Apparent Diffusion Coefficient to Subdivide Breast Imaging Reporting and Data System Magnetic Resonance Imaging (BI-RADS-MRI) Category 4 Lesions.

BACKGROUND This study aims to subdivide BI-RADS-MRI (Breast Imaging Reporting and Data System Magnetic Resonance Imaging) Category 4 lesions and to evaluate the role of Fischer's scoring system, apparent diffusion coefficient (ADC), and Fischer's + ADC in differential diagnosis of breast lesions. MATERIAL AND METHODS This study retrospectively analyzed the data of 143 patients (150 breast lesions), who were diagnosed by biopsy, and received dynamic contrast enhancement and diffusion-weighted imaging. The diagnostic efficacies of ADC, Fischer's scoring system, and the Fischer's + ADC were analyzed by the receiver operating characteristics curve. The area under the curve (AUC) was calculated. Fischer's scoring system and the Fischer's + ADC were used to subdivide BI-RADS Category 4 breast lesions. RESULTS ADC value was negatively correlated with the tumor grade. The AUC of Fischer's + ADC (0.949) was significantly higher than that of ADC (0.855) and Fischer's (0.912) (P=0.0008 and 0.001, respectively). Scored by Fischer's scoring system, Category 4 and 5 indicated a likely malignant threshold with sensitivity and specificity of 98.70% and 65.75%, respectively. Scored by the Fischer's + ADC method, Category 4B and 4C indicated a likely malignant threshold with sensitivity of 97.40% and specificity of 82.19%. Kappa values were 0.63 (ADC), 0.65 (Fischer's), and 0.80 (Fischer's + ADC), respectively. The positive predictive value of BI-RADS 4A, 4B, and 4C were 7.69%, 52.38% and 89.29%, respectively. CONCLUSIONS Fischer's scoring system combined with ADC could reasonably subdivide Category 4 breast lesions with high specificity and sensitivity.