The Breast Imaging Reporting And Data System: Clinical Value Of Mammographic Features And Final Assessment Categories In Microcalcification Lesions

Objective To evaluate the clinical value of mammographic features and final assessment categories described in the breast imaging reporting and data system(BI-RADS) for microcalcification lesions, and to determine the positive predictive value (PPV).Materials and Methods We prospectively evaluated 305 mammographically detected microcalcification lesions in 291 women aged 28-79 years (median age,47 years) on which wire localized biopsy was performed between January 2006 and October 2009. Diagnostic mammograms obtained before biopsy were analyzed by 2-3 radiologists. Each lesion was classified according to BI-RADS descriptors for calcification (morphology and distribution) and was categorized by the BI-RADS final assessment categories as category 2(benign), category 3 (probably benign), category 4 (suspicious abnormality), or category 5 (highly suggestive of malignancy). Mammographic and pathologic findings were reviewed.Results 1. The 305 localizations yielded 100 cancers (31 were ductal carcinoma in situ (DCIS),12 were DCIS with focal invasion,57 were invasive ductal carcinoma). The positive predictive value (PPV) of wire localized biopsy for malignancy was 32.79%.2. There were 34 category 2 lesions, the PPV was 0%. There were 65 category 3 lesions, the PPV was 4.62%(3/62). There were 152 category 4 lesions, the PPV was 30.92%(47/152). There were 54 category 5 lesions, the PPV was 92.59%(50/54). The categories 4 and 5 had a higher PPV than the category 3 (P<0.001).3. Each calcification morphologic descriptor was able to help stratify the probability of malignancy as follows:coarse heterogeneous, two (6.25%) of 32; amorphous,12 (20.34%) of 59; fine pleomorphic,68 (54.84%) of 124; and fine linear, 16 (94.12%) of 17. Fisher exact test results revealed a significant difference among these descriptor categories (P<0.001).4. The PPV of each calcification distribution descriptor was as follows:segmental 78.75%, linear 50%, clustered 32.43%, regional 21.62%, and scattered 6.25%(P<0.001).5. Combination of the morphologic and the distribution descriptors can also help to suggest malignancy risk.CONCLUSION 1. BI-RADS categorization for breast microcalcification lesions can help predict the risk of malignancy and help decision-making for biopsy.2. The microcalcification morphologic and distribution descriptors in BI-RADS can help predict the risk of malignancy for suspicious microcalcifications.