318 patients (331 breast lesions) with DCE-MRI and clinical features were analyzed to establish a nomogram for diagnosis of breast cancer. The dataset was split to 233 (145 malignant 88 benign) for training, and 98 (61 malignant 37 benign) for testing. Radiomics features were extracted from DCE-MRI and selected to calculate the radiomics score. The clinical features were analyzed by univariate and multivariate analyses. Then a nomogram was established based on clinical features and rad-score. When applying cut-off values with ≥95% sensitivity, the nomogram can reduce 59.5% to 65.9% unnecessary biopsies, which was higher than that of BI-RADS.
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