Preoperative prediction of Ki-67 expression level in breast cancer based on three-dimensional features of DCE-MRI imaging
Objective:To construct a 3D imaging model based on dynamic enhanced magnetic resonance imaging(DCE-MRI)to predict the expression level of Ki-67 in breast cancer.Methods:The clinical,pathological and MR Dynamic enhanced imaging data of 110 female patients with invasive breast cancer were analyzed retrospectively.Patients were divided into two groups according to Ki-67 value,those with Ki-67 value≥30%was defined as high expression group and<30%was defined as low expression group.The 3D imaging features of the tumor area in the fourth stage of DCE-MRI were extracted.The optimal features were selected to construct the expression state model of Ki-67 prediction in breast cancer,and the Nomogram was drawn to visualize the model and evaluate the effectiveness of the model.Bootstrap was used to sample the training sample for 1000 times and reconstruct the model for internal verification.Results:The receiver operating characteristic(ROC)of the training group showed that the area under the curve(AUC)was 0.876(95%CI 0.803～0.949),the optimal cut-off value was 0.513,the sensitivity was 80.6%,and the specificity was 86.9%.The Hosmer-Lemeshow goodness of fit test was 0.735.The decision curve(DCA)threshold ranges from 17%to 100%.In the internal validation group,AUC was 0.854(95%CI 0.851～0.878),sensitivity was 84.0%,and specificity was 72.9%.Conclusion:The expression status of Ki-67 in breast cancer can be predicted before surgery based on the 3D features of DCE-MRI imaging,which provides an effective and non-invasive imaging model to evaluate the proliferation of breast cancer tumor cells before surgery,and provides a new reference for the treatment decision selection of breast cancer.
万方数据
维普
