Machine learning-based radiomics for multiple primary prostate cancer biological characteristics prediction with 18 F-PSMA-1007 PET: comparison among different volume segmentation thresholds.

F-1007-PSMA PET-based radiomics features at 40-50% SUVmax showed the best predictive performance for multiple PCa biological characteristics evaluation. Compared to the single PSA model, radiomics features may provide additional benefits in predicting the biological characteristics of PCa.