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 |
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Erscheinungsjahr: |
2020 |
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Erschienen: |
2020 |
Enthalten in: |
Zur Gesamtaufnahme - volume:36 |
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Enthalten in: |
Neuroscience bulletin - 36(2020), 10 vom: 03. Okt., Seite 1107-1122 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Ediri Arachchi, Wasana [VerfasserIn] |
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Links: |
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Themen: |
Cortical thickness |
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Anmerkungen: |
Date Completed 27.07.2021 Date Revised 02.10.2021 published: Print-Electronic Citation Status MEDLINE |
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doi: |
10.1007/s12264-020-00520-8 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM310747767 |
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520 | |a 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 | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a Cortical thickness | |
650 | 4 | |a Deformation-based morphometry | |
650 | 4 | |a Multivariate pattern analysis | |
650 | 4 | |a Schizophrenia | |
650 | 4 | |a Structural MRI | |
650 | 4 | |a Tensor-based morphometry | |
650 | 4 | |a Voxel-based morphometry | |
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700 | 1 | |a Zhang, Xi |e verfasserin |4 aut | |
700 | 1 | |a Qin, Wen |e verfasserin |4 aut | |
700 | 1 | |a Zhuo, Chuanjun |e verfasserin |4 aut | |
700 | 1 | |a Yu, Chunshui |e verfasserin |4 aut | |
700 | 1 | |a Liang, Meng |e verfasserin |4 aut | |
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