeck, M., Lazeyras, F., Ranjeva, J.-P., Guye, M. and Vulliemoz, S. (2024) “Altered correlation of concurrently recorded EEG-fMRI connectomes in temporal lobe epilepsy,” Network Neuroscience (Cambridge, Mass.), 8(2), pp. 466–485. Available at: https://doi.org/10.1162/netn_a_00362.
Daudé, P., Roussel, T., Troalen, T., Viout, P., Hernando, D., Guye, M., Kober, F., Confort Gouny, S., Bernard, M. and Rapacchi, S. (2024) “Comparative review of algorithms and methods for chemical-shift-encoded quantitative fat-water imaging,” Magnetic Resonance in Medicine, 91(2), pp. 741–759. Available at: https://doi.org/10.1002/mrm.29860.
El Mendili, M.M., Verschueren, A., Ranjeva, J.-P., Guye, M., Attarian, S., Zaaraoui, W. and Grapperon, A.-M. (2023) “Association between brain and upper cervical spinal cord atrophy assessed by MRI and disease aggressiveness in amyotrophic lateral sclerosis,” Neuroradiology, 65(9), pp. 1395–1403. Available at: https://doi.org/10.1007/s00234-023-03191-0.
Testud, B., Fabiani, N., Demortière, S., Mchinda, S., Medina, N.L., Pelletier, J., Guye, M., Audoin, B., Stellmann, J.P. and Callot, V. (2023) “Contribution of the MP2RAGE 7T Sequence in MS Lesions of the Cervical Spinal Cord,” AJNR. American journal of neuroradiology, 44(9), pp. 1101–1107. Available at: https://doi.org/10.3174/ajnr.A7964.
Soustelle, L., Troalen, T., Hertanu, A., Ranjeva, J.-P., Guye, M., Varma, G., Alsop, D.C., Duhamel, G. and Girard, O.M. (2023) “Quantitative magnetization transfer MRI unbiased by on-resonance saturation and dipolar order contributions,” Magnetic Resonance in Medicine, 90(3), pp. 875–893. Available at: https://doi.org/10.1002/mrm.29678.
Lee, H.M., Hong, S.-J., Gill, R., Caldairou, B., Wang, I., Zhang, J., Deleo, F., Schrader, D., Bartolomei, F., Guye, M., Cho, K.H., Barba, C., Sisodiya, S., Jackson, G., Hogan, R.E., Wong-Kisiel, L., Cascino, G.D., Schulze-Bonhage, A., Lopes-Cendes, I., Cendes, F., Guerrini, R., Bernhardt, B., Bernasconi, N. and Bernasconi, A. (2023) “Multimodal mapping of regional brain vulnerability to focal cortical dysplasia,” Brain, 146(8), pp. 3404–3415. Available at: https://doi.org/10.1093/brain/awad060.
Guenoun, D., Wirth, T., Roche, D., Michel, C.P., Daudé, P., Ogier, A.C., Chagnaud, C., Mattei, J.P., Pini, L., Guye, M., Ollivier, M., Bendahan, D. and Guis, S. (2023) “Ultra-high field magnetic resonance imaging of the quadriceps tendon enthesis in healthy subjects,” Surgical and Radiologic Anatomy, 45(8), pp. 1049–1054. Available at: https://doi.org/10.1007/s00276-023-03175-y.
Graber, M., Cadour, F., El Ahmadi, A.A., Khati, I., Del Grande, J., Chagnaud, C., Fakhry, N., Guye, M. and Varoquaux, A. (2023) “Adding automated decision-tree models to multiparametric MRI for parotid tumours improves clinical performance,” European Journal of Radiology, 166, p. 110999. Available at: https://doi.org/10.1016/j.ejrad.2023.110999.
Cadour, F., Quemeneur, M., Biere, L., Donal, E., Bentatou, Z., Eicher, J.-C., Roubille, F., Lalande, A., Giorgi, R., Rapacchi, S., Cortaredona, S., Tradi, F., Bartoli, A., Willoteaux, S., Delahaye, F., Biene, S.M., Mangin, L., Ferrier, N., Dacher, J.-N., Bauer, F., Leurent, G., Lentz, P.-A., Kovacsik, H., Croisille, P., Thuny, F., Bernard, M., Guye, M., Furber, A., Habib, G. and Jacquier, A. (2023) “Prognostic value of cardiovascular magnetic resonance T1 mapping and extracellular volume fraction in nonischemic dilated cardiomyopathy,” Journal of Cardiovascular Magnetic Resonance: Official Journal of the Society for Cardiovascular Magnetic Resonance, 25(1), p. 7. Available at: https://doi.org/10.1186/s12968-023-00919-y.
