KLK3 and neoplasm: Sushentsev et al [23] proposed several machine learning models using baseline radiomic features and clinical variables comprising PSA, MRI-derived gland volume, PSA density, MRI-derived Likert score of tumor suspicion, target lesion localization, and target lesion biopsy grade group to predict baseline risk of PCa progression on AS.