To investigate the value of MRI in the differential diagnosis of breast masses with a maximum diameter ≤1 cm.

This retrospective study reviewed the preoperative MRI findings of 160 patients with small breast masses in the Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University between September 2012 and December 2018. There were 49 patients with malignant lesions and 111 patients with benign lesions. The mass location, morphological features, time-signal intensity curve (TIC), T2-weighted image features(T2WI) and apparent diffusion coefficient (ADC) of the masses were compared. Student’s t test was used to compare patient age between two groups. The Mann-Whitney U test was employed to compare lesion size and ADC value between two groups. The count data (mass location, surrounding fat sign, shape, margin, internal enhancement and TIC type) were compared by χ² test. The variables like proportion of concurrent contralateral cancer and T2WI features were compared by Fisher exact test. The pairwise comparison in the subgroups was adjusted by Bonferroni. Receiver operating characteristic (ROC) curve of the age and ADC value was drawn. A binary logistic regression was performed for multivariate analysis using the " Forward: LR" method to establish a diagnostic model for benign and malignant diseases. The area under the ROC curve (AUC), sensitivity, specificity, positive predictive value, negative predictive value and accuracy rate of this model were calculated. The nomogram of the model was plotted.

(1) Univariate analysis showed that there were significant differences in surrounding fat sign, margin of mass, internal enhancement, TIC type, T2-weighted image features and ADC values between the benign group and malignant group (χ²=13.083, 11.224, 7.628, 14.060, 21.892; P<0.001, 0.004, 0.006, 0.001, <0.001; Z=-3.952, P<0.001). (2) Multivariate analysis showed that age>50 years old, positive peripheral fat sign, slightly hypointense or peripheral hyperintense signal on T2-weighted images, and ADC value ≤1.22×10^-3 mm²/s were independent risk factors for malignancy (OR=6.728, 95%CI: 2.123~21.318, P=0.001; OR=5.545, 95%CI: 1.306~23.533, P=0.020; OR=31.110, 95%CI: 2.167~446.576, P=0.011; OR=13.794, 95%CI: 2.096~90.790, P=0.006; OR=5.802, 95%CI: 1.350~24.938, P=0.018). (3) Differential diagnosis model: The sensitivity, specificity, positive predictive value, negative predictive value and accuracy rate of the diagnostic model combining the above-mentioned characteristics for the differential diagnosis of small breast masses was 89.2%(33/37), 69.4%(59/85), 55.9%(33/59), 93.6%(59/63) and 75.4%(92/122), respectively.

Benign and malignant small breast masses overlap a lot in MRI features. It is challenging to make a differential diagnosis based on single feature. The combination of age, surrounding fat sign, T2-weighted image features and ADC values helps to increase the accuracy of diagnosis.