Textural analysis of contrast-enhanced MR images of the breast

Texture analysis was applied to high-resolution, contrast-enhanced (CE) images of the breast to provide a method of lesion discrimination. Significant differences were seen between benign and malignant lesions for a number of textural features, including entropy and sum entropy. Using logistic regression analysis (LRA), a diagnostic accuracy of A(z) = 0.80 +/- 0.07 was obtained with a model requiring only three parameters. By initially dividing the patient data into training and test datasets, reasonable model robustness was also established. On combining features obtained using textural analysis with lesion size, time to maximum enhancement, and patient age, a diagnostic accuracy of A(z) = 0.92 +/- 0.05 was demonstrated.