Julien Cohen-Adad

Thomas Dagonneau

Master's Research - Polytechnique Montréal

Naga Karthik Enamundram

PhD - Polytechnique Montréal

Co-supervisor :

Sarath Chandar

emvnagakarthik@gmail.com

PhD - Polytechnique Montréal

Nathan Molinier

PhD - Polytechnique Montréal

Kalum Ost

Collaborating researcher

Simon Queric

Research Intern - Polytechnique Montréal

Abel Salmona Salmona

Research Intern - Polytechnique Montréal

abel.salmona@gmail.com

Julien Thouveny

Master's Research - Université de Montréal

Arthur Toulouse

Master's Research - Polytechnique Montréal

Jan Valosek

Postdoctorate - Polytechnique Montréal

Website

Google Scholar

Publications

<scp>RF</scp> shimming in the cervical spinal cord at <scp>7 T</scp>

Daniel Papp

Kyle M. Gilbert

Gaspard Cereza

Alexandre D'Astous

Nibardo Lopez‐Rios

Mathieu Boudreau

Marcus J. Couch

Pedram Yazdanbakhsh

Robert L. Barry

Eva Alonso‐Ortiz

2024-08-13

Magnetic Resonance in Medicine (published)

SCIsegV2: A Universal Tool for Segmentation of Intramedullary Lesions in Spinal Cord Injury

Enamundram Naga Karthik

Jan Valošek

Lynn Farner

Dario Pfyffer

Simon Schading-Sassenhausen

A. Lebret

Gergely David

Andrew Smith

Kenneth A. Weber

Maryam Seif

Rhscir Network Imaging Group

Patrick Freund

2024-07-24

ArXiv (preprint)

arxiv.org

Myelin basic protein mRNA levels affect myelin sheath dimensions, architecture, plasticity, and density of resident glial cells

Hooman Bagheri

Hana Friedman

Amanda Hadwen

Celia Jarweh

Ellis Cooper

Lawrence Oprea

Claire Guerrier

Anmar Khadra

Armand Collin

Amanda Young

Gerardo Mendez Victoriano

Matthew Swire

Andrew Jarjour

Marie E. Bechler

Rachel S. Pryce

Pierre Chaurand

Lise Cougnaud

Dajana Vuckovic

Elliott Wilion … (see 11 more)

Owen Greene

Akiko Nishiyama

Anouk Benmamar‐Badel

Trevor Owens

Vladimir Grouza

Marius Tuznik

Hanwen Liu

David A. Rudko

Jinyi Zhang

Katherine A. Siminovitch

Alan C. Peterson

2024-07-18

Glia (published)

Automatic Segmentation of the Spinal Cord Nerve Rootlets

Jan Valošek

Theo Mathieu

Raphaëlle Schlienger

Olivia S. Kowalczyk

Precise identification of spinal nerve rootlets is relevant to delineate spinal levels for the study of functional activity in the spinal co… (see more)rd. The goal of this study was to develop an automatic method for the semantic segmentation of spinal nerve rootlets from T2-weighted magnetic resonance imaging (MRI) scans. Images from two open-access MRI datasets were used to train a 3D multi-class convolutional neural network using an active learning approach to segment C2-C8 dorsal nerve rootlets. Each output class corresponds to a spinal level. The method was tested on 3T T2-weighted images from datasets unseen during training to assess inter-site, inter-session, and inter-resolution variability. The test Dice score was 0.67 +- 0.16 (mean +- standard deviation across rootlets levels), suggesting a good performance. The method also demonstrated low inter-vendor and inter-site variability (coefficient of variation= 1.41 %), as well as low inter-session variability (coefficient of variation= 1.30 %) indicating stable predictions across different MRI

2024-07-02

Imaging Neuroscience (published)

arxiv.org

Calibration‐free parallel transmission of the cervical, thoracic, and lumbar spinal cord at <scp>7T</scp>

Christoph S. Aigner

Manuel F. Sánchez Alarcon

Alexandre D'Astous

Eva Alonso‐Ortiz

Sebastian Schmitter

2024-05-10

Magnetic Resonance in Medicine (published)

Repeat it without me: Crowdsourcing the T1 mapping common ground via the ISMRM reproducibility challenge.

Mathieu Boudreau

Agah Karakuzu

Ecem Bozkurt

Madeline Carr

Marco Castellaro

Luis Concha

Mariya Doneva

Seraina A. Dual

Alex Ensworth

Alexandru Foias

Véronique Fortier

Refaat E. Gabr

Guillaume Gilbert

Carri K. Glide‐Hurst

Matthew Grech‐Sollars

Siyuan Hu

Oscar Jalnefjord

Jorge Jovicich

Kübra Keskin … (see 22 more)

