White matter tract-specific quantitative analysis in multiple sclerosis: Comparison of optic radiation reconstruction techniques.

The posterior visual pathway is commonly affected by multiple sclerosis (MS) pathology that results in measurable clinical and electrophysiological impairment. Due to its highly structured retinotopic mapping, the visual pathway represents an ideal substrate for investigating patho-mechanisms in MS....

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Main Authors: Chenyu Wang, Alexander Klistorner, Linda Ly, Michael H Barnett
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2018-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5771610?pdf=render
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author Chenyu Wang
Alexander Klistorner
Linda Ly
Michael H Barnett
author_facet Chenyu Wang
Alexander Klistorner
Linda Ly
Michael H Barnett
author_sort Chenyu Wang
collection DOAJ
description The posterior visual pathway is commonly affected by multiple sclerosis (MS) pathology that results in measurable clinical and electrophysiological impairment. Due to its highly structured retinotopic mapping, the visual pathway represents an ideal substrate for investigating patho-mechanisms in MS. Therefore, a reliable and robust imaging segmentation method for in-vivo delineation of the optic radiations (OR) is needed. However, diffusion-based tractography approaches, which are typically used for OR segmentation are confounded by the presence of focal white matter lesions. Current solutions require complex acquisition paradigms and demand expert image analysis, limiting application in both clinical trials and clinical practice. In the current study, using data acquired in a clinical setting on a 3T scanner, we optimised and compared two approaches for optic radiation (OR) reconstruction: individual probabilistic tractography-based and template-based methods. OR segmentation results were applied to subjects with MS and volumetric and diffusivity parameters were compared between OR segmentation techniques. Despite differences in reconstructed OR volumes, both OR lesion volume and OR diffusivity measurements in MS subjects were highly comparable using optimised probabilistic tractography-based, and template-based, methods. The choice of OR reconstruction technique should be determined primarily by the research question and the nature of the available dataset. Template-based approaches are particularly suited to the semi-automated analysis of large image datasets and have utility even in the absence of dMRI acquisitions. Individual tractography methods, while more complex than template based OR reconstruction, permit measurement of diffusivity changes along fibre bundles that are affected by specific MS lesions or other focal pathologies.
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spelling doaj.art-797559e637e94f76afc26e34b2f7db912022-12-22T02:45:22ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-01131e019113110.1371/journal.pone.0191131White matter tract-specific quantitative analysis in multiple sclerosis: Comparison of optic radiation reconstruction techniques.Chenyu WangAlexander KlistornerLinda LyMichael H BarnettThe posterior visual pathway is commonly affected by multiple sclerosis (MS) pathology that results in measurable clinical and electrophysiological impairment. Due to its highly structured retinotopic mapping, the visual pathway represents an ideal substrate for investigating patho-mechanisms in MS. Therefore, a reliable and robust imaging segmentation method for in-vivo delineation of the optic radiations (OR) is needed. However, diffusion-based tractography approaches, which are typically used for OR segmentation are confounded by the presence of focal white matter lesions. Current solutions require complex acquisition paradigms and demand expert image analysis, limiting application in both clinical trials and clinical practice. In the current study, using data acquired in a clinical setting on a 3T scanner, we optimised and compared two approaches for optic radiation (OR) reconstruction: individual probabilistic tractography-based and template-based methods. OR segmentation results were applied to subjects with MS and volumetric and diffusivity parameters were compared between OR segmentation techniques. Despite differences in reconstructed OR volumes, both OR lesion volume and OR diffusivity measurements in MS subjects were highly comparable using optimised probabilistic tractography-based, and template-based, methods. The choice of OR reconstruction technique should be determined primarily by the research question and the nature of the available dataset. Template-based approaches are particularly suited to the semi-automated analysis of large image datasets and have utility even in the absence of dMRI acquisitions. Individual tractography methods, while more complex than template based OR reconstruction, permit measurement of diffusivity changes along fibre bundles that are affected by specific MS lesions or other focal pathologies.http://europepmc.org/articles/PMC5771610?pdf=render
spellingShingle Chenyu Wang
Alexander Klistorner
Linda Ly
Michael H Barnett
White matter tract-specific quantitative analysis in multiple sclerosis: Comparison of optic radiation reconstruction techniques.
PLoS ONE
title White matter tract-specific quantitative analysis in multiple sclerosis: Comparison of optic radiation reconstruction techniques.
title_full White matter tract-specific quantitative analysis in multiple sclerosis: Comparison of optic radiation reconstruction techniques.
title_fullStr White matter tract-specific quantitative analysis in multiple sclerosis: Comparison of optic radiation reconstruction techniques.
title_full_unstemmed White matter tract-specific quantitative analysis in multiple sclerosis: Comparison of optic radiation reconstruction techniques.
title_short White matter tract-specific quantitative analysis in multiple sclerosis: Comparison of optic radiation reconstruction techniques.
title_sort white matter tract specific quantitative analysis in multiple sclerosis comparison of optic radiation reconstruction techniques
url http://europepmc.org/articles/PMC5771610?pdf=render
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