Julien Cohen-Adad

Thomas Dagonneau

Maîtrise recherche - Polytechnique

Naga Karthik Enamundram

Doctorat - Polytechnique

Co-superviseur⋅e :

Sarath Chandar

emvnagakarthik@gmail.com

Doctorat - Polytechnique

Nathan Molinier

Doctorat - Polytechnique

Kalum Ost

Collaborateur·rice de recherche

Simon Queric

Stagiaire de recherche - Polytechnique

Abel Salmona Salmona

Stagiaire de recherche - Polytechnique

abel.salmona@gmail.com

Julien Thouveny

Maîtrise recherche - UdeM

Arthur Toulouse

Maîtrise recherche - Polytechnique

Jan Valosek

Postdoctorat - Polytechnique

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Publications

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, … (voir plus)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 (prépublication)

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… (voir plus) 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 (accepté)

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 … (voir 2 de plus)

David W. Cadotte

2024-04-01

The spine journal (publié)

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 … (voir plus)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 (publié)

The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Russell A. Poldrack

Christopher J. Markiewicz

Stefan Appelhoff

Yoni K. Ashar

Tibor Auer

Sylvain Baillet

Shashank Bansal

Leandro Beltrachini

Christian G. Benar

C. Bénar

Giacomo Bertazzoli

Suyash Bhogawar

Ross W. Blair

Marta Bortoletto

Mathieu Boudreau

Teon L. Brooks

Vince D. Calhoun

Filippo Maria Castelli

Patricia Clement

Alexander L. Cohen … (voir 100 de plus)

Sasha D’Ambrosio

Gilles de Hollander

María de la Iglesia-Vayá

Alejandro de la Vega

Arnaud Delorme

Orrin Devinsky

Dejan Draschkow

Eugene Paul Duff

E. Duff

Elizabeth DuPre

Eric Earl

Oscar Esteban

Franklin W. Feingold

Guillaume Flandin

Anthony Galassi

Giuseppe Gallitto

Melanie Ganz

Rémi Gau

James Gholam

Sulagna Dia Ghosh

Satrajit S. Ghosh

Alessio Giacomel

Ashley G. Gillman

Padraig Gleeson

Alexandre Gramfort

Samuel Guay

Giacomo Guidali

Yaroslav O. Halchenko

Daniel A. Handwerker

Nell Hardcastle

Peer Herholz

Dora Hermes

Christopher J. Honey

C. Honey

Robert B. Innis

Horea-Ioan Ioanas

Andrew Jahn

Agah Karakuzu

David B. Keator

Gregory Kiar

Balint Kincses

Angela R. Laird

Jonathan C. Lau

Alberto Lazari

Jon Haitz Legarreta

Adam Li

Xiangrui Li

Bradley C. Love

Hanzhang Lu

Eleonora Marcantoni

Camille Maumet

Giacomo Mazzamuto

Steven L. Meisler

Mark Mikkelsen

Henk Mutsaerts

Thomas E. Nichols

Aki Nikolaidis

Gustav Nilsonne

Guiomar Niso

Martin Norgaard

Thomas W. Okell

Robert Oostenveld

Eduard Ort

Patrick J. Park

Mateusz Pawlik

Cyril R. Pernet

Franco Pestilli

Jan Petr

Christophe Phillips

Jean-Baptiste Poline

Luca Pollonini

P. Raamana

Pradeep Reddy Raamana

Petra Ritter

Gaia Rizzo

Kay A. Robbins

Alexander P. Rockhill

Christine Rogers

Ariel Rokem

Chris Rorden

Alexandre Routier

Jose Manuel Saborit-Torres

Taylor Salo

Michael Schirner

Robert E. Smith

Tamas Spisak

Julia Sprenger

Nicole C. Swann

Martin Szinte

Sylvain Takerkart

Bertrand Thirion

Adam G. Thomas

Sajjad Torabian

Gael Varoquaux

Bradley Voytek

Julius Welzel

Martin Wilson

Tal Yarkoni

Krzysztof J. Gorgolewski

2024-01-09

ArXiv (prépublication)

SCIseg: Automatic Segmentation of T2-weighted Hyperintense Lesions in Spinal Cord Injury

