In this study, SHAP analysis of the XGBoost model’s decision-making process revealed that PSMA-TVp, and TL-PSMAp made the largest marginal contributions, suggesting that volumetric parameters exhibit greater stability and discriminative power in predicting prostate cancer metastasis. The gene discussed is FOLH1; the disease is Familial prostate cancer.