Wang, H.E., Woodman, M., Triebkorn, P., Lemarechal, J.-D., Jha, J., Dollomaja, B., Vattikonda, A.N., Sip, V., Medina Villalon, S., Hashemi, M., Guye, M., Makhalova, J., Bartolomei, F. and Jirsa, V. (2023) “Delineating epileptogenic networks using brain imaging data and personalized modeling in drug-resistant epilepsy,” Science Translational Medicine, 15(680), p. eabp8982. Available at: https://doi.org/10.1126/scitranslmed.abp8982.
Haast, R.A.M., Testud, B., Makhalova, J., Dary, H., Cabane, A., Le Troter, A., Ranjeva, J.-P., Bartolomei, F. and Guye, M. (2023) “Multi-scale structural alterations of the thalamus and basal ganglia in focal epilepsy using 7T MRI,” Human Brain Mapping, 44(13), pp. 4754–4771. Available at: https://doi.org/10.1002/hbm.26414.
Destruel, A., Mauconduit, F., Massire, A., Abdeddaim, R., Guye, M., Gras, V. and Callot, V. (2023) “Optimized interferometric encoding of presaturated TurboFLASH B1 mapping for parallel transmission MRI at 7 T: Preliminary application for quantitative T1 mapping in the spinal cord,” Magnetic Resonance in Medicine, 90(4), pp. 1328–1344. Available at: https://doi.org/10.1002/mrm.29708.
Hostin, M.-A., Ogier, A.C., Michel, C.P., Le Fur, Y., Guye, M., Attarian, S., Fortanier, E., Bellemare, M.-E. and Bendahan, D. (2023) “The Impact of Fatty Infiltration on MRI Segmentation of Lower Limb Muscles in Neuromuscular Diseases: A Comparative Study of Deep Learning Approaches,” Journal of Magnetic Resonance Imaging, 58(6), pp. 1826–1835. Available at: https://doi.org/10.1002/jmri.28708.
Azilinon, M., Makhalova, J., Zaaraoui, W., Medina Villalon, S., Viout, P., Roussel, T., El Mendili, M.M., Ridley, B., Ranjeva, J.-P., Bartolomei, F., Jirsa, V. and Guye, M. (2023) “Combining sodium MRI, proton MR spectroscopic imaging, and intracerebral EEG in epilepsy,” Human Brain Mapping, 44(2), pp. 825–840. Available at: https://doi.org/10.1002/hbm.26102.
Scholly, J., Gras, A., Guye, M., Bilger, M., Valenti Hirsch, M.P., Hirsch, E., Timofeev, A., Vidailhet, P., Bénar, C.G. and Bartolomei, F. (2022) “Connectivity Alterations in Emotional and Cognitive Networks During a Manic State Induced by Direct Electrical Stimulation,” Brain Topography, 35(5), pp. 627–635. Available at: https://doi.org/10.1007/s10548-022-00913-0.
Maarouf, A., Audoin, B., Gherib, S., El Mendili, M.M., Viout, P., Pariollaud, F., Boutière, C., Rico, A., Guye, M., Ranjeva, J.-P., Zaaraoui, W. and Pelletier, J. (2022) “Grey-matter sodium concentration as an individual marker of multiple sclerosis severity,” Multiple Sclerosis Journal, 28(12), pp. 1903–1912. Available at: https://doi.org/10.1177/13524585221102587.
Forodighasemabadi, A., Baucher, G., Soustelle, L., Troalen, T., Girard, O.M., Guye, M., Grisoli, J.-B., Ranjeva, J.-P., Duhamel, G. and Callot, V. (2022) “Spinal cord and brain tissue impairments as long-term effects of rugby practice? An exploratory study based on T1 and ihMTsat measures,” NeuroImage. Clinical, 35, p. 103124. Available at: https://doi.org/10.1016/j.nicl.2022.103124.