Cortical thickness in Parkinson disease: A coordinate-based meta-analysis

Medicine (Baltimore). 2020 Jul 31;99(31):e21403. doi: 10.1097/MD.0000000000021403.

Abstract

Background: A growing number of studies have used surface-based morphometry (SBM) analyses to investigate gray matter cortical thickness (CTh) abnormalities in Parkinson disease (PD). However, the results across studies are inconsistent and have not been systematically reviewed. A clear picture of CTh alterations in PD remains lacked. Coordinate-based meta-analysis (CBMA) is a powerful tool to quantitatively integrate the results of individual voxel-based neuroimaging studies to identify the functional or structural neural substrates of particular neuropsychiatric disorders. Recently, CBMA has been updated for integrating SBM studies.

Methods: The online databases PubMed, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), WanFang, and SinoMed were comprehensively searched without language limitations from the database inception to February 2, 2020. We will include all SBM studies that compared regional CTh between patients with idiopathic PD and healthy control subjects at the whole-cortex level using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI). In addition to the main CBMA, we will conduct several supplementary analyses to test the robustness of the results, such as jackknife analyses, subgroup analyses, heterogeneity analyses, publication bias analyses, and meta-regression analyses.

Results: This CBMA will offer the latest evidence of CTh alterations in PD.

Conclusions: Consistent and robust evidence of CTh alterations will feature brain morphometry of PD and may facilitate biomarker development.

Prospero registration number: CRD42020148775.

Publication types

  • Meta-Analysis

MeSH terms

  • Cerebral Cortex / diagnostic imaging
  • Cerebral Cortex / physiopathology*
  • Databases, Factual
  • Humans
  • Neuroimaging
  • Parkinson Disease / diagnostic imaging
  • Parkinson Disease / physiopathology*
  • Regression Analysis