Investigating brain structural patterns in first episode psychosis and schizophrenia using MRI and a machine learning approach

Investigating brain structural patterns in first episode psychosis and schizophrenia using MRI and a machine learning approach

Author Moura, Adriana Miyazaki de Google Scholar
Pinaya, Walter Hugo Lopez Google Scholar
Gadelha, Ary Autor UNIFESP Google Scholar
Zugman, Andre Autor UNIFESP Google Scholar
Noto, Cristiano Autor UNIFESP Google Scholar
Cordeiro, Quirino Autor UNIFESP Google Scholar
Belangero, Sintia Iole Autor UNIFESP Google Scholar
Jackowski, Andrea Parolin Autor UNIFESP Google Scholar
Bressan, Rodrigo Affonseca Autor UNIFESP Google Scholar
Sato, Joao Ricardo Autor UNIFESP Google Scholar
Abstract In this study, we employed the Maximum Uncertainty Linear Discriminant Analysis (MLDA) to investigate whether the structural brain patterns in first episode psychosis (FEP) patients would be more similar to patients with chronic schizophrenia (SCZ) or healthy controls (HC), from a schizophrenia model perspective. Brain regions volumetric data were estimated by using MRI images of SCZ and FEP patients and HC. First, we evaluated the MLDA performance in discriminating SCZ from controls, which provided a score based on a model for changes in brain structure in SCZ. In the following, we compared the volumetric patterns of FEP patients with patterns of SCZ and healthy controls using these scores. The FEP group had a score distribution more similar to patients with schizophrenia (p-value = .461

Cohen's d = -.15) in comparison with healthy subjects (p-value = .003

Cohen's d = .62). Structures related to the limbic system and the circuitry involved in goal-directed behaviours were the most discriminant regions. There is a distinct pattern of volumetric changes in patients with schizophrenia in contrast to healthy controls, and this pattern seem to be detectable already in FEP.
Keywords First-episode psychosis
Machine learning
Pattern Recognition
Language English
Sponsor UFABC
Sao Paulo Research Foundation (FAPESP)
Grant number FAPESP: 2013/05168-7
FAPESP: 2013/10498-6
FAPESP: 2013/08531-5
FAPESP: 2014/07280-1
CNPq: 457217/2014-6
Date 2018
Published in Psychiatry Research-Neuroimaging. Clare, v. 275, p. 14-20, 2018.
ISSN 0925-4927 (Sherpa/Romeo, impact factor)
Publisher Elsevier Ireland Ltd
Extent 14-20
Access rights Closed access
Type Article
Web of Science ID WOS:000429897200003

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