Development and internal validation of a nomogram combining ultrasound O-RADS classification, quantitative contrast-enhanced ultrasound, and serological biomarkers for the preoperative prediction of ovarian malignancy

Abstract Purpose To develop and internally validate a nomogram combining ultrasound O-RADS classification, quantitative contrast-enhanced ultrasound (CEUS), and serological biomarkers for the preoperative prediction of ovarian malignancy. Methods In this retrospective study, 112 patients with pathologically confirmed adnexal masses (59 benign, 53 malignant) underwent preoperative conventional ultrasound, O-RADS grading, and CEUS between January 2025 and January 2026. Candidate predictors were screened by LASSO regression and entered into multivariate logistic regression to construct a nomogram. Discrimination, calibration, and clinical utility were evaluated by the area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow testing, precision-recall (PR) curves, and decision curve analysis (DCA). Results The nomogram integrated O-RADS classification, four quantitative CEUS parameters (arrival time, time to peak, peak intensity, time-intensity curve area under the curve), and six laboratory indicators (CA125, HE4, platelet count, thrombin time, prealbumin, high-density lipoprotein). The model achieved an AUC of 0.979, sensitivity of 91.43%, specificity of 92.31%, and accuracy of 91.89%, outperforming O-RADS classification alone (AUC, 0.890); Hosmer-Lemeshow testing indicated good calibration (chi-square = 5.51, P = 0.70). Conclusion The multimodal nomogram combining O-RADS classification, quantitative CEUS, and serological biomarkers improved preoperative discrimination of ovarian malignancy and may serve as an objective risk-stratification tool for adnexal masses. Prospective multicenter external validation is required before clinical implementation.