Development and validation of 68Ga-PSMA-11 PET/CT-based radiomics model to detect primary prostate cancer
Shiming Zang, Shuyue Ai, Rui Yang, Pengjun Zhang, Wenyu Wu, Zhenyu Zhao, Yudan Ni, Qing Zhang, Hongbin Sun, Hongqian Guo, Ruipeng Jia, Feng Wang
Abstract
BACKGROUND: Ga-prostate-specific membrane antigen (PSMA)-11 PET/CT for predicting intraprostatic lesions in patients with prostate cancer (PCa). METHODS: Ga-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. RESULTS: 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). CONCLUSION: Ga-PSMA-11 PET may non-invasively predict intraprostatic lesions in patients with PCa.