Jan Valosek

Maxime Bouthillier

Naga Karthik Enamundram

Naama Rotem-Kohavi

Suzanne Humphreys

Sean Christie

Michael Fehlings

Brian Kwon

Jean-Marc Mac-Thiong

Philippe Phan

Jérôme Paquet

Mathieu Guay-Paquet

David Cadotte

Jean-Marc Mac-Thiong

Heather Hong

Dilnur Kurban

Jijie Xu

Dorothy Barthélemy

Sean Christie

Daryl Fourney

Gary Linassi

Adalberto Loyola Sanchez

Jérôme Paquet

Vidya Sreenivasan

Andrea Townson

Eve C. Tsai

Andréane Richard-Denis

Pedram Laghaei

Harsh Kahlon

Tamir Ailon

Raphael Charest-Morin

Charlotte Dandurand

Scott Paquette

Nicholas Dea

John Street

Charles G. Fisher

Marcel F. Dvorak

Brian K. Kwon

Antoine Dionne

Mohamed Al-Sofyani

Rémi Pelletier-Roy

Andréane Richard-Denis

Étienne Bourassa-Moreau

Jean-Marc Mac-Thiong

Naga Karthik Enamundram

Mathieu Guay-Paquet

Nick Guenther

Naama Rotem-Kohavi

Suzanne Humphreys

Sean Christie

Michael Fehlings

Brian K. Kwon

Jean Marc Mac-Thiong

Philippe Phan

David Cadotte

Colton Kennedy

Stephanie Stefaniuk

Parvin Eftekhar

Larry Robinson

Cathy Craven

Jana Dengler

Luke Reda

Stephanie Stefaniuk

Parvin Eftekhar

Larry Robinson

Cathy Craven

Jana Dengler

Maitreya Patel

Eve Tsai

Ahmad Galuta

Sasi Jagadeesan

Ryan Vimukthie Sandarage

Wojtek Michalowski

William Van Woensel

Jillian Kazley

Abdul Arain

Gabriella Rivas

Robert Ravinsky

James Lawrence

Jibrahn Patel

Isaac Turkstra

Kirill Pustovetov

Victor Yang

Gonzalo Mariscal

Christopher D. Witiw

James S. Harrop

Ahmed Essa

Gonzalo Mariscal

W. Bradley Jacobs

James S. Harrop

Ahmed Essa

Ahmed Cherry

Rajesh Kumar

Nadia Jaber

Michael Fehlings

Albert Yee

Mark Driscoll

Justin L. Brown

Michelle Gallagher

James Sugar

James Hektner

Scott Donia

John Chernesky

Vanessa K. Noonan

Flo Slomp

Emily Thiessen

Nataliya Lastivnyak

Linda Slater Maclean

Vanessa Ritchie

Aaron Hockley

Christine Potvin

Peggy Flynn

Sean Christie

Bruno Oppermann

Marcelo Oppermann

Shaurya Gupta

Jibrahn Patel

Kirill Pustovetov

Kenneth Lee

ChaoLiang Chen

Mohammadmahdi Rastgarjazi

Victor Yang

Samuel Strantzas

Alison Anthony

Jennifer Dermott

Mike Vandenberk

Samer Hassan

David Lebel

Bernard LaRue

Jerome Couture

Newton Pimenta

Jocelyn Blanchard

Alexandre Chenevert

Julien Goulet

Sean D. Christie

Amanda Hall

Holly Etchegary

Jae Han

Ryan Greene

Sean Christie

Gwynedd Pickett

James Harrop

W. Bradley Jacobs

Gonzalo Mariscal

Ahmed Essa

Gonzalo Mariscal

Christopher Witiw

James S. Harrop

Ahmed Essa

Parham Rasoulinejad

Richard Hu

Chris Bailey

Fawaz Siddiqi

