Julien Cohen-Adad

thomas.dagonneau@mila.quebec

Thomas Dagonneau

Master's Research - Polytechnique Montréal

Naga Karthik Enamundram

PhD - Polytechnique Montréal

Co-supervisor :

Sarath Chandar

emvnagakarthik@gmail.com

Master's Research - Polytechnique Montréal

paul.hoareau@mila.quebec

youssef.laatar@mila.quebec

Youssef Laatar

Master's Research - Polytechnique Montréal

julien.laborde-peyre@mila.quebec

Julien Laborde-Peyré

Research Intern - Polytechnique Montréal

nilser.lainesmedina@mila.quebec

Nilser Laines Medina

PhD - Polytechnique Montréal

Nathan Molinier

PhD - Polytechnique Montréal

nathan.molinier@mila.quebec

revillon.quentin@mila.quebec

Quentin Revillon

Research Intern - Polytechnique Montréal

arthur.toulouse@mila.quebec

Arthur Toulouse

Master's Research - Polytechnique Montréal

Publications

<scp>1D</scp> Pre‐Acquisition Navigator Correcting Respiratory‐Induced Field Fluctuations in Multi‐Echo Gradient‐Echo Imaging of the Thoracic Spinal Cord

Alicia E. Cronin

Alexandre D’Astous

Nathan Williams

Antoine Guénette

Aimee Salakhov

Seth Stubblefield

Colin D. Mcknight

Lipika Narisetti

Subramaniam Sriram

Seth A. Smith

Ryan K. Robison

Guillaume Gilbert

Julien Cohen‐Adad

Kristin P. O’Grady

PURPOSE: In the spinal cord (SC), multi-echo gradient echo (ME-GRE) increases gray (GM) and white matter (WM) contrast and improves sensitiv… (see more)ity to lesions in people with multiple sclerosis (pwMS). However, SC ME-GRE is susceptible to breathing-induced field fluctuations, causing ghosting artifacts and signal loss. Recent work introduced a 1D phase navigator following the last echo to measure field variations; however, susceptibility to phase wrapping increases at longer echo times. We propose a 1D phase navigator preceding the first echo, reducing phase accumulation and eliminating the need for respiratory monitoring. METHODS: ME-GRE data covering the lower (T9-T12 vertebrae) and upper (T4-T8 vertebrae) thoracic SC were acquired in 20 healthy volunteers and 3 pwMS at 3T. Standard and navigator-corrected images were acquired in the same acquisition. To evaluate image quality, WM and GM signal-to-noise ratio (SNR), WM/GM contrast-to-noise ratio (CNR), and background ghosting signals were measured and compared between the two reconstructions. Both were blindly assessed for artifacts, structural delineation, and diagnostic confidence in pwMS. RESULTS: Navigator correction significantly increased GM and WM SNR and CNR, reduced posterior ghosting across both thoracic regions, and significantly reduced artifacts while increasing structural delineation. Preliminary evaluation in three pwMS showed consistent improvements in artifact mitigation, structural delineation, and lesion conspicuity with navigator correction, providing proof-of-concept for potential clinical application. CONCLUSION: A 1D navigator prior to the first echo reduces ghosting and improves thoracic SC image quality without respiratory monitoring. This approach could improve the diagnostic value and enhance the reliability of thoracic SC ME-GRE.

2026-07-23

Magnetic Resonance in Medicine (published)

Patterns of Muscle Health in Single- and Multi-Site Chronic Pain: A UK Biobank Normative Modeling Study

Merve Kaptan

Yiyu Wang

Augustijn de Boer

Ananya Goyal

Skylar Holmes

Kerem Ozkan

Teresa Indriolo

Christine S W Law

Dario Pfyffer

Joel Fundaun

Estifanos Berhe

Garry E. Gold

Akshay Chaudhari

Anoosha Pai S

Anthony A. Gatti

Feliks Kogan

Brian A. Hargreaves

Scott L. Delp

John Ratliff … (see 21 more)

