Abstract：Objective To evaluate the efficacy of a combined 3D-VIBE dynamic contrast-enhanced MRI quantitative parameter model in the differential diagnosis of epithelial ovarian cancer. Methods A retrospective analysis was conducted on the clinical and imaging data of patients with pathologically confirmed epithelial ovarian tumors admitted to our hospital from January 2023 to December 2025.Based on pathological examination results,100 patients were divided into a benign epithelial ovarian tumor group(benign group,n=40) and an epithelial ovarian cancer group(malignant group,n=60).All patients underwent routine MRI and 3D-VIBE dynamic contrast-enhanced MRI scans preoperatively.Quantitative parameters were compared between the two groups,and a combined quantitative parameter model was constructed.Receiver operating characteristic(ROC) curves were plotted to evaluate the differential diagnostic efficacy of single quantitative parameters and the combined model. Results The levels of Ktrans,Kep,and MS in the malignant group were higher than those in the benign group,while the levels of TTP and Ve were lower in the malignant group(all P<0.05).Multivariate logistic regression analysis showed that the five quantitative parameters(Ktrans,Kep,Ve,MS,and TTP) were closely related to the incidence of epithelial ovarian cancer(P<0.05).ROC curve analysis showed that the AUCs for the combined diagnosis of epithelial ovarian cancer by the five parameters(Ktrans,Kep,Ve,MS,and TTP) were 0.548,0.716,0.825,0.774,and 0.904,respectively.Z-tests showed that the combined diagnostic efficacy was higher than that of the individual parameters(Z=7.753,12.656,2.992,4.229,and 23.212,all P<0.05). Conclusion The 3D-VIBE dynamic contrast-enhanced MRI quantitative parameter combined model(Ktrans,Kep,Ve,MS,TTP) can effectively integrate the diagnostic information of multiple quantitative parameters,which helps to improve the differential diagnosis efficacy between epithelial ovarian cancer and benign epithelial ovarian tumors.Its sensitivity and specificity are higher than those of single-parameter diagnosis.
2026, Vol. 46 