Mohamed Amin Soliman

Juhi Maraj

Deven Jhawar

Balraj Jhawar

Lindsay D. Orosz

Tarek Yamout

Brandon J. Allen

Wondwossen T. Lerebo

Rita T. Roy

Thomas C. Schuler

Christopher R. Good

Colin M. Haines

Ehsan Jazini

Abdul Al-Shawwa

David Anderson

Nathan Evaniew

Bradley W. Jacobs

Peter Lewkonia

Fred Nicholls

Paul T. Salo

Kenneth C. Thomas

Michael Yang

David Cadotte

Nathasha Rajapaksege

Nicolas Dea

Nathan Evaniew

Greg McIntosh

Markian Pahuta

Khaled Skaik

Eugene K. Wai

Stephen Kingwell

Alexandra Stratton

Eve Tsai

Philippe Tran Nhut Phan

Zhi Wang

CSORN Investigators

Ian Polyzois

Trevor Gascoyne

Michael Goytan

Mohamed Sarra

Juan P. Sardi

Anastasios Charalampidis

Jeff Gum

Stephen J. Lewis

Samuel Kirk

Otis Shirley

Jeffrey Bone

Andrew Morrison

Firoz Miyanji

Ethan Sanders

Manjot Birk

Fred Nicholls

Holly Livock

Jessica Romeo

James Jarvis

Andrew Tice

Hubert Labelle

Stephan Parent

Soraya Barchi

Julie Joncas

Jean-Marc Mac-Thiong

Julie Joncas

Soraya Barchi

Stefan Parent

Marie Beausejour

Jean-Marc Mac-Thiong

Stefan Parent

Jesse Shen

Julie Joncas

Soraya Barchi

Hubert Labelle

Fred Nicholls

Rémi Pelletier-Roy

Ethan Sanders

Yousef Aljamaan

Lawrence G. Lenke

Justin Smith

Zeeshan Sardar

David Lebel

Jennifer Dermott

Natasha Bath

Karen Mathias

Deepa Kattail

Janneke Loomans

Ferran Pellise

Justin S. Smith

So Kato

Zeeshan Sardar

Lawrence Lenke

Stephen J. Lewis

Manmeet Dhiman

David Hart

Neil Duncan

Paul Salo

Ganesh Swamy

Peyton Lloyd Lawrence

Justin Smith

Ferran Pellise

Zeeshan Sardar

Stephen Joel Lewis

Justin Smith

Ferran Pellise

Zeeshan Sardar

Abdulrhman Alnasser

Uri Barak

Lior M. Elkaim

Thien Sa Hoang

Naif M. Alotaibi

Daipayan Guha

Isaac L. Moss

Alexander G. Weil

Michael H. Weber

Kashif Parvez

John Sun

Brent Rosenstein

Neda Naghdi

Maryse Fortin

Ran Ankory

Lisa Stallwood

Henry Ahn

Abdul Naeem

Deven Jhawar

Milad Moradi

Balraj Jhawar

Vithushan Surendran

Victoria Shi

Emily Cheung

Sophie Ngana

Muhammad A. Qureshi

Sunjay V. Sharma

Markian Pahuta

Daipayan Guha

2024-11-12

Canadian Journal of Surgery (published)

SCIseg: Automatic Segmentation of Intramedullary Lesions in Spinal Cord Injury on T2-weighted MRI Scans

Enamundram Naga Karthik

Andrew C. Smith

Dario Pfyffer

Simon Schading-Sassenhausen

Lynn Farner

Kenneth A. Weber

Patrick Freund

The proposed deep learning model accurately segmented the spinal cord and spinal cord injury lesions in a diverse, multicenter dataset of T2… (see more)-weighted MRI scans.

