Julien Cohen-Adad

Pierre Louis Benveniste

Doctorat - Polytechnique

Co-superviseur⋅e :

Doctorat - Polytechnique

Thomas Dagonneau

Maîtrise recherche - Polytechnique

Naga Karthik Enamundram

Doctorat - Polytechnique

Co-superviseur⋅e :

Sarath Chandar

emvnagakarthik@gmail.com

Maîtrise recherche - Polytechnique

Nilser Laines Medina

Doctorat - Polytechnique

Nathan Molinier

Doctorat - Polytechnique

Kalum Ost

Collaborateur·rice de recherche

Julien Thouveny

Maîtrise recherche - UdeM

Arthur Toulouse

Maîtrise recherche - Polytechnique

Jan Valosek

Postdoctorat - Polytechnique

Site web

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Publications

Brain-spinal cord interaction in long-term motor sequence learning in human: An fMRI study

Ali Khatibi

Shahabeddin Vahdat

Ovidiu Lungu

Jürgen Finsterbusch

Christian Büchel

V. Marchand-Pauvert

Julien Doyon

2022-03-21

NeuroImage (publié)

Medical Image Segmentation on MRI Images with Missing Modalities: A Review

Reza Azad

Nika Khosravi

Mohammad Dehghanmanshadi

Dorit Merhof

2022-03-11

ArXiv (prépublication)

arxiv.org

Quantitative electrophysiological assessments as predictive markers of lower limb motor recovery after spinal cord injury: a pilot study with an adaptive trial design

Yin Nan Huang

El-Mehdi Meftah

Charlotte H. Pion

Jean-Marc Mac-Thiong

Dorothy Barthélémy

2022-02-24

Spinal Cord Series and Cases (publié)

Advanced Diffusion MR Imaging for Multiple Sclerosis in the Brain and Spinal Cord

Masaaki Hori

Tomoko Maekawa

Kouhei Kamiya

Akifumi Hagiwara

Masami Goto

Mariko Yoshida Takemura

Shohei Fujita

Christina Andica

Koji Kamagata

Shigeki Aoki

Diffusion tensor imaging (DTI) has been established its usefulness in evaluating normal-appearing white matter (NAWM) and other lesions that… (voir plus) are difficult to evaluate with routine clinical MRI in the evaluation of the brain and spinal cord lesions in multiple sclerosis (MS), a demyelinating disease. With the recent advances in the software and hardware of MRI systems, increasingly complex and sophisticated MRI and analysis methods, such as q-space imaging, diffusional kurtosis imaging, neurite orientation dispersion and density imaging, white matter tract integrity, and multiple diffusion encoding, referred to as advanced diffusion MRI, have been proposed. These are capable of capturing in vivo microstructural changes in the brain and spinal cord in normal and pathological states in greater detail than DTI. This paper reviews the current status of recent advanced diffusion MRI for assessing MS in vivo as part of an issue celebrating two decades of magnetic resonance in medical sciences (MRMS), an official journal of the Japanese Society of Magnetic Resonance in Medicine.

2022-02-15

Magnetic Resonance in Medical Sciences (publié)

Advanced Diffusion MR Imaging for Multiple Sclerosis in the Brain and Spinal Cord

Masaaki Hori

Tomoko Maekawa

Kouhei Kamiya

Akifumi Hagiwara

Masami Goto

Mariko Y. Takemura

Shohei Fujita

Christina Andica

Koji Kamagata

Shigeki Aoki

2022-02-15

Magnetic Resonance in Medical Sciences (published)

Erratum to: Rapid simultaneous acquisition of macromolecular tissue volume, susceptibility, and relaxometry maps (Magn Reson Med. 2022;87:781‐790.)

Fang Frank Yu

Susie Yi Huang

Ashwin Kumar

Thomas Witzel

Congyu Liao

Tanguy Duval

Berkin Bilgic

2022-02-10

Magnetic Resonance in Medicine (publié)

Erratum to: Rapid simultaneous acquisition of macromolecular tissue volume, susceptibility, and relaxometry maps (Magn Reson Med. 2022;87:781‐790.)