Serena Hu

Anand Veeravagu

Atman Desai

Suzanne Tharin

Todd Alamin

Andrew C. Smith

Marnee J. McKay

Brian Kim

Robert Walsh

Alec Schielke

Dean Dennis

Johannes Decker

Benjamin De Leener

Zachary A. Smith

Fauziyya Muhammad

James M. Elliott

Andre F. Marquand

Sean Mackey

Evert Onno Wesselink

Kenneth A. Weber II

Abstract Background Chronic pain is associated with impaired muscle health, but whether these changes reflect site-specific factors, broader… (see more) systemic factors, or both remains unclear. The purpose of this study is to determine whether normative markers of muscle health derived from MRI show site-specific patterns in chronic pain. Methods UK Biobank participants who underwent whole-body MRI from 2006 to 2010 were included in this retrospective cross-sectional study. The MuscleMap Toolbox quantified volume and intramuscular fat (IMF) in 42 muscles of the abdomen, pelvis, and thigh. Normative models trained on a no pain group generated muscle-specific deviations from normal (i.e., Z-scores) for single- and multi-site chronic and acute pain. Results Of 17,843 participants, the primary site-specific analysis included 9,704 no pain, 885 single-site chronic back pain (CBP), 438 single-site chronic hip pain (CHP), and 1,315 single-site chronic knee pain (CKP) participants (n=12,342; mean age 63.7±7.5 years; 52.7% female). Additional analyses included single-site chronic neck/shoulder pain, acute pain, and multi-site chronic pain groups. In CBP, deviations were localized to abdominal muscles, with decreased volume in 6/8 and increased IMF in 6/8. In CHP, deviations were broad, with decreased volume in 3/8 of the abdominal and 14/26 of the thigh muscles, and increased IMF in 6/8 of the abdominal, 5/8 of the pelvic, and 4/26 of the thigh muscles. In CKP, deviations were localized to thigh muscles, with decreased volume in 8/26 and increased IMF in 6/26. Acute pain groups showed no significant differences except for decreased volume in one thigh muscle in acute knee pain. With each additional chronic pain site, volume decreased (β=−.078;IQR:−0.100−0.051), and IMF increased (β=.085;IQR:0.066−0.101). Combined Z-scores classified chronic pain groups better than chance (accuracy: 48.6%;p<.001), but not acute pain groups (accuracy: 39.0%;p=.20). Conclusions Whole-body MRI combined with AI-driven muscle segmentation and normative modeling revealed site-specific patterns of muscle health in single-site chronic pain.

2026-06-21

medRxiv (preprint)

Charting Cervical Spinal Cord Morphometry Across the Lifespan

Kurt Schilling

Michael E Kim

Matthew Amandola

Chenyu Gao

Karthik Ramadass

Praitayini Kanakaraj

Sam Bogdanov

G Rudravaram

Nancy R. Newlin

Derek B. Archer

Timothy J Hohman

Angela L Jefferson

Victoria L Morgan

Alexandra Roche

Dario J Englot

Murat Bilgel

Lori L Beason-Held

Luigi Ferrucci

Laurie Cutting

Laura A Barquero … (see 21 more)

Micah D’Archangel

Tin Q Nguyen

Kathryn L Humphreys

Yanbin Niu

Sophia Vinci-Booher

Carissa J. Cascio

Zhiyuan Li

Daniel Moyer

Simon Vandekar

Panpan Zhang

Samuelle St-Onge

Jan Valosek

Benjamin De Leener

John C Gore

Seth Smith

B A Landman

John C. Gore

Seth Smith

Bennett A. Landman

Abstract Spinal cord morphometry provides essential biomarkers of neurological health, but clinical interpretations are confounded by inter-… (see more)subject variability and a lack of normative references across the full human lifespan. We address this gap by generating the first comprehensive lifespan charts for cervical spinal cord morphometry. We leveraged 30 population-based brain MRI datasets, aggregating 78,269 scans from 41,042 individuals (ages 0–100) whose imaging protocols included cervical cord coverage. To overcome contrast variability, we employed a state-of-the-art contrast-agnostic deep learning segmentation method, extracting cross-sectional area (CSA), anteroposterior (AP) and right–left (RL/transverse), and shape indices (compression ratio, eccentricity, and solidity) from C1 to C7. Normative trajectories were modeled using Generalized Additive Models for Location, Scale, and Shape (GAMLSS). The resulting charts reveal distinct non-linear lifespan changes: rapid growth through childhood and adolescence, peak maturation occurring in early-to-mid adulthood (e.g., mid-30s for CSA), followed by gradual decreases. Significant regional variations along the cervical cord and consistent sex differences (males > females for size metrics) were quantified. Spinal cord trajectories showed strong temporal coupling with brain white matter and brainstem volumes, suggesting integrated CNS development and aging. These lifespan charts provide a robust normative framework, enabling age- and sex-specific centile scoring of individual spinal cord morphometry. This resource offers a critical tool for differentiating typical variation from pathological changes, enhancing the clinical utility of spinal cord MRI in studies of development and neurodegeneration.

