Development and validation of ⁶⁸Ga-PSMA-11 PET/CT-based radiomics model to detect primary prostate cancer

This study aimed to develop a novel analytic approach based on a radiomics model derived from ⁶⁸Ga-prostate-specific membrane antigen (PSMA)-11 PET/CT for predicting intraprostatic lesions in patients with prostate cancer (PCa).

This retrospective study included consecutive patients with or without PCa who underwent surgery or biopsy after ⁶⁸Ga-PSMA-11 PET/CT. A total of 944 radiomics features were extracted from the images. A radiomics model was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm with tenfold cross-validation in the training set. PET/CT images for the test set were reviewed by experienced nuclear medicine radiologists. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) were calculated for the model and radiologists' results. The AUCs were compared.

The total of 125 patients (86 PCa, 39 benign prostate disease [BPD]) included 87 (61 PCa, 26 BPD) in the training set and 38 (61 PCa, 26 BPD) in the test set. Nine features were selected to construct the radiomics model. The model score differed between PCa and BPD in the training and test sets (both P < 0.001). In the test set, the radiomics model performed better than the radiologists' assessment (AUC, 0.85 [95% confidence interval 0.73, 0.97] vs. 0.63 [0.47, 0.79]; P = 0.036) and showed higher sensitivity (model vs radiologists, 0.84 [0.63, 0.95] vs. 0.74 [0.53, 0.88]; P = 0.002).

Radiomics analysis based on ⁶⁸Ga-PSMA-11 PET may non-invasively predict intraprostatic lesions in patients with PCa.