Fang Frank Yu

Susie Y. Huang

Ashwin S. Kumar

T. Witzel

Congyu Liao

Tanguy Duval

Berkin Bilgic

2022-02-10

Magnetic Resonance in Medicine (published)

Titre: Title: Comparison of Myelin Imaging Techniques in Ex Vivo Spinal Cord Auteur:

Nikola Stikov

Manh-Tung Vuong

Vuong Manh Tung

Myelin is a dielectric material that wraps around the axons of nerve fibers to enable fast conduction of signals throughout the nervous syst… (voir plus)em. Loss of myelin can cause anywhere from minor interruption to complete disruption of nerve impulses in a range of neurodegenerative diseases such as multiple sclerosis and Parkinson’s disease. There is an ongoing debate in the myelin imaging community about which biomarker based on Magnetic Resonance Imaging (MRI) is more correlated with myelin. In this work, we implemented and compared several MRI-based myelin imaging techniques (quantitative magnetization transfer imaging, myelin water imaging, and proton density imaging) by evaluating their repeatability and their relation to large-scale histology in the ex vivo spinal cords of a rat, a dog, and a human. While there are studies investigating the relationship between pairs of them as well as with histology, to the best of our knowledge, this is the first study that implemented and compared all those methods at the same time to evaluate their reproducibility and their correlation with myelin. Qualitatively the contrasts were similar, and all techniques had comparable scan-rescan and correlations with histology. Surprisingly, the voxel-wise correlations between the various myelin measures were almost as high as the scan-rescan correlations. The correlations decreased when only white matter was considered, which could be due to the small dynamic range of the measurement, or due to artifacts related to the preparation and panoramic scanning of the tissue. We conclude that the myelin imaging techniques explored in this thesis exhibit similar specificity to myelin, yet the histological correlations suggest that more work is needed to determine the optimal myelin imaging protocol. The study also pointed out some potential miscalibrations during acquisitions as well as data processing that may lead to anywhere from minor to major impact on the accuracy of the results. These include B1 mapping, insufficient spoiling and variation of the predelay time. We have also standardized the data processing routines by upgrading qMTLab to qMRLab which adds several quantitative MR methods to the toolbox, such as standard T1 mapping and field mapping. In addition, the data of the dog spinal cord in this study will be published together with the analysis scripts to help the interested reader to reproduce the findings from this thesis.

The Myelin‐Weighted Connectome in Parkinson's Disease

Tommy Boshkovski

Bratislav Mišić

Isabelle Arnulf

Jean‐Christophe Corvol

Marie Vidailhet

Stéphane Lehéricy

Nikola Stikov

Matteo Mancini

2021-12-22

Movement Disorders (publié)

2D Multi-Class Model for Gray and White Matter Segmentation of the Cervical Spinal Cord at 7T

Nilser Laines Medina

Charley Gros

Virginie Callot

A. Troter

2021-10-13

ArXiv (prépublication)

arxiv.org

Minimum detectable spinal cord atrophy with automatic segmentation: Investigations using an open-access dataset of healthy participants

Paul Bautin

2021-10-04

NeuroImage : Clinical (publié)

Normalizing automatic spinal cord cross-sectional area measures

S. Bédard

Spinal cord cross-sectional area (CSA) is a relevant biomarker to assess spinal cord atrophy in various neurodegenerative diseases. However,… (voir plus) the considerable inter-subject variability among healthy participants currently limits its usage. Previous studies explored factors contributing to the variability, yet the normalization models were based on a relatively limited number of participants (typically 300 participants), required manual intervention, and were not implemented in an open-access comprehensive analysis pipeline. Another limitation is related to the imprecise prediction of the spinal levels when using vertebral levels as a reference; a question never addressed before in the search for a normalization method. In this study we implemented a method to measure CSA automatically from a spatial reference based on the central nervous system (the pontomedullary junction, PMJ), we investigated various factors to explain variability, and we developed normalization strategies on a large cohort (N=804). Cervical spinal cord CSA was computed on T1w MRI scans for 804 participants from the UK Biobank database. In addition to computing cross-sectional at the C2-C3 vertebral disc, it was also measured at 64 mm caudal from the PMJ. The effect of various biological, demographic and anatomical factors was explored by computing Pearson’s correlation coefficients. A stepwise linear regression found significant predictors; the coefficients of the best fit model were used to normalize CSA. The correlation between CSA measured at C2-C3 and using the PMJ was y = 0.98x + 1.78 (R2 = 0.97). The best normalization model included thalamus volume, brain volume, sex and interaction between brain volume and sex. With this model, the coefficient of variation went down from 10.09% (without normalization) to 8.59%, a reduction of 14.85%. In this study we identified factors explaining inter-subject variability of spinal cord CSA over a large cohort of participants, and developed a normalization model to reduce the variability. We implemented an approach, based on the PMJ, to measure CSA to overcome limitations associated with the vertebral reference. This approach warrants further validation, especially in longitudinal cohorts. The PMJ-based method and normalization models are readily available in the Spinal Cord Toolbox.

2021-10-01

bioRxiv (prépublication)