2026-06-07

bioRxiv (accepted)

Automated robust segmentation of the spinal canal on MRI

Abel Salmona

Jan Valosek

Kalum Ost

Maxime Bouthillier

Gergely David

Maryam Seif

Armin Curt

Nikolai Pfender

Markus Hupp

Patrick Freund

Tomáš Horák

Petr Kudlička

Josef Bednařík

Fauziyya Muhammad

Zachary A. Smith

2026-05-31

European Journal of Radiology Artificial Intelligence (published)

Spinal cord imaging for multiple sclerosis: Advances, priorities, and opportunities

Cornelia Laule

Atlee A Witt

Gabriele C De Luca

Cristina Granziera

B Mark Keegan

Anne Kerbrat

Eric C Klawiter

Shannon Kolind

Kristin P O’Grady

Jiwon Oh

Kurt G Schilling

Dinesh K Sivakolundu

Seth A Smith

Ceren Tozlu

Irene M Vavasour

Francesca Bagnato

Susan A Gauthier

Caterina Mainero

Eva Alonso-Ortiz … (see 9 more)

Rohit Bakshi

Erin S Beck

Matthew R Brier

Christopher C Hemond

Stephen Krieger

David KB Li

Russell T Shinohara

Roland G Henry

North American Imaging in Multiple Sclerosis (NAIMS) Cooperative

The spinal cord plays a central role in the pathophysiology and clinical manifestations of multiple sclerosis (MS), yet remains under-studie… (see more)d compared with the brain. This review summarizes key insights from the 2025 North American Imaging in MS Spinal Cord Imaging Workshop, highlighting recent advances, ongoing challenges, and future opportunities in MS spinal cord imaging. We review pathological studies and outline the clinical relevance of spinal cord lesions and atrophy for diagnosis, prognosis, and disease monitoring, highlighting emerging biomarkers of progression independent of relapse activity. Correlations between magnetic resonance imaging, histopathology, and clinical outcomes support the validation and translational potential of advanced spinal cord imaging techniques. Finally, we discuss spinal cord–specific processing pipelines and reproducibility challenges. Collectively, these insights underscore the need to integrate advanced and quantitative spinal cord imaging into clinical trials, research studies, and—when feasible—clinical care, to fully capture the extent of MS pathology, and ultimately improve patient outcomes.

2026-05-31

Multiple Sclerosis Journal (published)

Optimization in Sparse 2D to Dense 3D Weakly Supervised Learning: Application to Multi-Label Segmentation of Large ex vivo MRI Data

Paul Hoareau

Kuan Yi Wang

Brandon Bujak

Roy Sun

Govind Nair

Irene Cortese

Charidimos Tsagkas

Daniel Reich

INTRODUCTION | Fully supervised 3D segmentation of high-resolution ex vivo MRI is limited by the prohibitive cost of volumetric annotation, … (see more)forcing reliance on sparse 2D slices. Weakly supervised Sparse-to-Dense frameworks bridge this gap, but guidelines remain ambiguous regarding human-centric visual enhancements and transferring optimization strategies across dimensions. We analyze divergent regularization needs for multi-class segmentation of high-resolution ex vivo spinal cord MRI. METHODS | We used 9.4T MRI of multiple sclerosis spinal cords (>104,000 slices) with sparse annotations (428 slices). A 2D Teacher trained on sparse slices generated dense pseudo-labels to train a 3D Student. We systematically evaluated the impact of human-centric preprocessing, spatial augmentation, and soft-label regularization on both architectures. RESULTS | We identified a critical divergence in training dynamics. The 2D Teacher required strong spatial augmentation and soft-labeling to overcome data scarcity, improving White Matter Lesion Dice scores by>11 points. However, propagating these techniques to the 3D Student degraded its performance. Furthermore, human-centric preprocessing (e.g., CLAHE) disrupted global statistical cues, dropping Gray Matter Lesion Dice scores by ~25 points. DISCUSSION | Our study highlights a perception divergence (human-centric contrast enhancement harms machine models) and a regularization conflict across dimensions. 3D architectures trained on dense pseudo-labels exhibit fundamentally different optimization landscapes than 2D counterparts and require distinct, conservative regularization. Code and models: https://github.com/ivadomed/model_seg_sc-gm-lesion_human_ms_exvivo_t2star.