Enamundram Naga Karthik

Jan Valošek

Andrew C. Smith

Dario Pfyffer

Simon Schading-Sassenhausen

Lynn Farner

Kenneth A. Weber

Patrick Freund

Background: Quantitative MRI biomarkers in spinal cord injury (SCI) can help understand the extent of the focal injury. However, due to the … (voir plus)lack of automatic segmentation methods, these biomarkers are derived manually, which is a time-consuming process prone to intra- and inter-rater variability, thus limiting large multi-site studies and translation to clinical workflows. Purpose: To develop a deep learning tool for the automatic segmentation of T2-weighted hyperintense lesions and the spinal cord in SCI patients. Material and Methods: This retrospective study included a cohort of SCI patients from three sites enrolled between July 2002 and February 2023 who underwent clinical MRI examination. A deep learning model, SCIseg, was trained on T2-weighted images with heterogeneous image resolutions (isotropic, anisotropic), and orientations (axial, sagittal) acquired using scanners from different manufacturers (Siemens, Philips, GE) and different field strengths (1T, 1.5T, 3T) for the automatic segmentation of SCI lesions and the spinal cord. The proposed method was visually and quantitatively compared with other open-source baseline methods. Quantitative biomarkers (lesion volume, lesion length, and maximal axial damage ratio) computed from manual ground-truth lesion masks and automatic SCIseg predictions were correlated with clinical scores (pinprick, light touch, and lower extremity motor scores). A between-group comparison was performed using the Wilcoxon signed-rank test. Results: MRI data from 191 SCI patients (mean age, 48.1 years {+/-} 17.9 [SD]; 142 males) were used for training. Compared to existing methods, SCIseg achieved the best segmentation performance for both the cord and lesions and generalized well to both traumatic and non-traumatic SCI patients. SCIseg is open-source and accessible through the Spinal Cord Toolbox. Conclusion: Automatic segmentation of intramedullary lesions commonly seen in traumatic SCI replaces the tedious manual annotation process and enables the extraction of relevant lesion morphometrics in large cohorts. The proposed model generalizes across lesion etiologies (traumatic, ischemic), scanner manufacturers and heterogeneous image resolutions.

2024-01-03

medRxiv (prépublication)

Influence of scanning plane on Human Spinal Cord functional Magnetic Resonance echo planar imaging

Marta Moraschi

Silvia Tommasin

Laura Maugeri

Mauro Dinuzzo

Marco Masullo

Fabio Mangini

Lorenzo Giovannelli

Daniele Mascali

Tommaso Gili

Valerio Pisani

Ugo Md Nocentini

Federico Giove

Michela Fratini

BACKGROUND: Functional Magnetic Resonance Imaging (fMRI) is based on the Blood Oxygenation Level Dependent contrast and has been exploited f… (voir plus)or the indirect study of the neuronal activity within both the brain and the spinal cord. However, the interpretation of spinal cord fMRI (scfMRI) is still controversial and its diffusion is rather limited because of technical limitations. Overcoming these limitations would have a beneficial effect for the assessment and follow-up of spinal injuries and neurodegenerative diseases. PURPOSE: This study was aimed at systematically verify whether sagittal scanning in scfMRI using EPI readout is a viable alternative to the more common axial scanning, and at optimizing a pipeline for EPI-based scfMRI data analysis, based on Spinal Cord Toolbox (SCT). METHODS: Forty-five healthy subjects underwent MRI acquisition in a Philips Achieva 3T MRI scanner. T2*-weighted fMRI data were acquired using a GE-EPI sequence along sagittal and axial planes during an isometric motor task. Differences on benchmarks were assessed via paired two-sample t-test at p=0.05. RESULTS: We investigated the impact of the acquisition strategy by means of various metrics such as Temporal Signal to Noise Ratio (tSNR), Dice Coefficient to assess geometric distortions, Reproducibility and Sensitivity. tSNR was higher in axial than in sagittal scans, as well as reproducibility within the whole cord mask (t=7.4, p0.01) and within the GM mask (t=4.2, p0.01). The other benchmarks, associated with distortion and functional response, showed no differenc

2024-01-02

ArXiv (prépublication)

Reproducible Spinal Cord Quantitative MRI Analysis with the Spinal Cord Toolbox.