2024-11-05

Radiology: Artificial Intelligence (unknown)

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

René Labounek

Monica T. Bondy

Amy Paulson

Mihael Abramovic

Eva Alonso‐Ortiz

Nicole Atcheson

Laura Barlow

Robert 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 73 more)

Adam Dvorak

Falk Eippert

Karla R. Epperson

Kevin 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

Sławomir Kuśmia

Maria Marcella Laganà

Cornelia Laule

Christine Law

Tobias Leutritz

Yaou Liu

Sara Llufriú

Sean Mackey

Allan R. Martin

Eloy Martínez‐Heras

Loan Mattera

Kristin P. O’Grady

Nico Papinutto

Daniel S. Papp

Deborah Pareto

Todd B. Parrish

Anna Pichiecchio

Ferrán 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

Dimitri Van De Ville

Marios Yiannakas

Kenneth A. Weber

Nikolaus Weiskopf

Richard G. Wise

Patrik O. Wyss

Junqian Xu

Julien Cohen‐Adad

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.

2024-04-30

bioRxiv (preprint)

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

Enamundram Naga Karthik

A. 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

2024-04-26

MIDL.io/2024/Short_Papers (accepted)

openreview.net

Normalizing Spinal Cord Compression Morphometric Measures: Application in Degenerative Cervical Myelopathy

Maryam Seif

Armin Curt

Simon Schadings

M.Sc

Nikolai Pfender

Patrick Freund

Markus Hupp

The study introduced an automatic method for computation of normalized MSCC measures of cord compression from MRI scans, which is an importa… (see more)nt step towards better informed therapeutic decisions in DCM patients. The method is open-source and available in the Spinal Cord Toolbox v6.0.

2024-03-14

medRxiv (preprint)

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

Miloš Keřkovský

Tomáš Rohan

Measures of spinal cord morphometry computed from magnetic resonance images serve as relevant prognostic biomarkers for a range of spinal co… (see more)rd 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.

2024-01-09

Imaging Neuroscience (published)

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

Naga Karthik Enamundram

Andrew C. Smith

Dario Pfyffer

Simon Schading-Sassenhausen

Lynn Farner

Kenneth A. Weber II

Patrick Freund

Background: Quantitative MRI biomarkers in spinal cord injury (SCI) can help understand the extent of the focal injury. However, due to the … (see more)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.

2024-01-02

MedRxiv (preprint)

Reproducible Spinal Cord Quantitative MRI Analysis with the Spinal Cord Toolbox

The spinal cord plays a pivotal role in the central nervous system, providing communication between the brain and the body and containing cr… (see more)itical motor and sensory networks. Recent advancements in spinal cord MRI data acquisition and image analysis have shown a potential to improve the diagnostics, prognosis, and management of a variety of pathological conditions. In this review, we first discuss the significance of standardized spinal cord MRI acquisition protocol in multi-center and multi-manufacturer studies. Then, we cover open-access spinal cord MRI datasets, which are important for reproducible science and validation of new methods. Finally, we elaborate on the recent advances in spinal cord MRI data analysis techniques implemented in the open-source software package Spinal Cord Toolbox (SCT).

2023-12-31

Magnetic Resonance in Medical Sciences (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

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

Ferrán 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)

Author Correction: Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

Eva Alonso‐Ortiz

Mihael Abramovic

Carina Arneitz

Nicole Atcheson

Laura Barlow

Robert L. Barry

Markus Barth

Marco Battiston

Christian Büchel

Matthew D. Budde

Virginie Callot

Anna J. E. Combes

Benjamin De Leener

Maxime Descoteaux

Paulo Loureiro de Sousa

Marek Dostál

Julien Doyon

Adam Dvorak

Falk Eippert … (see 71 more)

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

Charley Gros

Francesco Grussu

Akifumi Hagiwara

Pierre-Gilles Henry

Tomáš Horák

Masaaki Hori

James 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

René Labounek

Maria Marcella Laganà

Cornelia Laule

Christine S. Law

Christophe Lenglet

Tobias Leutritz

Yaou Liu

Sara Llufriú

Sean Mackey

Eloy Martinez-Heras

Loan Mattera

Igor Nestrašil

Kristin P. O’Grady

Nico Papinutto

Daniel Papp

Deborah Pareto

Todd B. Parrish

Anna Pichiecchio

Ferrán 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

Y. Suzuki

George Tackley

Alexandra Tinnermann

Dimitri Van De Ville

Marios C. Yiannakas

Kenneth A. Weber

Nikolaus Weiskopf

Richard G. Wise

Patrik O. Wyss

Junqian Xu

2021-09-22

Scientific Data (published)

