Prediction of violence in male schizophrenia using sMRI, based on machine learning algorithms

BMC Psychiatry

卷:22

Research

Wenzhi Pei¹  Xulai Zhang¹  Tao Yu¹  Chunyuan Xu¹  Chenchen Deng² 

[1] Anhui Mental Health Center; Affiliated Psychological Hospital of Anhui Medical University; Hefei Fourth People’s Hospital; Anhui Clinical Research Center for Mental Disorders, 230022, Hefei, Anhui, China;

[2] Anhui Province Maternity & Child Health Hospital, 230022, Hefei, Anhui, China;

关键词: Schizophrenia;    Violence;    Machine learning;    Structural MRI;   

DOI  :  10.1186/s12888-022-04331-1

 received in 2022-07-19, accepted in 2022-10-24,  发布年份 2022

来源: Springer

【 摘 要 】

BackgroundViolent behavior in patients with schizophrenia (SCZ) is a major social problem. The early identification of SCZ patients with violence can facilitate implementation of targeted intervention.MethodsA total of 57 male SCZ patients were recruited into this study. The general linear model was utilized to compare differences in structural magnetic resonance imaging (sMRI) including gray matter volume, cortical surface area, and cortical thickness between 30 SCZ patients who had exhibited violence and 27 SCZ patients without a history of violence. Based on machine learning algorithms, the different sMRI features between groups were integrated into the models for prediction of violence in SCZ patients.ResultsAfter controlling for the whole brain volume and age, the general linear model showed significant reductions in right bankssts thickness, inferior parietal thickness as well as left frontal pole volume in the patients with SCZ and violence relative to those without violence. Among seven machine learning algorithms, Support Vector Machine (SVM) have better performance in differentiating patients with violence from those without violence, with its balanced accuracy and area under curve (AUC) reaching 0.8231 and 0.841, respectively.ConclusionsPatients with SCZ who had a history of violence displayed reduced cortical thickness and volume in several brain regions. Based on machine learning algorithms, structural MRI features are useful to improve predictive ability of SCZ patients at particular risk of violence.

【 授权许可】

CC BY   
© The Author(s) 2022

【 图 表 】

Fig. 1