Peter Koken

Anastasia Kolokotronis

Simran Kukran

Nam G. Lee

Ives R. Levesque

Bochao Li

Dan Ma

Burkhard Mädler

Nyasha G. Maforo

Jamie Near

Erick Pasaye

Alonso Ramirez‐Manzanares

Ben Statton

Christian Stehning

Stefano Tambalo

Ye Tian

Chenyang Wang

Kilian Weiss

Niloufar Zakariaei

Shuo Zhang

Ziwei Zhao

Nikola Stikov

PURPOSE T1 mapping is a widely used quantitative MRI technique, but its tissue-specific values remain inconsistent across protocols, sites, … (see more)and vendors. The ISMRM Reproducible Research and Quantitative MR study groups jointly launched a challenge to assess the reproducibility of a well-established inversion-recovery T1 mapping technique, using acquisition details from a seminal T1 mapping paper on a standardized phantom and in human brains. METHODS The challenge used the acquisition protocol from Barral et al. (2010). Researchers collected T1 mapping data on the ISMRM/NIST phantom and/or in human brains. Data submission, pipeline development, and analysis were conducted using open-source platforms. Intersubmission and intrasubmission comparisons were performed. RESULTS Eighteen submissions (39 phantom and 56 human datasets) on scanners by three MRI vendors were collected at 3 T (except one, at 0.35 T). The mean coefficient of variation was 6.1% for intersubmission phantom measurements, and 2.9% for intrasubmission measurements. For humans, the intersubmission/intrasubmission coefficient of variation was 5.9/3.2% in the genu and 16/6.9% in the cortex. An interactive dashboard for data visualization was also developed: https://rrsg2020.dashboards.neurolibre.org. CONCLUSION The T1 intersubmission variability was twice as high as the intrasubmission variability in both phantoms and human brains, indicating that the acquisition details in the original paper were insufficient to reproduce a quantitative MRI protocol. This study reports the inherent uncertainty in T1 measures across independent research groups, bringing us one step closer to a practical clinical baseline of T1 variations in vivo.

2024-05-10

Magnetic Resonance in Medicine (published)

Quantifying neurodegeneration of the cervical cord and brain in degenerative cervical myelopathy: A multicentre study using quantitative <scp>magnetic resonance imaging</scp>

Patrick Freund

Viveka Boller

Tim M. Emmenegger

Muhammad Akbar

Markus Hupp

Nikolai Pfender

Claudia A. M. Gandini Wheeler-Kingshott

Michael G. Fehlings

Armin Curt

Maryam Seif

2024-05-07

European Journal of Neurology (published)

Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study

René Labounek

Monica T. Bondy

Amy L. Paulson

Sandrine Bédard

Mihael Abramovic

Eva Alonso‐Ortiz

Nicole Atcheson

Laura R. Barlow

Robert L. Barry

Markus Barth

Marco Battiston

Christian Büchel

Matthew D. Budde

Virginie Callot

Anna Combes

Benjamin De Leener

Maxime Descoteaux

Paulo Loureiro de Sousa

Marek Dostál

Julien Doyon … (see 74 more)

Adam Dvorak

Falk Eippert

Karla R. Epperson

Kevin S. Epperson

Patrick Freund

Jürgen Finsterbusch

Alexandru Foias

Michela Fratini

Issei Fukunaga

Claudia A. M. Gandini Wheeler-Kingshott

Giancarlo Germani

Guillaume Gilbert

Federico Giove

Francesco Grussu

Akifumi Hagiwara

Pierre-Gilles Henry

Tomáš Horák

Masaaki Hori

James M. Joers

Kouhei Kamiya

Haleh Karbasforoushan

Miloš Keřkovský

Ali Khatibi

Joo‐Won Kim

Nawal Kinany

Hagen H. Kitzler

Shannon Kolind

Yazhuo Kong

Petr Kudlička

Paul Kuntke

Nyoman D. Kurniawan

Slawomir Kusmia

Maria Marcella Lagana

Cornelia Laule

Christine S. W. Law

Csw Law

Tobias Leutritz

Yaou Liu

Sara Llufriu

Sean Mackey

Allan R. Martin

Eloy Martinez-Heras

Loan Mattera

Kristin P. O’Grady

Nico Papinutto

Daniel Papp

Deborah Pareto

Todd B. Parrish

Anna Pichiecchio

Ferran Prados

Àlex Rovira

Marc J. Ruitenberg

Rebecca S. Samson

Giovanni Savini

Maryam Seif

Alan C. Seifert

Alex K. Smith

Seth A. Smith

Zachary A. Smith

Elisabeth Solana

Yuichi Suzuki

George Tackley

Alexandra Tinnermann

Jan Valošek

Dimitri Van De Ville

Marios C. Yiannakas

Kenneth A. Weber

Nikolaus Weiskopf

Richard G. Wise

Patrik O. Wyss

Junqian Xu

Christophe Lenglet

Igor Nestrašil

Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controllin… (see more)g for sources of biological variation such as subject’s sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1±6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44≤r≤0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21≥r≥-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20≥r≥-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39≤r≤0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22≥r≥-0.25). Linear mixture of sex and age explained 26±10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33±11% when body height was added into the mixture model. Age itself explained only 2±2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure.

