Non-mass-like breast lesions at ultrasonography: Feature analysis and BI-RADS assessment. Issue 1 (January 2015) - Ko, Kai-Hsiung; Hsu, Hsian-He; Yu, Jyh-Cherng; Peng, Yi-Jen; Tung, Ho-Jui; Chu, Chi-Ming; Chang, Tsun-Hou; Chang, Wei-Chou; Wu, Yu-Cheng; Lin, Yu-Pang; Hsu, Giu-Cheng
Highlights: The positive predictive value of an NML lesion on ultrasound ranges from 10 to 79%. A sizable number of NML malignant lesions are pure DCIS or ILC. Biopsy is indicated for histopathological diagnosis when an ultrasound NML lesion is recognized. Abstract: Objective: To analyze the features of non-mass-like (NML) breast lesions on ultrasound (US) and determine their corresponding malignancy rate and to stratify these lesion patterns according to US BI-RADS categories. Materials and methods: One hundred sixty-four consecutive lesions were retrospectively classified into four types according to the US features, the corresponding positive predictive values (PPVs) were obtained. Clinical, imaging, and histopathological findings were reviewed. Results: Among the 164 lesions, 39 (24%) were classified as type Ia, 14 (8%) as type Ib, 39 (24%) as type IIa, 19 (12%) as type IIb, 19 (12%) as type III, and 34 (21%) as type IV. The PPVs for malignancy were 21% for type Ia, 79% for type Ib, 10% for type IIa, 58% for type IIb, 16% for type III, and 21% for type IV. All NML lesions were classified as BI-RADS category 4a (type IIa), 4b (type Ia, III and IV) and 4c (type Ib and IIb) according to their PPVs. There was a significantly higher frequency of malignancy among lesions of type Ib and type IIb compared with the other types ( P  < 0.01 for each). Lesions with associated calcifications, presence of abnormal axillary nodes, or a mammographic finding of suspected malignancy had a higher probability of malignancy ( P  < 0.05 for each). Conclusion: US is useful in clarifying the indication for biopsy of NML lesions. The types of US classifications used in our study establish reliable references for the NML patterns when stratified according to the BI-RADS categories.