Cargando…
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...
Autores principales: | , , , , , , , , |
---|---|
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 |
_version_ | 1783470602764419072 |
---|---|
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. |
format | Online Article Text |
id | pubmed-6856605 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT shiraniafsaneh diffusionbasisspectrumimagingforidentifyingpathologiesinmssubtypes AT sunpeng diffusionbasisspectrumimagingforidentifyingpathologiesinmssubtypes AT trinkauskathryn diffusionbasisspectrumimagingforidentifyingpathologiesinmssubtypes AT perantiedanac diffusionbasisspectrumimagingforidentifyingpathologiesinmssubtypes AT georgeajit diffusionbasisspectrumimagingforidentifyingpathologiesinmssubtypes AT naismithrobertt diffusionbasisspectrumimagingforidentifyingpathologiesinmssubtypes AT schmidtroberte diffusionbasisspectrumimagingforidentifyingpathologiesinmssubtypes AT songshengkwei diffusionbasisspectrumimagingforidentifyingpathologiesinmssubtypes AT crossanneh diffusionbasisspectrumimagingforidentifyingpathologiesinmssubtypes |