[18F] PSMA-3Q PET/CT radiomics at 45% SUVmax threshold: predicting post-surgical ISUP grade ≥ 4 and extraprostatic extension for noninvasive stratification in prostate cancer management.

OBJECTIVE: To systematically evaluate radiomic features extracted from [18F] PSMA-3Q PET/CT using 40%, 45%, and 50% SUVmax thresholds for their ability to predict post-surgical International Society of Urological Pathology (psISUP) grading and extraprostatic extension (EPE) in prostate cancer and ultimately develop an optimal threshold-based predictive model. MATERIALS & METHODS: This retrospective study included 243 prostate cancer patients undergoing [18F] PSMA-3Q PET/CT before radical prostatectomy. Patients were chronologically divided into training (n = 190) and test (n = 53) cohorts, with stratification by prostate-specific antigen density (PSAD < 0.25 vs. ≥ 0.25 ng/mL). Radiomics features were extracted using 40%, 45%, and 50% SUVmax thresholds. Nine machine learning algorithms developed integrated PET/CT radiomics-clinical models (PC40, PC45, PC50) and PET radiomics-clinical models (P40, P45, P50). Model performance was evaluated using area under the curve (AUC), sensitivity, specificity, positive and negative predictive values. RESULTS: Among the models constructed with 40%, 45%, and 50% SUVmax thresholds, the PC45 model (PET/CT radiomics + clinical parameters) performed best. For predicting psISUP grade ≥ 4, its test set AUC reached 0.917 (95% CI: 0.828-0.985), with 0.800 sensitivity and 0.921 specificity. For EPE prediction, the test set AUC was 0.772(95% CI: 0.633-0.883), sensitivity 0.700 and specificity 0.727. It showed stable performance across PSAD subgroups and higher net clinical benefit. CONCLUSION: The [18F] PSMA-3Q PET/CT radiomics model with a 45% SUVmax threshold may facilitate relatively accurate noninvasive prediction of psISUP grade and EPE. These findings suggest its potential value as a promising preoperative tool for precision prostate cancer management, and provide preliminary evidence supporting its stable and balanced performance as a noninvasive decision‑making aid, pending further validation in larger cohorts.