2026-05-11

arXiv (preprint)

arxiv.org

One Sequence to Segment Them All: Efficient Data Augmentation for CT and MRI Cross-Domain 3D Spine Segmentation

Nathan Molinier

Hendrik Möller

Thomas Dagonneau

Anna Curto-Vilalta

Robert Graf

Matan Atad

Daniel Rueckert

Jan S. Kirschke

Deep learning-based medical image segmentation is increasingly used to support clinical diagnosis and develop new treatment strategies. Howe… (see more)ver, model performance remains limited by the scarcity of high-quality annotated data and insufficient generalization across imaging protocols. This limitation is particularly evident in MRI and CT, where models are typically trained on a single acquisition sequence and exhibit reduced robustness when applied to unseen sequences or contrasts. Although data augmentation is widely used to improve general robustness on medical images, its impact on cross-modality generalization has not been quantitatively explored. In this work, we study a targeted set of data augmentation techniques designed to improve cross-modality transfer. We train three spine segmentation models, each on a single-modality/sequence dataset, and evaluate them across seven out-of-distribution datasets (spanning CT and MRI), reflecting a realistic single-sequence training and multi-sequence/contrast/modality deployment scenario. Our results demonstrate substantial performance gains on unseen domains (average Dice gain of 155 %) while preserving in-domain accuracy (average Dice decrease of 0.008 %), including effective transfer between CT and MRI. To mitigate the computational cost typically associated with strong data augmentation, we implement GPU-optimized augmentations that maintain, and even improve, training efficiency by approximately 10 %. We release our approach as an open-source toolbox, enabling seamless integration into commonly used frameworks such as nnUNet and MONAI. These augmentations significantly enhance robustness to heterogeneous clinical imaging scenarios without compromising training speed.

2026-05-03

arXiv (preprint)

arxiv.org

Segmentation of spinal rootlets across MRI contrasts with RootletSeg.

Katerina Krejci

Jiri Chmelik

Falk Eippert

Ulrike Horn

Virginie Callot

Jan Valosek

Segmentation of spinal nerve rootlets is relevant for spinal level estimation, lesion classification, neuromodulation therapy, and group-lev… (see more)el analyses. The aim of this study was to develop a deep learning method for the automatic segmentation of C2-T1 dorsal and ventral spinal nerve rootlets on various MRI scans. The study included MRI scans from two open-access and one private dataset, consisting of 3D isotropic 3T turbo spin echo T2-weighted (T2w) and 7T MP2RAGE (T1-weighted [T1w] INV1 and INV2, and UNIT1) MRI scans. A deep learning model, RootletSeg, was developed on 93 MRI scans from 50 healthy adults (mean age, 28.70 years ± 6.53 [SD]; 28 [56%] males, 22 [44%] females) and achieved a mean ± SD Dice score of 0.67 ± 0.09 for T1w-INV2, 0.65 ± 0.11 for UNIT1, 0.64 ± 0.08 for T2w, and 0.62 ± 0.10 for T1w-INV1 contrasts. RootletSeg accurately segmented C2-T1 spinal rootlets across MRI contrasts, enabling the determination of spinal levels directly from MRI scans. The method is open-source and can be used for a variety of downstream analyses.

2026-05-01

Scientific Reports (published)

Automatic multiple sclerosis lesion segmentation in the spinal cord using 3 T and 7 T MP2RAGE images

Nilser Laines Medina

Samira Mchinda

Benoit Testud

Sarah Demortière

Emanuele Pravatà

Govind Nair

Daniel S. Reich

Cristina Granziera

Charidimos Tsagkas

Virginie Callot

2026-04-30

Multiple Sclerosis and Related Disorders (published)

Generalizable spinal cord multiple sclerosis lesion segmentation across MRI contrasts, protocols, and centers

Pierre‐Louis Benveniste

Laurent Létourneau‐Guillon

David Araújo

Lydia Chougar

Dumitru Fetco

Masaaki Hori

Kouhei Kamiya

Steven Messina

Charidimos Tsagkas

Bertrand Audoin

Rohit Bakshi

Élise Bannier

Daniel Blezek

Jean‐Christophe Brisset

Virginie Callot

Erik Charlson

Michelle Chen

Olga Ciccarelli

Sarah Demortière

Gilles Edan … (see 36 more)

M Filippi

Tobias Granberg

Cristina Granziera

Christopher C. Hemond

B. Mark Keegan

Anne Kerbrat

J Kirschke

Petr Kudlička

Pierre Labauge

Lisa Eunyoung Lee

Yaou Liu

Caterina Mainero

Julian McGinnis

Nilser Laines Medina

Mark Mühlau

Govind Nair

Kristin P. O’Grady

Jiwon Oh

Russell Ouellette

Alexandre Prat

Daniel S. Reich

Maria A. Rocca

Timothy M. Shepherd

Seth A. Smith

Leszek Stawiarz

Jason Talbott

Roger Tam

Shahamat Tauhid

Anthony Traboulsee

Constantina A. Treaba

Paola Valsasina

Zachary Vavasour

Marios Yiannakas

Hervé Lombaert

Shannon Kolind

The proposed model can achieve accurate and reliable spinal cord MS lesion segmentation across heterogeneous MRI data, addressing a key barr… (see more)ier to clinical translation. The model is available in the Spinal Cord Toolbox v7.2 and higher.Code repository: https://github.com/ivadomed/seg-sc-ms-lesion-multicontrast.

