Literature DB >> 27720818

SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data.

Benjamin De Leener1, Simon Lévy2, Sara M Dupont1, Vladimir S Fonov3, Nikola Stikov4, D Louis Collins3, Virginie Callot5, Julien Cohen-Adad6.   

Abstract

For the past 25 years, the field of neuroimaging has witnessed the development of several software packages for processing multi-parametric magnetic resonance imaging (mpMRI) to study the brain. These software packages are now routinely used by researchers and clinicians, and have contributed to important breakthroughs for the understanding of brain anatomy and function. However, no software package exists to process mpMRI data of the spinal cord. Despite the numerous clinical needs for such advanced mpMRI protocols (multiple sclerosis, spinal cord injury, cervical spondylotic myelopathy, etc.), researchers have been developing specific tools that, while necessary, do not provide an integrative framework that is compatible with most usages and that is capable of reaching the community at large. This hinders cross-validation and the possibility to perform multi-center studies. In this study we introduce the Spinal Cord Toolbox (SCT), a comprehensive software dedicated to the processing of spinal cord MRI data. SCT builds on previously-validated methods and includes state-of-the-art MRI templates and atlases of the spinal cord, algorithms to segment and register new data to the templates, and motion correction methods for diffusion and functional time series. SCT is tailored towards standardization and automation of the processing pipeline, versatility, modularity, and it follows guidelines of software development and distribution. Preliminary applications of SCT cover a variety of studies, from cross-sectional area measures in large databases of patients, to the precise quantification of mpMRI metrics in specific spinal pathways. We anticipate that SCT will bring together the spinal cord neuroimaging community by establishing standard templates and analysis procedures.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Atlas; MRI; Open-source; Software; Spinal cord; Template

Mesh:

Year:  2016        PMID: 27720818     DOI: 10.1016/j.neuroimage.2016.10.009

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  119 in total

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Authors:  C Tsagkas; A Horvath; A Altermatt; S Pezold; M Weigel; T Haas; M Amann; L Kappos; T Sprenger; O Bieri; P Cattin; K Parmar
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6.  Diffusion MRI microstructural models in the cervical spinal cord - Application, normative values, and correlations with histological analysis.

Authors:  Kurt G Schilling; Samantha By; Haley R Feiler; Bailey A Box; Kristin P O'Grady; Atlee Witt; Bennett A Landman; Seth A Smith
Journal:  Neuroimage       Date:  2019-07-19       Impact factor: 6.556

7.  Clinically Feasible Microstructural MRI to Quantify Cervical Spinal Cord Tissue Injury Using DTI, MT, and T2*-Weighted Imaging: Assessment of Normative Data and Reliability.

Authors:  A R Martin; B De Leener; J Cohen-Adad; D W Cadotte; S Kalsi-Ryan; S F Lange; L Tetreault; A Nouri; A Crawley; D J Mikulis; H Ginsberg; M G Fehlings
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Journal:  J Magn Reson Imaging       Date:  2018-08-29       Impact factor: 4.813

9.  A Novel MRI Biomarker of Spinal Cord White Matter Injury: T2*-Weighted White Matter to Gray Matter Signal Intensity Ratio.

Authors:  A R Martin; B De Leener; J Cohen-Adad; D W Cadotte; S Kalsi-Ryan; S F Lange; L Tetreault; A Nouri; A Crawley; D J Mikulis; H Ginsberg; M G Fehlings
Journal:  AJNR Am J Neuroradiol       Date:  2017-04-20       Impact factor: 3.825

10.  Machine Learning for the Prediction of Cervical Spondylotic Myelopathy: A Post Hoc Pilot Study of 28 Participants.

Authors:  Benjamin S Hopkins; Kenneth A Weber; Kartik Kesavabhotla; Monica Paliwal; Donald R Cantrell; Zachary A Smith
Journal:  World Neurosurg       Date:  2019-03-25       Impact factor: 2.104

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