Diffusion tensor and restriction spectrum imaging reflect different aspects of neurodegeneration in Parkinson's disease

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F19%3A00071108" target="_blank" >RIV/00159816:_____/19:00071108 - isvavai.cz</a>

Alternative codes found

RIV/00216224:14740/19:00109991

Result on the web

<a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0217922" target="_blank" >https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0217922</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1371/journal.pone.0217922" target="_blank" >10.1371/journal.pone.0217922</a>

Result language

angličtina

Original language name

Diffusion tensor and restriction spectrum imaging reflect different aspects of neurodegeneration in Parkinson's disease

Original language description

To meet the need for Parkinson&apos;s disease biomarkers and evidence for amount and distribution of pathological changes, MRI diffusion tensor imaging (DTI) has been explored in a number of previous studies. However, conflicting results warrant further investigations. As tissue microstructure, particularly of the grey matter, is heterogeneous, a more precise diffusion model may benefit tissue characterization. The purpose of this study was to analyze the diffusion-based imaging technique restriction spectrum imaging (RSI) and DTI, and their ability to detect microstructural changes within brain regions associated with motor function in Parkinson&apos;s disease. Diffusion weighted (DW) MR images of a total of 100 individuals, (46 Parkinson&apos;s disease patients and 54 healthy controls) were collected using b-values of 0-4000s/mm(2). Output diffusion-based maps were estimated based on the RSI-model combining the full set of DW-images (Cellular Index (CI), Neurite Density (ND)) and DTI-model combining b = 0 and b = 1000 s/mm(2) (fractional anisotropy (FA), Axial-, Mean-and Radial diffusivity (AD, MD, RD)). All parametric maps were analyzed in a voxel-wise group analysis, with focus on typical brain regions associated with Parkinson&apos;s disease pathology. CI, ND and DTI diffusivity metrics (AD, MD, RD) demonstrated the ability to differentiate between groups, with strongest performance within the thalamus, prone to pathology in Parkinson&apos;s disease. Our results indicate that RSI may improve the predictive power of diffusion-based MRI, and provide additional information when combined with the standard diffusivity measurements. In the absence of major atrophy, diffusion techniques may reveal microstructural pathology. Our results suggest that protocols for MRI diffusion imaging may be adapted to more sensitive detection of pathology at different sites of the central nervous system.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

30103 - Neurosciences (including psychophysiology)

Project

<a href="/en/project/EF16_013%2F0001775" target="_blank" >EF16_013/0001775: Modernization and support of research activities of the national infrastructure for biological and medical imaging Czech-BioImaging</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

PLoS ONE

ISSN

1932-6203

e-ISSN

—

Volume of the periodical

14

Issue of the periodical within the volume

5

Country of publishing house

US - UNITED STATES

Number of pages

13

Pages from-to

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UT code for WoS article

000469759100127

EID of the result in the Scopus database

2-s2.0-85066635216