Julien Cohen-Adad

Pierre Louis Benveniste

PhD - Polytechnique Montréal

Co-supervisor :

PhD - Polytechnique Montréal

Thomas Dagonneau

Master's Research - Polytechnique Montréal

Naga Karthik Enamundram

PhD - Polytechnique Montréal

Co-supervisor :

Master's Research - Polytechnique Montréal

Youssef Laatar

Master's Research - Polytechnique Montréal

Julien Laborde-Peyré

Research Intern - Polytechnique Montréal

Nilser Laines Medina

PhD - Polytechnique Montréal

Nathan Molinier

PhD - Polytechnique Montréal

Kalum Ost

Collaborating researcher

Arthur Toulouse

Master's Research - Polytechnique Montréal

Publications

Intervertebral Disc Labeling With Learning Shape Information, A Look Once Approach

Reza Azad

Moein Heidari

Ehsan Adeli

Dorit Merhof

Accurate and automatic segmentation of intervertebral discs from medical images is a critical task for the assessment of spine-related disea… (see more)ses such as osteoporosis, vertebral fractures, and intervertebral disc herniation. To date, various approaches have been developed in the literature which routinely relies on detecting the discs as the primary step. A disadvantage of many cohort studies is that the localization algorithm also yields false-positive detections. In this study, we aim to alleviate this problem by proposing a novel U-Net-based structure to predict a set of candidates for intervertebral disc locations. In our design, we integrate the image shape information (image gradients) to encourage the model to learn rich and generic geometrical information. This additional signal guides the model to selectively emphasize the contextual representation and suppress the less discriminative features. On the post-processing side, to further decrease the false positive rate, we propose a permutation invariant 'look once' model, which accelerates the candidate recovery procedure. In comparison with previous studies, our proposed approach does not need to perform the selection in an iterative fashion. The proposed method was evaluated on the spine generic public multi-center dataset and demonstrated superior performance compared to previous work. We have provided the implementation code in https://github.com/rezazad68/intervertebral-lookonce

2022-09-15

Predictive Intelligence in Medicine (published)

arxiv.org

Advanced MRI scan acquisition metrics improve baseline disease severity predictions compared to traditional community MRI scan metrics

Abdul Al-Shawwa

Kalum Ost

David W. Cadotte

David Anderson

Nathan Evaniew

Bradley Jacobs

Julien Cohen‐Adad

Degenerative Cervical Myelopathy (DCM) is the functional derangement of the spinal cord and acts as one of the most common atraumatic spinal… (see more) cord injuries. Magnetic resonance imaging (MRI) are key in confirming the diagnosis of DCM in patients, though the utilization of higher fidelity magnetic resonance imaging scans and their integration into machine learning models remains largely unexplored. This study looks at the predictive ability of common community MRI scans in comparison to high fidelity scans in disease diagnosis. We hypothesize that the utilization of higher fidelity "advanced" MRI scans will increase the effectiveness of machine learning models predicting DCM severity. Through the utilization of Random Forest Classifiers, we have been able to predict disease severity with 41.8% accuracy in current community MRI scans and 63.9% in the advanced MRI scans. Furthermore, across the different predictive model variations tested, the advanced MRI scans consistently produced higher prediction accuracies compared to the community MRI counterparts. These results support our hypothesis and indicate that machine learning models have the potential to predict disease severity. However, neither performed well enough to be considered for use in clinical practice, indicating that the utilization of more sophisticated machine models may be required for these purposes.

2022-07-06

medRxiv (preprint)

Relationship Between Arterial Stiffness Index, Pulse Pressure, and Magnetic Resonance Imaging Markers of White Matter Integrity: A UK Biobank Study

Atef Badji

Hélène Girouard

Alzheimer’s disease and dementia in general constitute one of the major public health problems of the 21st century. Research in arterial s… (see more)tiffness and pulse pressure (PP) play an important role in the quest to reduce the risk of developing dementia through controlling modifiable risk factors. The aim of the study is to investigate the association between peripheral PP, arterial stiffness index (ASI) and brain integrity, and to discover if ASI is a better predictor of white matter integrity than peripheral PP. 17,984 participants 63.09 ± 7.31 from the UK Biobank were used for this study. ASI was estimated using infrared light (photoplethysmography) and peripheral PP was calculated by subtracting the diastolic from the systolic brachial blood pressure value. Measure of fractional anisotropy (FA) was obtained from diffusion imaging to estimate white matter microstructural integrity. White matter hyperintensities were segmented from the combined T1 and T2-weighted FLAIR images as a measure of irreversible white matter damage. An important finding is that peripheral PP better predicts white matter integrity when compared to ASI. This finding is consistent until 75 years old. Interestingly, no significant relationship is found between either peripheral PP or ASI and white matter integrity after 75 years old. These results suggest that ASI from plethysmography should not be used to estimate cerebrovascular integrity in older adults and further question the relationship between arterial stiffness, blood pressure, and white matter damage after the age of 75 years old.