2024-05-01

bioRxiv (preprint)

Spinal cord perfusion impairments in the M83 mouse model of Parkinson’s disease

Benjamin F. Combes

Sandeep Kumar Kalva

Pierre-Louis Benveniste

Agathe Tournant

Man Hoi Law

Joshua Newton

Maik Krüger

Rebecca Z. Weber

Inês Dias

Daniela Noain

Xose Luis Dean-Ben

Uwe Konietzko

Christian R. Baumann

Per-Göran Gillberg

Christoph Hock

Roger M. Nitsch

Daniel Razansky

Ruiqing Ni

Metabolism and bioenergetics in the central nervous system play important roles in the pathophysiology of Parkinson’s disease (PD). Here, … (see more)we employed a multimodal imaging approach to assess oxygenation changes in the spinal cord of a transgenic M83 murine model of PD in comparison to non-transgenic littermates at 9-12 months-of-age. A lower oxygen saturation (SO2)SVOT was detected in vivo with spiral volumetric optoacoustic tomography (SVOT) in the spinal cord of M83 mice compared to non-transgenic littermate mice. Ex-vivo high-field T1-weighted magnetic resonance imaging (MRI) and immunostaining for alpha-synuclein (phospho-S129) and vascular organisation (CD31 and GLUT1) were used to investigate the nature of the abnormalities detected via in vivo imaging. Ex-vivo analysis showed that the vascular network in the spinal cord was not impaired in the spinal cord of M83 mice. Ex-vivo MRI assisted with deep learning-based automatic segmentation showed no volumetric atrophy in the spinal cord of M83 mice compared to non-transgenic littermates, whereas nuclear alpha-synuclein phosphorylated at Ser129 site could be linked to early pathology and metabolic dysfunction. The proposed and validated non-invasive high-resolution imaging tool to study oxygen saturation in the spinal cord of PD mice holds promise for assessing early changes preceding motor deficits in PD mice.

2024-04-29

bioRxiv (preprint)

Contrast-agnostic Spinal Cord Segmentation: A Comparative Study of ConvNets and Vision Transformers

Enamundram Naga Karthik

Sandrine Bédard

Jan Valošek

Sarath Chandar

The cross-sectional area (CSA) of the spinal cord (SC) computed from its segmentation is a relevant clinical biomarker for the diagnosis and… (see more) monitoring of cord compression and atrophy. One key limitation of existing automatic methods is that their SC segmentations depend on the MRI contrast, resulting in different CSA across contrasts. Furthermore, these methods rely on CNNs, leaving a gap in the literature for exploring the performance of modern deep learning (DL) architectures. In this study, we extend our recent work \cite{Bdard2023TowardsCS} by evaluating the contrast-agnostic SC segmentation capabilities of different classes of DL architectures, namely, ConvNeXt, vision transformers (ViTs), and hierarchical ViTs. We compared 7 different DL models using the open-source \textit{Spine Generic} Database of healthy participants

2024-04-27

MIDL.io/2024/Short_Papers (accepted)

openreview.net

Advanced MRI metrics improve the prediction of baseline disease severity for individuals with degenerative cervical myelopathy

Abdul Al-Shawwa

Kalum Ost

David Anderson

Newton Cho

Nathan Evaniew

W. Bradley Jacobs

Allan R. Martin

Ranjeet Gaekwad

Saswati Tripathy

Jacques Bouchard

Steven Casha

Roger Cho

Stephen duPlessis

Peter Lewkonia

Fred Nicholls

Paul T. Salo

Alex Soroceanu

Ganesh Swamy

Kenneth C. Thomas

Michael M.H. Yang … (see 2 more)

David W. Cadotte

2024-04-01

The spine journal (published)

A database of the healthy human spinal cord morphometry in the PAM50 template space

Jan Valošek

Sandrine Bédard

Miloš Keřkovský

Tomáš Rohan

Abstract Measures of spinal cord morphometry computed from magnetic resonance images serve as relevant prognostic biomarkers for a range of … (see more)spinal cord pathologies, including traumatic and non-traumatic spinal cord injury and neurodegenerative diseases. However, interpreting these imaging biomarkers is difficult due to considerable intra- and inter-subject variability. Yet, there is no clear consensus on a normalization method that would help reduce this variability and more insights into the distribution of these morphometrics are needed. In this study, we computed a database of normative values for six commonly used measures of spinal cord morphometry: cross-sectional area, anteroposterior diameter, transverse diameter, compression ratio, eccentricity, and solidity. Normative values were computed from a large open-access dataset of healthy adult volunteers (N = 203) and were brought to the common space of the PAM50 spinal cord template using a newly proposed normalization method based on linear interpolation. Compared to traditional image-based registration, the proposed normalization approach does not involve image transformations and, therefore, does not introduce distortions of spinal cord anatomy. This is a crucial consideration in preserving the integrity of the spinal cord anatomy in conditions such as spinal cord injury. This new morphometric database allows researchers to normalize based on sex and age, thereby minimizing inter-subject variability associated with demographic and biological factors. The proposed methodology is open-source and accessible through the Spinal Cord Toolbox (SCT) v6.0 and higher.

2024-02-02

Imaging Neuroscience (published)