基于多模态超声特征的列线图模型可有效预测三阴性乳腺癌OA

Objective To investigate the predictive value of multimodal ultrasound and pathological features in the diagnosis of triple-negative breast cancer(TNBC),and to construct a nomogram model based on multi-parameter features and evaluate its diagnostic performance.Methods Clinical data of 50 patients with TNBC and 100 patients with non-TNBC(nTNBC)treated at the First Hospital of Shanxi Medical University and the 985th Hospital from October 2023 to October 2025 were retrospectively analyzed.General patient information including age,gender,and medical history was collected.BI-RADS features included morphology,orientation,margin,echo pattern,posterior features,and calcifications.Elastography parameters included maximum and mean SWE values.Contrast-enhanced ultrasound(CEUS)parameters included peak intensity(PI)and time to peak(TP).Histological grade,Ki-67 index,and tumor-infiltrating lymphocyte(TILs)density were also recorded.Independent predictors of TNBC were identified by logistic regression analysis,and a corresponding predictive nomogram was constructed.The area under the receiver operating characteristic curve(AUC)and calibration curve were used to evaluate the predictive ability and clinical application value of the model.Results Pathological analysis showed that most patients in the TNBC group had moderate to high histological grades(grade II and III),whereas the nTNBC group predominantly had low to intermediate grades,with a statistically significant difference between the two groups(P<0.05).The Ki-67 index and TILs density were significantly higher in the TNBC group than in the nTNBC group(both P<0.001).Logistic regression analysis identified oval shape(OR=0.291,P=0.006),absence of calcifications(OR=0.143,P<0.001),posterior acoustic enhancement(OR=0.187,P<0.001),lower mean SWE value(OR=0.753,P<0.001),and higher CEUS PI value(OR=1.091,P<0.001)as independent predictors of TNBC.The AUC of the predictive model was 0.894,indicating high predictive accuracy.Conclusion The predictive nomogram constructed in this study and its validation results show good diagnostic effectiveness,which helps improve clinical diagnosis of TNBC,thereby optimizing treatment plans and improving patient prognosis.