2022-06-20

Frontiers in Aging Neuroscience (published)

Vendor-neutral sequences and fully transparent workflows improve inter-vendor reproducibility of quantitative MRI

Agah Karakuzu

Labonny Biswas

Nikola Stikov

We conclude that vendor-neutral workflows are feasible and compatible with clinical MRI scanners. The significant reduction of inter-vendor … (see more)variability using vendor-neutral sequences has important implications for qMRI research and for the reliability of multicenter clinical trials.

2022-06-02

Magnetic Resonance in Medicine (unknown)

Diffusion Kurtosis Imaging of neonatal Spinal Cord in clinical routine

Rosella Trò

Monica Roascio

Domenico Tortora

Mariasavina Severino

Andrea Rossi

Julien Cohen‐Adad

Marco Fato

Gabriele Arnulfo

Diffusion Kurtosis Imaging (DKI) has undisputed advantages over more classical diffusion Magnetic Resonance Imaging (dMRI), as witnessed by … (see more)a fast-increasing number of clinical applications and software packages widely adopted in brain imaging domain. Despite its power in probing tissue microstructure compared to conventional MRI, DKI is still largely underutilized in Spinal Cord (SC) imaging because of its inherently demanding technological requirements. If state-of-the-art hardware advancements have recently allowed to make great strides in applying this emerging method to adult and child SC, the same does not apply to neonatal setting. Indeed, amplified technical issues related to SC district in this age range have made this field still unexplored. However, results arising from recent application of DKI to adult and child SC are promising enough to suggest how informative this technique would be in investigating newborns, too. Due to its extreme sensitivity to non-gaussian diffusion, DKI proves particularly suitable for detecting complex, subtle, fast microstructural changes occurring in this area at this early and critical stage of development, and not identifiable with only DTI. Given the multiplicity of congenital anomalies of the spinal canal, their crucial effect on later developmental outcome, and the close interconnection between SC region and the above brain, managing to apply such a method to neonatal cohort becomes of utmost importance. In this work, we illustrate the first semi-automated pipeline for handling with DKI data of neonatal SC, from acquisition setting to estimation of diffusion (DTI & DKI) measures, through accurate adjustment of processing algorithms customized for adult SC. Each processing step of this pipeline, built on Spinal Cord Toolbox (SCT) software, has undergone Quality Control check by supervision of an expert pediatric neuroradiologist, and the overall procedure has preliminarily been tested in a pilot clinical case study. Results of this application agree with findings achieved in a corresponding adult survey, thus confirming validity of adopted pipeline and diagnostic value of DKI in pediatrics. This novel tool hence paves the wave for extending its application also to other promising advanced dMRI models, such as Neurite Orientation Dispersion and Density Imaging (NODDI), and to a wider range of potential clinical applications concerning neonatal period.

2022-05-22

Frontiers in Radiology (published)

Microscopy-BIDS: An Extension to the Brain Imaging Data Structure for Microscopy Data

Marie-Hélène Bourget

Lee Kamentsky

Satrajit S. Ghosh

Giacomo Mazzamuto

Alberto Lazari

Christopher J. Markiewicz

Robert Oostenveld

Guiomar Niso

Yaroslav O. Halchenko

Ilona Lipp

Sylvain Takerkart

Paule-Joanne Toussaint

Ali R. Khan

Gustav Nilsonne

Filippo Maria Castelli

Stefan Ross Eric Franklin Anthony Rémi Christopher J. Taylor Appelhoff

The Brain Imaging Data Structure (BIDS) is a specification for organizing, sharing, and archiving neuroimaging data and metadata in a reusab… (see more)le way. First developed for magnetic resonance imaging (MRI) datasets, the community-led specification evolved rapidly to include other modalities such as magnetoencephalography, positron emission tomography, and quantitative MRI (qMRI). In this work, we present an extension to BIDS for microscopy imaging data, along with example datasets. Microscopy-BIDS supports common imaging methods, including 2D/3D, ex/in vivo, micro-CT, and optical and electron microscopy. Microscopy-BIDS also includes comprehensible metadata definitions for hardware, image acquisition, and sample properties. This extension will facilitate future harmonization efforts in the context of multi-modal, multi-scale imaging such as the characterization of tissue microstructure with qMRI.

2022-04-18

Frontiers in Neuroscience (published)

Rapid, automated nerve histomorphometry through open-source artificial intelligence

