The value of 3D and 2D radiomics features models of MRI in predicting Ki-67 expression in Luminal breast cancer
Objective To explore the value of 3D and 2D radiomics features models based on multiparameter MRI in predicting Ki-67 expression(with 14%and 20%as the critical values,respectively)in breast cancer.Methods The MRI images of 147 patients with pathologically confirmed Luminal breast cancer were analyzed retrospectively.The patients were randomly divided into training set and test set according to the ratio of 7︰3.The 3D and 2D radiomics features of intratumor and peritumor were extracted from diffusion weighted imaging(DWI),dynamic contrast enhancement(DCE)mask(S0)and DCE phase 3(S3)images.Then the models were constructed by multiple pipeline combinations of three feature normalization methods,two feature dimensionality reduction methods,four feature selection methods,and ten classifiers.The receiver operating characteristic(ROC)curve and the area under the curve(AUC)were used to evaluate the prediction performance of the models in order to select the best 3D and 2D single parame-ter(DWI,S0,S3)and multiparameter combination(S0+S3,S0+DWI,S3+DWI,S0+S3+DWI)models.Finally,the differ-ences between the models were compared by De Long test.Results With 14%as the critical value,the AUC of 3D and 2D models in the training set were 0.726-0.824 and 0.707-0.835,respectively,and those in the test set were 0.724-0.82 and 0.701-0.805.With 20%as the critical value,the AUC of 3D and 2D models in the training set were 0.743-0.868 and 0.793-0.881,respectively,and those in the test set were 0.738-0.853 and 0.743-0.814.There was no significant statistical difference between 3D and 2D models with the same parameter in the two critical values standards.Conclusion The multiparameter MRI-based radiomics models can bet-ter predict the expression of Ki-67 in breast cancer,and the models based on intratumor and peritumor 3D and 2D features have the same prediction efficiency.
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