2026-04-23

Multiple Sclerosis Journal (published)

White and Gray Matter Multiple Sclerosis Spinal Cord Lesion Characteristics and Individualized Tissue Damage Assessment Using 7 T T1 Mapping

Nilser Laines-Medina

Samira Mchinda

Benoit Testud

Arnaud Le Troter

Lauriane Pini

Bertrand Audoin

Jean Pelletier

Sarah Demortière

Virginie Callot

The aim of this exploratory study was to demonstrate how 7 T MP2RAGE T1 mapping can be used to evaluate spinal cord (SC) tissue damage and l… (see more)esion characteristics in multiple sclerosis (MS) at both subregional and individual levels. Fifteen patients with relapsing-remitting MS (pwRRMS; mean disease duration = 32 ± 24.9 mo) and 15 age-matched healthy controls (HC) underwent 7 T cervical 3D MP2RAGE imaging with submillimetric spatial resolution. Automatic SC and lesion segmentations were obtained and manually corrected when necessary. Images were registered to the AMU7T template space to extract T1 values from specific regions of interest (ROIs), including white matter (WM) tracts: corticospinal (CST), lateral sensory (LST), posterior sensory (PST), ventral motor (VMT), and gray matter (GM) subregions: ventral, intermediate, and dorsal. Individual Z -score maps were computed and used to derive a global index of tissue impairment (patient-specific Z -score barplot) for lesion and normal appearing tissues (NAT). Finally, MS lesions were further characterized by their relative lesion load (RLL%), frequency maps, and topography across ROIs. Lesions were predominantly located in the posterior half of the cord, with GM showing the highest RLL. However, no lesions were observed exclusively in GM. An increasing gradient in T1 values was observed, with T1_HC 0.01). Mixed GM-WM lesions exhibited higher T1 values and larger volumes than WM-only lesions. Elevated T1 values

2026-04-12

Investigative Radiology (published)

Spatial distribution of spinal cord fMRI activity with electrocutaneous stimulation

Merve Kaptan

Teresa Indriolo

Christine SW Law

Dario Pfyffer

Lindsay Lee

John K Ratliff

Serena S. Hu

Suzanne Tharin

Zachary A. Smith

GARY GLOVER

Sean C Mackey

Kenneth A. Weber

Sensory organization at the spinal segment level is commonly inferred from dermatomal maps that assume a fixed correspondence between cutane… (see more)ous regions and spinal segments. However, based on the complexities of spinal neuroanatomy and neurophysiology, the distribution of sensory signals within the cord may be broader and less segment-specific than dermatomal maps suggest, leaving the segment-level localization of sensory-evoked activity in humans uncertain. Spinal cord functional magnetic resonance imaging (fMRI) is currently the only technique capable of noninvasively mapping sensory activity with high spatial resolution in the human spinal cord. However, its application remains technically challenging and is limited by the uncertainty in segmental localization. In this study, we leveraged recent advancements in spinal cord fMRI, including spinal nerve rootlet-based spatial normalization, to investigate how sensory information is represented and distributed within the human spinal cord during electrocutaneous stimulation of the third digit of the right hand (i.e., C7 dermatome). Forty healthy adults were scanned with electrocutaneous stimulation at four individualized intensities across multiple runs to quantify (i) the rostrocaudal distribution of sensory-evoked activity, (ii) intensity-dependent changes in detectability and localization, and (iii) the effect of normalization strategy on segmental localization. Across participants, stimulation produced activation localized in the lower cervical cord (e.g., C6-C8), with the most consistent segmental localization near C7. Stronger stimulation increased detectability and produced more consistent segmental localization across participants. Importantly, normalization that incorporated nerve rootlet landmarks sharpened localization and improved sensitivity relative to conventional intervertebral disc-based alignment. This highlights the value of functionally relevant anatomical landmarks for group inference in the spinal cord. Responses were strongest in the initial run and attenuated with repetition, suggesting habituation or adaptation that can bias multi-run paradigms if unmodeled. Together, our results define practical acquisition and analysis conditions (e.g., stimulation strength, anatomical alignment strategy, and run structure) under which segment-level spinal sensory responses can be detected, thereby supporting more reliable studies of human spinal cord future basic and translational studies, including pain mechanisms, sensory function, and spinal injury.

2026-03-01

medRxiv (preprint)