联合双模态超声及双参数核磁影像组学技术构建对前列腺癌的预测模型OA

Objective To construct and validate a combined model for preoperative noninvasive prediction of prostate cancer(PCa)using radiomic features from dual-modal ultrasound(B-mode+shear wave elastography)and biparametric MRI(T2 WI+ADC).Methods A total of 232 patients with prostate mass lesions who visited the Aerospace Center Hospital from January 2023 to October 2025 were selected,including 127 cases of PCa and 105 cases of benign conditions.All patients underwent dual-modal ultrasound and biparametric MRI examinations.After manual delineation of the lesions,high-throughput radiomics features were extracted.Feature selection was per-formed using LASSO regression,and independent clinical risk factors(age,PSA density)were integrated.Four models were constructed and compared:a clinical model,an ultrasound radiomics model,an MRI radiomics model,and a combined model.The performance was evalua-ted via five-fold cross-validation.Results The combined model demonstrated the best diagnostic efficacy in the validation set,with an AUC of 0.92(95%CI:0.84-0.97),significantly higher than the AUCs of the clinical model(0.76),the ultrasound radiomics model(0.78),and the MRI radiomics model(0.85)(all P<0.05).Decision curve analysis confirmed its greater net clinical benefit across a wide threshold range.Conclusions The validated combined model integrating multimodal radiomics and clinical factors can significantly improve the accura-cy of preoperative noninvasive diagnosis of PCa,demonstrating robust performance and high clinical applicability.