A Systematic Characterization of Structural Brain Changes in Schizophrenia

A systematic characterization of the similarities and differences among different methods for detecting structural brain abnormalities in schizophrenia, such as voxel-based morphometry (VBM), tensor-based morphometry (TBM), and projection-based thickness (PBT), is important for understanding the brain pathology in schizophrenia and for developing effective biomarkers for a diagnosis of schizophrenia. However, such studies are still lacking. Here, we performed VBM, TBM, and PBT analyses on T1-weighted brain MR images acquired from 116 patients with schizophrenia and 116 healthy controls. We found that, although all methods detected wide-spread structural changes, different methods captured different information - only 10.35% of the grey matter changes in cortex were detected by all three methods, and VBM only detected 11.36% of the white matter changes detected by TBM. Further, pattern classification between patients and controls revealed that combining different measures improved the classification accuracy (81.9%), indicating that fusion of different structural measures serves as a better neuroimaging marker for the objective diagnosis of schizophrenia.

Medienart:

E-Artikel

Erscheinungsjahr:

2020

Erschienen:

2020

Enthalten in:

Zur Gesamtaufnahme - volume:36

Enthalten in:

Neuroscience bulletin - 36(2020), 10 vom: 03. Okt., Seite 1107-1122

Sprache:

Englisch

Beteiligte Personen:

Ediri Arachchi, Wasana [VerfasserIn]
Peng, Yanmin [VerfasserIn]
Zhang, Xi [VerfasserIn]
Qin, Wen [VerfasserIn]
Zhuo, Chuanjun [VerfasserIn]
Yu, Chunshui [VerfasserIn]
Liang, Meng [VerfasserIn]

Links:

Volltext

Themen:

Cortical thickness
Deformation-based morphometry
Journal Article
Multivariate pattern analysis
Schizophrenia
Structural MRI
Tensor-based morphometry
Voxel-based morphometry

Anmerkungen:

Date Completed 27.07.2021

Date Revised 02.10.2021

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1007/s12264-020-00520-8

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM310747767