Structural abnormalities in gray matter, white matter, and cerebrospinal fluid in parkinson's disease: a voxel-based morphometry study.

Authors

Yetong Shi, Yan Zhang, Yunhe Zhang, Yuzhang Wu, Xin Liu, Keke Feng, Yifeng Cheng, Shaoya Yin

Published in

Neurological research. Pages 1-14. Sep 15, 2026. Epub Sep 15, 2026.

Abstract

Parkinson's disease (PD) is a neurodegenerative disorder affecting multiple brain systems, yet whole-brain structural changes remain incompletely characterized. We used voxel-based morphometry (VBM) to systematically quantify gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) volume alterations in PD and explore their potential clinical significance for deep brain stimulation (DBS).
High-resolution T1-weighted MRI scans were acquired from 200 PD patients and 176 age- and sex-matched healthy controls. VBM analysis was performed using SPM12/CAT12, with age, sex, and total intracranial volume as covariates. Statistical threshold was set at voxel-level p < 0.001, cluster-level family-wise error-corrected p < 0.05, with a cluster extent ≥ 100 voxels.
Compared with controls, PD patients showed significant GM and WM volume reductions (both p < 0.001) and CSF volume increase (p < 0.001). GM atrophy was observed in the olfactory cortex, caudate nucleus, precentral gyrus, and supplementary motor area, while bilateral putamen and ventral posterolateral thalamus showed GM volume increase. WM atrophy was distributed in brain regions anatomically corresponding to key tracts of the sensorimotor network, default mode network, and dorsal attention network.
PD patients demonstrate global GM and WM atrophy with increased CSF volume, a bidirectional pattern of coexisting GM reduction and increase, and widespread WM atrophy across multiple functional networks, providing macrostructural imaging evidence for understanding PD clinical heterogeneity. The potential utility of these structural features for preoperative DBS assessment remains purely theoretical and requires prospective validation.

PMID:
42742255
Bibliographic data and abstract were imported from PubMed on 15 Sep 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.