Abstract

Motivation: Tracking hippocampal radiomic changes over time may provide a biomarker to monitor disease progression and treatment response in cerebral small vessel disease (CSVD). Extending proven hippocampal radiomic methods from AD research to the study of CSVD represents a promising approach worthy of further investigation. Goal(s): To develop a radiomics model based on 3D-T1WI images to improve the diagnosis of CSVD with cognitive impairment. Approach: LASSO regression was used for feature selection and model constructionResults: The model attained an accuracy of 0.781, AUC of 0.818, sensitivity of 0.538, and specificity of 0.947 in distinguishing group 2 from NCs in the test sets. Impact: Overall, our findings support the potential for hippocampal textural features to serve as neuroimaging biomarkers of CSVD, providing a useful tool to aid clinical decision-making in precision medicine.