Simeon Christian Daeschler

Marie-Hélène Bourget

Dorsa Derakhshan

Vasudev Sharma

Stoyan Ivaylov Asenov

Tessa Gordon

Gregory Howard Borschel

We aimed to develop and validate a deep learning model for automated segmentation and histomorphometry of myelinated peripheral nerve fibers… (see more) from light microscopic images. A convolutional neural network integrated in the AxonDeepSeg framework was trained for automated axon/myelin segmentation using a dataset of light-microscopic cross-sectional images of osmium tetroxide-stained rat nerves including various axonal regeneration stages. In a second dataset, accuracy of automated segmentation was determined against manual axon/myelin labels. Automated morphometry results, including axon diameter, myelin sheath thickness and g-ratio were compared against manual straight-line measurements and morphometrics extracted from manual labels with AxonDeepSeg as a reference standard. The neural network achieved high pixel-wise accuracy for nerve fiber segmentations with a mean (± standard deviation) ground truth overlap of 0.93 (± 0.03) for axons and 0.99 (± 0.01) for myelin sheaths, respectively. Nerve fibers were identified with a sensitivity of 0.99 and a precision of 0.97. For each nerve fiber, the myelin thickness, axon diameter, g-ratio, solidity, eccentricity, orientation, and individual x -and y-coordinates were determined automatically. Compared to manual morphometry, automated histomorphometry showed superior agreement with the reference standard while reducing the analysis time to below 2.5% of the time needed for manual morphometry. This open-source convolutional neural network provides rapid and accurate morphometry of entire peripheral nerve cross-sections. Given its easy applicability, it could contribute to significant time savings in biomedical research while extracting unprecedented amounts of objective morphologic information from large image datasets.

2022-04-07

Scientific Reports (published)

Comparison of multi-center MRI protocols for visualizing the spinal cord gray matter

Eva Alonso-Ortiz

Stephanie Alley

Maria Marcella Laganà

Francesca Baglio

Signe Johanna Vannesjo

Haleh Karbasforoushan

Maryam Seif

Alan C. Seifert

Junqian Xu

Joo-Won Kim

René Labounek

Lubomír Vojtíšek

Marek Dostál

Jan Valosek

Rebecca S. Samson

Francesco Grussu

Marco Battiston

Claudia A. M. Gandini Wheeler-Kingshott

Marios C. Yiannakas … (see 4 more)

Guillaume Gilbert

Torben Schneider

Brian Johnson

Ferran Prados

We propose quality assessment criteria and metrics for gray‐matter visualization and apply them to different protocols. The proposed crite… (see more)ria and metrics, the analyzed protocols, and our open‐source code can serve as a benchmark for future optimization of spinal cord gray‐matter imaging protocols.

2022-04-04

Magnetic Resonance in Medicine (unknown)

Reproducibility and Evolution of Diffusion Mri Measurements Within the Cervical Spinal Cord in Multiple Sclerosis

Haykel Snoussi

Emmanuel Caruyer

Benoit Combes

Olivier Commowick

Elise Bannier

Anne Kerbrat

Christian Barillot

In Multiple Sclerosis (MS), there is a large discrepancy between the clinical observations and how the pathology is exhibited on brain image… (see more)s, this is known as the clinical-radiological paradox. One of the hypotheses is that the clinical deficit may be more related to the spinal cord damage than the number or location of lesions in the brain. Therefore, investigating how the spinal cord is damaged becomes an acute challenge to better understand and overcome this paradox. Diffusion MRI is known to provide quantitative figures of neuronal degeneration and axonal loss, in the brain as well as in the spinal cord. In this paper, we propose to investigate how diffusion MRI metrics vary in the different cervical regions with the progression of the disease. We first study the reproducibility of diffusion MRI on healthy volunteers with a test-retest procedure using both standard diffusion tensor imaging (DTI) and multi-compartment Ball-and-Stick models. Then, based on the test re-test quantitative calibration, we provide quantitative figures of pathology evolution between M0 and M12 in the cervical spine on a set of 31 MS patients, exhibiting how the pathology damage spans in the cervical spinal cord.

2022-03-27

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) (published)

arxiv.org

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

Reza Azad

Nika Khosravi

Mohammad Dehghanmanshadi

Dorit Merhof

2022-03-10

ArXiv (preprint)

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 Barthélemy

Observational, cohort study. (1) Determine the feasibility and relevance of assessing corticospinal, sensory, and spinal pathways early aft… (see more)er traumatic spinal cord injury (SCI) in a rehabilitation setting. (2) Validate whether electrophysiological and magnetic resonance imaging (MRI) measures taken early after SCI could identify preserved neural pathways, which could then guide therapy. Intensive functional rehabilitation hospital (IFR). Five individuals with traumatic SCI and eight controls were recruited. The lower extremity motor score (LEMS), electrical perceptual threshold (EPT) at the S2 dermatome, soleus (SOL) H-reflex, and motor evoked potentials (MEPs) in the tibialis anterior (TA) muscle were assessed during the stay in IFR and in the chronic stage (>6 months post-SCI). Control participants were only assessed once. Feasibility criteria included the absence of adverse events, adequate experimental session duration, and complete dataset gathering. The relationship between electrophysiological data collected in IFR and LEMS in the chronic phase was studied. The admission MRI was used to calculate the maximal spinal cord compression (MSCC). No adverse events occurred, but a complete dataset could not be collected for all subjects due to set-up configuration limitations and time constraints. EPT measured at IFR correlated with LEMS in the chronic phases (r = −0.67), whereas SOL H/M ratio, H latency, MEPs and MSCC did not. Adjustments are necessary to implement electrophysiological assessments in an IFR setting. Combining MRI and electrophysiological measures may lead to better assessment of neuronal deficits early after SCI.

2022-02-23

Spinal Cord Series and Cases (published)

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… (see more) 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.

2022-02-14

Magnetic Resonance in Medical Sciences (published)