Jan Valošek

2024-01-01

Magnetic Resonance in Medical Sciences (publié)

Towards contrast-agnostic soft segmentation of the spinal cord

Sandrine Bédard

Enamundram Naga Karthik

Charidimos Tsagkas

Emanuele Pravatà

Cristina Granziera

Andrew C. Smith

Kenneth Arnold Weber

Spinal cord segmentation is clinically relevant and is notably used to compute spinal cord cross-sectional area (CSA) for the diagnosis and … (voir plus)monitoring of cord compression or neurodegenerative diseases such as multiple sclerosis. While several semi and automatic methods exist, one key limitation remains: the segmentation depends on the MRI contrast, resulting in different CSA across contrasts. This is partly due to the varying appearance of the boundary between the spinal cord and the cerebrospinal fluid that depends on the sequence and acquisition parameters. This contrast-sensitive CSA adds variability in multi-center studies where protocols can vary, reducing the sensitivity to detect subtle atrophies. Moreover, existing methods enhance the CSA variability by training one model per contrast, while also producing binary masks that do not account for partial volume effects. In this work, we present a deep learning-based method that produces soft segmentations of the spinal cord. Using the Spine Generic Public Database of healthy participants (

2023-10-23

ArXiv (prépublication)

Effectiveness of regional diffusion MRI measures in distinguishing multiple sclerosis abnormalities within the cervical spinal cord

Haykel Snoussi

Olivier Commowick

Benoit Combes

Elise Bannier

Slimane Tounekti

Anne Kerbrat

Christian Barillot

Emmanuel Caruyer

Multiple sclerosis (MS) is an inflammatory disorder of the central nervous system. Although conventional magnetic resonance imaging (MRI) is… (voir plus) widely used for MS diagnosis and clinical follow‐up, quantitative MRI has the potential to provide valuable intrinsic values of tissue properties that can enhance accuracy. In this study, we investigate the efficacy of diffusion MRI in distinguishing MS lesions within the cervical spinal cord, using a combination of metrics extracted from diffusion tensor imaging and Ball‐and‐Stick models.

2023-09-29

Brain and Behavior (publié)

Influence of preprocessing, distortion correction and cardiac triggering on the quality of diffusion MR images of spinal cord

Kurt G Schilling

Anna J. E. Combes

Karthik Ramadass

Francois Rheault

Grace Sweeney

Logan Prock

Subramaniam Sriram

John C Gore

Bennett A Landman

Seth A. Smith

Kristin P. O’Grady

Diffusion MRI of the spinal cord (SC) is susceptible to geometric distortion caused by field inhomogeneities, and prone to misalignment acro… (voir plus)ss time series and signal dropout caused by biological motion. Several modifications of image acquisition and image processing techniques have been introduced to overcome these artifacts, but their specific benefits are largely unproven and warrant further investigations. We aim to evaluate two specific aspects of image acquisition and processing that address image quality in diffusion studies of the spinal cord: susceptibility corrections to reduce geometric distortions, and cardiac triggering to minimize motion artifacts. First, we evaluate 4 distortion preprocessing strategies on 7 datasets of the cervical and lumbar SC and find that while distortion correction techniques increase geometric similarity to structural images, they are largely driven by the high-contrast cerebrospinal fluid, and do not consistently improve the geometry within the cord nor improve white-to-gray matter contrast. We recommend at a minimum to perform bulk-motion correction in preprocessing and posit that improvements/adaptations are needed for spinal cord distortion preprocessing algorithms, which are currently optimized and designed for brain imaging. Second, we design experiments to evaluate the impact of removing cardiac triggering. We show that when triggering is foregone, images are qualitatively similar to triggered sequences, do not have increased prevalence of artifacts, and result in similar diffusion tensor indices with similar reproducibility to triggered acquisitions. When triggering is removed, much shorter acquisitions are possible, which are also qualitatively and quantitatively similar to triggered sequences. We suggest that removing cardiac triggering for cervical SC diffusion can be a reasonable option to save time with minimal sacrifice to image quality.

2023-09-27

bioRxiv (prépublication)

Pontomedullary junction as a reference for spinal cord cross-sectional area: validation across neck positions

Sandrine Bédard

Maxime Bouthillier

2023-08-19

Scientific Reports (publié)