Generic acquisition protocol for quantitative MRI of the spinal cord

Julien Cohen‐Adad

Eva Alonso‐Ortiz

Mihael Abramovic

Carina Arneitz

Nicole Atcheson

Laura Barlow

Robert 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

Adam Dvorak

Falk Eippert … (see 71 more)

Karla R. Epperson

Kevin Epperson

Patrick Freund

Jürgen Finsterbusch

Alexandru Foias

Michela Fratini

Issei Fukunaga

Claudia A. M. Gandini Wheeler‐Kingshott

Giancarlo Germani

Guillaume Gilbert

Federico Giove

Charley Gros

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

Sławomir Kuśmia

René Labounek

Maria Marcella Laganà

Cornelia Laule

Christine Law

Christophe Lenglet

Tobias Leutritz

Yaou Liu

Sara Llufriú

Sean Mackey

Eloy Martínez‐Heras

Loan Mattera

Igor Nestrašil

Kristin P. O’Grady

Nico Papinutto

Daniel S. Papp

Deborah Pareto

Todd B. Parrish

Anna Pichiecchio

Ferrán 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

Dimitri Van De Ville

Marios Yiannakas

Kenneth A. Weber

Nikolaus Weiskopf

Richard G. Wise

Patrik O. Wyss

Junqian Xu

Optimized and standardized MRI acquisition protocols for the spinal cord, compatible with Siemens, GE and Philips scanners.

2021-08-15

Nature Protocols (published)

Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

Eva Alonso-Ortiz

Mihael Abramovic

Carina Arneitz

Nicole Atcheson

Laura Barlow

Robert L. Barry

Markus Barth

Marco Battiston

Christian Büchel

Matthew Budde

Virginie Callot

Anna J. E. Combes

Benjamin De Leener

Maxime Descoteaux

Paulo Loureiro de Sousa

Marek Dostál

Julien Doyon

Adam Dvorak

Falk Eippert … (see 71 more)

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

Charley Gros

Francesco Grussu

Akifumi Hagiwara

Pierre-Gilles Henry

Tomáš Horák

Masaaki Hori

James 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

René Labounek

Maria Marcella Laganà

Cornelia Laule

Christine S. Law

Christophe Lenglet

Tobias Leutritz

Yaou Liu

Sara Llufriú

Sean Mackey

Eloy Martinez-Heras

Loan Mattera

Igor Nestrašil

Kristin P. O'Grady

Nico Papinutto

Daniel Papp

Deborah Pareto

Todd B. Parrish

Anna Pichiecchio

Ferrán 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

Y. Suzuki

George Tackley

Alexandra Tinnermann

Dimitri Van De Ville

Marios C. Yiannakas

Kenneth A. Weber II

Nikolaus Weiskopf

Richard G. Wise

Patrik O. Wyss

Junqian Xu

In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assess… (see more)ing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject dataset across 19 centers and a multi-subject dataset across 42 centers (for a total of 260 participants), spanning the three main MRI manufacturers: GE, Philips and Siemens. Both datasets are publicly available via git-annex. Data were analysed using the Spinal Cord Toolbox to produce normative values as well as inter/intra-site and inter/intra-manufacturer statistics. Reproducibility for the spine generic protocol was high across sites and manufacturers, with an average inter-site coefficient of variation of less than 5% for all the metrics. Full documentation and results can be found at https://spine-generic.rtfd.io/. The datasets and analysis pipeline will help pave the way towards accessible and reproducible quantitative MRI in the spinal cord.

2021-08-15

Scientific Data (published)