Predicting Pathogenic DNA Damage Repair Gene Mutations in Prostate Cancer Patients: A Multi-Center MRI Radiomics Study

Motivation: Pathogenic DDR gene alterations are associated with aggressive disease and poor outcomes among prostate cancer (PCa) patients. Goal(s): To develop a radiomics-based pre-testing model for identifying DDR mutation carriers among PCa patients. Approach: A total of 225 patients from three centers with both multiparameter MRI and genetic DDR mutations testing were included. Radiomic models were established based on T2WI and ADC sequences of MRI images. The predictive values were validated in both internal and external validation cohorts. Results: The radiomics-based model exhibited an AUC of 0.835 in the training dataset, 0.824 in the internal validation dataset, and 0.836 in the external validation dataset. Impact: In the current study, we introduced a noninvasive radiomics feature-based tool designed to predict pDDRg mutations in prostate cancer patients. External validation of the novel tool by datasets from other medical centers revealed a high predictive accuracy for pDDRg mutations.