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Diffusion basis spectrum imaging for identifying pathologies in MS subtypes

Diffusion basis spectrum imaging (DBSI) combines discrete anisotropic diffusion tensors and the spectrum of isotropic diffusion tensors to model the underlying multiple sclerosis (MS) pathologies. We used clinical MS subtypes as a surrogate of underlying pathologies to assess DBSI as a biomarker of...

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Autores principales: Shirani, Afsaneh, Sun, Peng, Trinkaus, Kathryn, Perantie, Dana C., George, Ajit, Naismith, Robert T., Schmidt, Robert E., Song, Sheng‐Kwei, Cross, Anne H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6856605/
https://www.ncbi.nlm.nih.gov/pubmed/31588688
http://dx.doi.org/10.1002/acn3.50903
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author Shirani, Afsaneh
Sun, Peng
Trinkaus, Kathryn
Perantie, Dana C.
George, Ajit
Naismith, Robert T.
Schmidt, Robert E.
Song, Sheng‐Kwei
Cross, Anne H.
author_facet Shirani, Afsaneh
Sun, Peng
Trinkaus, Kathryn
Perantie, Dana C.
George, Ajit
Naismith, Robert T.
Schmidt, Robert E.
Song, Sheng‐Kwei
Cross, Anne H.
author_sort Shirani, Afsaneh
collection PubMed
description Diffusion basis spectrum imaging (DBSI) combines discrete anisotropic diffusion tensors and the spectrum of isotropic diffusion tensors to model the underlying multiple sclerosis (MS) pathologies. We used clinical MS subtypes as a surrogate of underlying pathologies to assess DBSI as a biomarker of pathology in 55 individuals with MS. Restricted isotropic fraction (reflecting cellularity) and fiber fraction (representing apparent axonal density) were the most important DBSI metrics to classify MS using brain white matter lesions. These DBSI metrics outperformed lesion volume. When analyzing the normal‐appearing corpus callosum, the most significant DBSI metrics were fiber fraction, radial diffusivity (reflecting myelination), and nonrestricted isotropic fraction (representing edema). This study provides preliminary evidence supporting the ability of DBSI as a potential noninvasive biomarker of MS neuropathology.
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spelling pubmed-68566052019-12-12 Diffusion basis spectrum imaging for identifying pathologies in MS subtypes Shirani, Afsaneh Sun, Peng Trinkaus, Kathryn Perantie, Dana C. George, Ajit Naismith, Robert T. Schmidt, Robert E. Song, Sheng‐Kwei Cross, Anne H. Ann Clin Transl Neurol Brief Communications Diffusion basis spectrum imaging (DBSI) combines discrete anisotropic diffusion tensors and the spectrum of isotropic diffusion tensors to model the underlying multiple sclerosis (MS) pathologies. We used clinical MS subtypes as a surrogate of underlying pathologies to assess DBSI as a biomarker of pathology in 55 individuals with MS. Restricted isotropic fraction (reflecting cellularity) and fiber fraction (representing apparent axonal density) were the most important DBSI metrics to classify MS using brain white matter lesions. These DBSI metrics outperformed lesion volume. When analyzing the normal‐appearing corpus callosum, the most significant DBSI metrics were fiber fraction, radial diffusivity (reflecting myelination), and nonrestricted isotropic fraction (representing edema). This study provides preliminary evidence supporting the ability of DBSI as a potential noninvasive biomarker of MS neuropathology. John Wiley and Sons Inc. 2019-10-06 /pmc/articles/PMC6856605/ /pubmed/31588688 http://dx.doi.org/10.1002/acn3.50903 Text en © 2019 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals, Inc on behalf of American Neurological Association. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Brief Communications
Shirani, Afsaneh
Sun, Peng
Trinkaus, Kathryn
Perantie, Dana C.
George, Ajit
Naismith, Robert T.
Schmidt, Robert E.
Song, Sheng‐Kwei
Cross, Anne H.
Diffusion basis spectrum imaging for identifying pathologies in MS subtypes
title Diffusion basis spectrum imaging for identifying pathologies in MS subtypes
title_full Diffusion basis spectrum imaging for identifying pathologies in MS subtypes
title_fullStr Diffusion basis spectrum imaging for identifying pathologies in MS subtypes
title_full_unstemmed Diffusion basis spectrum imaging for identifying pathologies in MS subtypes
title_short Diffusion basis spectrum imaging for identifying pathologies in MS subtypes
title_sort diffusion basis spectrum imaging for identifying pathologies in ms subtypes
topic Brief Communications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6856605/
https://www.ncbi.nlm.nih.gov/pubmed/31588688
http://dx.doi.org/10.1002/acn3.50903
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