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Fourier transform power spectrum is a potential measure of tissue alignment in standard MRI: A multiple sclerosis study
Loss of tissue coherency in brain white matter is found in many neurological diseases such as multiple sclerosis (MS). While several approaches have been proposed to evaluate white matter coherency including fractional anisotropy and fiber tracking in diffusion-weighted imaging, few are available fo...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5393867/ https://www.ncbi.nlm.nih.gov/pubmed/28414816 http://dx.doi.org/10.1371/journal.pone.0175979 |
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author | Sharma, Shrushrita Zhang, Yunyan |
author_facet | Sharma, Shrushrita Zhang, Yunyan |
author_sort | Sharma, Shrushrita |
collection | PubMed |
description | Loss of tissue coherency in brain white matter is found in many neurological diseases such as multiple sclerosis (MS). While several approaches have been proposed to evaluate white matter coherency including fractional anisotropy and fiber tracking in diffusion-weighted imaging, few are available for standard magnetic resonance imaging (MRI). Here we present an image post-processing method for this purpose based on Fourier transform (FT) power spectrum. T(2)-weighted images were collected from 19 patients (10 relapsing-remitting and 9 secondary progressive MS) and 19 age- and gender-matched controls. Image processing steps included: computation, normalization, and thresholding of FT power spectrum; determination of tissue alignment profile and dominant alignment direction; and calculation of alignment complexity using a new measure named angular entropy. To test the validity of this method, we used a highly organized brain white matter structure, corpus callosum. Six regions of interest were examined from the left, central and right aspects of both genu and splenium. We found that the dominant orientation of each ROI derived from our method was significantly correlated with the predicted directions based on anatomy. There was greater angular entropy in patients than controls, and a trend to be greater in secondary progressive MS patients. These findings suggest that it is possible to detect tissue alignment and anisotropy using traditional MRI, which are routinely acquired in clinical practice. Analysis of FT power spectrum may become a new approach for advancing the evaluation and management of patients with MS and similar disorders. Further confirmation is warranted. |
format | Online Article Text |
id | pubmed-5393867 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-53938672017-05-04 Fourier transform power spectrum is a potential measure of tissue alignment in standard MRI: A multiple sclerosis study Sharma, Shrushrita Zhang, Yunyan PLoS One Research Article Loss of tissue coherency in brain white matter is found in many neurological diseases such as multiple sclerosis (MS). While several approaches have been proposed to evaluate white matter coherency including fractional anisotropy and fiber tracking in diffusion-weighted imaging, few are available for standard magnetic resonance imaging (MRI). Here we present an image post-processing method for this purpose based on Fourier transform (FT) power spectrum. T(2)-weighted images were collected from 19 patients (10 relapsing-remitting and 9 secondary progressive MS) and 19 age- and gender-matched controls. Image processing steps included: computation, normalization, and thresholding of FT power spectrum; determination of tissue alignment profile and dominant alignment direction; and calculation of alignment complexity using a new measure named angular entropy. To test the validity of this method, we used a highly organized brain white matter structure, corpus callosum. Six regions of interest were examined from the left, central and right aspects of both genu and splenium. We found that the dominant orientation of each ROI derived from our method was significantly correlated with the predicted directions based on anatomy. There was greater angular entropy in patients than controls, and a trend to be greater in secondary progressive MS patients. These findings suggest that it is possible to detect tissue alignment and anisotropy using traditional MRI, which are routinely acquired in clinical practice. Analysis of FT power spectrum may become a new approach for advancing the evaluation and management of patients with MS and similar disorders. Further confirmation is warranted. Public Library of Science 2017-04-17 /pmc/articles/PMC5393867/ /pubmed/28414816 http://dx.doi.org/10.1371/journal.pone.0175979 Text en © 2017 Sharma, Zhang http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Sharma, Shrushrita Zhang, Yunyan Fourier transform power spectrum is a potential measure of tissue alignment in standard MRI: A multiple sclerosis study |
title | Fourier transform power spectrum is a potential measure of tissue alignment in standard MRI: A multiple sclerosis study |
title_full | Fourier transform power spectrum is a potential measure of tissue alignment in standard MRI: A multiple sclerosis study |
title_fullStr | Fourier transform power spectrum is a potential measure of tissue alignment in standard MRI: A multiple sclerosis study |
title_full_unstemmed | Fourier transform power spectrum is a potential measure of tissue alignment in standard MRI: A multiple sclerosis study |
title_short | Fourier transform power spectrum is a potential measure of tissue alignment in standard MRI: A multiple sclerosis study |
title_sort | fourier transform power spectrum is a potential measure of tissue alignment in standard mri: a multiple sclerosis study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5393867/ https://www.ncbi.nlm.nih.gov/pubmed/28414816 http://dx.doi.org/10.1371/journal.pone.0175979 |
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