Investigating brain structural patterns in first episode psychosis and schizophrenia using MRI and a machine learning approach. (30th May 2018)
- Record Type:
- Journal Article
- Title:
- Investigating brain structural patterns in first episode psychosis and schizophrenia using MRI and a machine learning approach. (30th May 2018)
- Main Title:
- Investigating brain structural patterns in first episode psychosis and schizophrenia using MRI and a machine learning approach
- Authors:
- de Moura, Adriana Miyazaki
Pinaya, Walter Hugo Lopez
Gadelha, Ary
Zugman, André
Noto, Cristiano
Cordeiro, Quirino
Belangero, Sintia Iole
Jackowski, Andrea P.
Bressan, Rodrigo A.
Sato, João Ricardo - Abstract:
- 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.T he 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. Highlights: We employed machine learning to investigate structural brain patterns in first episode psychosis. Brain regions volumetric data were estimated from MRI. FEP group had a profile more similar to patients in comparison with healthy subjects. Volumetric changes in patients withAbstract: 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.T he 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. Highlights: We employed machine learning to investigate structural brain patterns in first episode psychosis. Brain regions volumetric data were estimated from MRI. FEP group had a profile more similar to patients in comparison with healthy subjects. Volumetric changes in patients with schizophrenia seems to be detectable already in FEP. … (more)
- Is Part Of:
- Psychiatry research. Volume 275(2018)
- Journal:
- Psychiatry research
- Issue:
- Volume 275(2018)
- Issue Display:
- Volume 275, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 275
- Issue:
- 2018
- Issue Sort Value:
- 2018-0275-2018-0000
- Page Start:
- 14
- Page End:
- 20
- Publication Date:
- 2018-05-30
- Subjects:
- First-episode psychosis -- Machine learning -- Neuroimaging -- Pattern Recognition -- Schizophrenia
Psychiatry -- Periodicals
Brain -- Imaging -- Periodicals
Psychiatry -- Periodicals
Diagnostic Imaging -- Periodicals
Psychiatrie -- Périodiques
Cerveau -- Imagerie pour le diagnostic -- Périodiques
616.890754 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09254927 ↗
http://www.clinicalkey.com/dura/browse/journalIssue/09254927 ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/09254927 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.pscychresns.2018.03.003 ↗
- Languages:
- English
- ISSNs:
- 0925-4927
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6946.263705
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 6315.xml