Kai-Hsiung Ko1, Hsian-He Hsu2, Jyh-Cherng Yu3, Yi-Jen Peng4, Ho-Jui Tung5, Chi-Ming Chu6, Tsun-Hou Chang1, Wei-Chou Chang1, Yu-Cheng Wu1, Yu-Pang Lin1, Giu-Cheng Hsu1. 1. Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC. 2. Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC. Electronic address: hsianhe@yahoo.com.tw. 3. Department of Surgery, Division of General Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC. 4. Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC. 5. Department of Healthcare Administration, Asia University, Taichung, Taiwan, ROC. 6. Section of Health Informatics, Institute of Public Health, National Defense Medical Center and University, Taipei, Taiwan, ROC.
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.
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.
Authors: Jiwoon Seo; Sun Mi Kim; Mijung Jang; Bo La Yun; Soo Hyun Lee; Eun-Kyu Kim; Eunyoung Kang; So Yeon Park; Woo Kyung Moon; Hye Young Choi; Bohyoung Kim Journal: PLoS One Date: 2017-06-19 Impact factor: 3.240