Sigmoid model analysis of breast dynamic contrast-enhanced MRI: Distinguishing between benign and malignant breast masses and breast cancer subtype prediction.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is performed to distinguish between benign and malignant lesions by evaluating the changes in signal intensity of the acquired image (kinetic curve). This study aimed to verify whether the existing breast DCE-MRI analyzed by the sigmoid model can accurately distinguish between benign and invasive ductal carcinoma (IDC) and predict the subtype. A total of 154 patients who underwent breast MRI for detailed breast mass examinations were included in this study (38 with benign masses and 116 with IDC. The sigmoid model involved the acquisition of images at seven timepoints in 1-min intervals to determine the change in signal intensity before and after contrast injection. From this curve, the magnitude of the increase in signal intensity in the early phase, the time to reach the maximum increase, and the slopes in the early and late phases were calculated. The Mann-Whitney U-test was used for the statistical analysis. The IDC group exhibited a significantly larger and faster signal increase in the early phase and a significantly smaller rate of increase in the late phase than the benign group (P < 0.001). The luminal A-like group demonstrated a significantly longer time to reach the maximum signal increase rate than other IDC subtypes (P < 0.05). The sigmoid model analysis of breast DCE-MRI can distinguish between benign lesions and IDC and may also help in predicting luminal A-like breast cancer.