Identification of texture MRI brain abnormalities on first-episode psychosis and clinical high-risk subjects using explainable artificial intelligence

Alexandra I. Korda*, Christina Andreou, Helena Victoria Rogg, Mihai Avram, Anne Ruef, Christos Davatzikos, Nikolaos Koutsouleris, Stefan Borgwardt

*Corresponding author for this work
3 Citations (Scopus)

Abstract

Structural MRI studies in first-episode psychosis and the clinical high-risk state have consistently shown volumetric abnormalities. Aim of the present study was to introduce radiomics texture features in identification of psychosis. Radiomics texture features describe the interrelationship between voxel intensities across multiple spatial scales capturing the hidden information of underlying disease dynamics in addition to volumetric changes. Structural MR images were acquired from 77 first-episode psychosis (FEP) patients, 58 clinical high-risk subjects with no later transition to psychosis (CHR_NT), 15 clinical high-risk subjects with later transition (CHR_T), and 44 healthy controls (HC). Radiomics texture features were extracted from non-segmented images, and two-classification schemas were performed for the identification of FEP vs. HC and FEP vs. CHR_NT. The group of CHR_T was used as external validation in both schemas. The classification of a subject’s clinical status was predicted by importing separately (a) the difference of entropy feature map and (b) the contrast feature map, resulting in classification balanced accuracy above 72% in both analyses. The proposed framework enhances the classification decision for FEP, CHR_NT, and HC subjects, verifies diagnosis-relevant features and may potentially contribute to identification of structural biomarkers for psychosis, beyond and above volumetric brain changes.

Original languageEnglish
Article number481
JournalTranslational Psychiatry
Volume12
Issue number1
DOIs
Publication statusPublished - 12.2022

Research Areas and Centers

  • Academic Focus: Center for Brain, Behavior and Metabolism (CBBM)

DFG Research Classification Scheme

  • 206-08 Cognitive and Systemic Human Neuroscience
  • 206-10 Clinical Psychiatry, Psychotherapy amd Paediatric and Juvenile Psychiatrie
  • 206-09 Biological Psychiatry

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