Evaluate Values of First-order Features based on Advanced DWI Models in Predicting the HER-2 Expression in Breast Invasive Ductal Cancer

In this study, we compared first-order features of six DWI models in predicting the HER-2 expression in breast invasive ductal carcinoma, including conventional mono-exponential model derived parameter ADC, IVIM derived parameters (D, Dstar, f), DKI derived parameters (D, K), SEM derived parameters (DDC, α), FROC derived parameters (D, β, mu), CTRW derived parameters (D, α, β), and a comprehensive diagnostic logistic regression model was established to improve the diagnostic performance. We found that CTRM and IVIM derived first-order features demonstrated the powerful performance, and their combination reached the highest performance. The finding has a great value in breast cancer treatment.