Progression of Regional Microstructural Degeneration in Parkinson's Disease: A Multicenter Diffusion Tensor Imaging Study

Yu Zhang; I-Wei Wu; Duygu Tosun; Eric Foster; Norbert Schuff; Parkinson’s Progression Markers Initiative

doi:10.1371/journal.pone.0165540

Back

Progression of Regional Microstructural Degeneration in Parkinson's Disease: A Multicenter Diffusion Tensor Imaging Study

Journal article

Open access

Peer reviewed

Progression of Regional Microstructural Degeneration in Parkinson's Disease: A Multicenter Diffusion Tensor Imaging Study

Yu Zhang, I-Wei Wu, Duygu Tosun, Eric Foster, Norbert Schuff and Parkinson’s Progression Markers Initiative

PloS one, Vol.11(10), pp.e0165540-e0165540

2016

DOI: 10.1371/journal.pone.0165540

PMCID: PMC5087900

PMID: 27798653

Files and links (1)

url

https://doi.org/10.1371/journal.pone.0165540View

Published (Version of record) Open Access

Abstract

This study aimed to identify the utility of diffusion tensor imaging (DTI) in measuring the regional distribution of abnormal microstructural progression in patients with Parkinson's disease who were enrolled in the Parkinson's progression marker initiative (PPMI). One hundred and twenty two de-novo PD patients (age = 60.5±9) and 50 healthy controls (age = 60.6±11) had DTI scans at baseline and 12.6±1 months later. Automated image processing included an intra-subject registration of all time points and an inter-subjects registration to a brain atlas. Annualized rates of DTI variations including fractional anisotropy (FA), radial (rD) and axial (aD) diffusivity were estimated in a total of 118 white matter and subcortical regions of interest. A mixed effects model framework was used to determine the degree to which DTI changes differed in PD relative to changes in healthy subjects. Significant DTI changes were also tested for correlations with changes in clinical measures, dopaminergic imaging and CSF biomarkers in PD patients. Compared to normal aging, PD was associated with higher rates of FA reduction, rD and aD increases predominantly in the substantia nigra, midbrain and thalamus. The highest rates of FA reduction involved the substantia nigra (3.6±1.4%/year from baseline, whereas the highest rates of increased diffusivity involved the thalamus (rD: 8.0±2.9%/year, aD: 4.0±1.5%/year). In PD patients, high DTI changes in the substantia nigra correlated with increasing dopaminergic deficits as well as with declining α-synuclein and total tau protein concentrations in cerebrospinal fluid. Increased DTI rates in the thalamus correlated with progressive decline in global cognition in PD. The results suggest that higher rates of regional microstructural degeneration are potential markers of PD progression.

Biomarkers - cerebrospinal fluid

Diffusion Tensor Imaging - methods

Disease Progression

Female

Follow-Up Studies

Humans

Image Processing, Computer-Assisted

Male

Neurodegenerative Diseases - diagnostic imaging

Neurodegenerative Diseases - pathology

Parkinson Disease - diagnostic imaging

Parkinson Disease - metabolism

Parkinson Disease - pathology

Parkinson Disease - physiopathology

Phenotype

Putamen - metabolism

Putamen - pathology

Substantia Nigra - metabolism

Substantia Nigra - pathology

Details

Title: Subtitle: Progression of Regional Microstructural Degeneration in Parkinson's Disease: A Multicenter Diffusion Tensor Imaging Study
Creators: Yu Zhang - University of California, San Francisco
I-Wei Wu - University of California, San Francisco
Duygu Tosun - University of California, San Francisco
Eric Foster - University of Iowa
Norbert Schuff - University of California, San Francisco
Parkinson’s Progression Markers Initiative
Resource Type: Journal article
Publication Details: PloS one, Vol.11(10), pp.e0165540-e0165540
DOI: 10.1371/journal.pone.0165540
PMID: 27798653
PMCID: PMC5087900
NLM abbreviation: PLoS One
ISSN: 1932-6203
eISSN: 1932-6203
Grant note: DOI: 10.13039/100000864, name: Michael J. Fox Foundation; DOI: 10.13039/100000864, name: Michael J. Fox Foundation, award: 9692
Language: English
Date published: 2016
Academic Unit: Biostatistics
Record Identifier: 9984363571402771

Metrics

12 Record Views

71 Times Cited - Web of Science