Predictive MRI signatures of alcohol-related risk diverge from group-level structural differences in firefighters
Year: 2026
Type: article
Study design: Observational Study
Abstract: Group-level structural differences may not identify features most relevant to individual prediction. In this cross-sectional study of 686 firefighters, high alcohol-related risk was defined as an Alcohol Use Disorders Identification Test score ≥ 16. We compared structural effect sizes associated with alcohol-related risk with SHAP-derived importance at feature and region levels in a model combining MRI radiomics with demographic, cognitive, and laboratory features. The primary stratified 70/30 split was fixed at seed 42 before held-out performance was examined. In this prespecified split, multimodal CatBoost achieved an AUC of 0.743 (95% CI 0.666–0.819), higher than the clinical-only and radiomics-only representative models. Across 10 training-stage runs on the same held-out test set, its mean AUC was 0.681 (SD 0.054; range 0.555–0.743), and it ranked highest in 6 of 10 runs; 0.743 was the maximum. Cortical features showed larger group differences, whereas SHAP-derived importance highlighted distributed subcortical features in the primary model; thalamic, ventral diencephalic, and ventricular features were among stable repeated-run contributors. Structural effect sizes and SHAP importance showed weak feature-level correspondence ( r = 0.22, p = 0.044) and no detectable region-level correspondence ( r = 0.03, p = 0.844). Within the selected radiomics set, these findings support evaluating group-level association and model-dependent predictive contribution as complementary properties of candidate imaging biomarkers.
Source: Scientific Reports
Institutions: Korea University, Ewha Womans University
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,690
OpenAlex ID: W7223127404