Establishment and validation of novel predictive models to predict bone metastasis in newly diagnosed prostate adenocarcinoma based on single-photon emission computed tomography radiomics.

Abstract

Abstract Purpose In order to establish and validate novel predictive models for predicting bone metastasis (BM) in newly diagnosed prostate adenocarcinoma (PCa) in single-photon emission computed tomography radiomics. Method In a retrospective review of clinical SPECT database, 176 patients (training set: n = 140; validation set: n = 36) who underwent SPECT/CT imaging and histologically confirmed with newly diagnosed PCa from June 2016 to June 2022 were enrolled. Radiomic features were extracted from ROI in a targeted lesion of each patient. Clinical features, including age, t-PSA, and Gleason grades, were included. Statistical tests were then used to eliminate irrelevant and redundant features. Finally, three types of optimized models were constructed for the prediction. Furthermore, 5-fold cross-validation was applied to obtain the sensitivity, specificity, accuracy, and area under the curve (AUC) for performance evaluation. The clinical usefulness of the multivariate models was estimated through decision curve analysis (DCA). Results Radiomics signature consisting of 27 selected features was significantly correlated with bone status(P < 0.01 for both training and validation sets). Collectively, the models showed good predictive efficiency. The AUC values ranged from 0.87 to 0.98 in four models. The AUC value of the human experts was 0.655 and 0.872 in the training and validation groups, respectively. Most radiomic models showed better diagnostic accuracy than human experts in the training group and the validation group. DCA also demonstrated the superiority of the radiomics models compared to human experts. Conclusion Our proposed models, which incorporate SPECT-based radiomics signature and clinical risk factors, could be a promising auxiliary means to assist radiologists or medical physicians in their subsequent workup to confirm the diagnosis of BM.