The optimal biomarkers for the diagnosis of breast lymphovascular invasion have not yet been found. DCE-MRI features can evaluate the tumor microenvironment which is related to LVI. This study explored the independent predictor of LVI, as well as developed and validated the parametric combined prediction model for the diagnosis of lymphovascular invasion in breast cancer using quantitative analysis of DCE-MRI. The prediction model based on Kep and N stage could improve the performance of LVI prediction, compared to clinicopathological or magnetic resonance parameters.
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