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Updated: May 7, 2026

Clinical Imaging of Microwave Mammography
Published on: November 14, 2025
Columnar cell lesions without atypia initially diagnosed on breast needle biopsies: is imaging follow-up enough?
Mirinae Seo1, Jung Min Chang, Won Hwa Kim
11 Department of Radiology, Seoul National University Hospital, 28, Yongon-dong, Chongno-gu, Seoul 100-744, Republic of Korea.
Objective:
The purpose of this study was to evaluate the underestimation rate and predictive factor of underestimation of columnar cell lesions (CCLs) without atypia diagnosed through breast core needle biopsies (CNBs).
Materials And Methods:
From January 2007 through December 2011, 141 CCLs without atypia, including columnar cell change and columnar cell hyperplasia, were diagnosed in 138 women by CNB. Excisional (n = 16) or imaging follow-up (n = 125) findings were available in all cases. On a per-lesion basis, the underestimation rate and predictive factor of underestimation were evaluated.
Results:
Among the 16 surgically excised lesions, there were two malignancies (one ductal carcinoma in situ and one invasive ductal carcinoma) and one lobular carcinoma in situ. Overall, the pooled underestimation rate of malignancy was 1.4% (2/141). With regard to lesion variables, the mean lesion size was significantly larger in the underestimation group of CCLs (p = 0.007). Fine pleomorphic morphology of microcalcifications (p < 0.001), the distribution of the microcalcifications (p = 0.007), BI-RADS final assessment (p = 0.001), and imaging-pathologic correlation (p < 0.001) were significantly associated with underestimation. Multivariate analysis showed that fine pleomorphic morphology of microcalcifications (p < 0.0001) was an independent predictor of underestimation in 58 lesions with microcalcifications on mammography.
Conclusion:
The overall underestimation rate of malignancy was 1.4%. Imaging follow-up is reasonable for CCLs without atypia at CNB, especially in small lesions with less suspicious imaging findings. Fine pleomorphic microcalcifications and higher BI-RADS category might be helpful in the prediction of underestimation of a high-risk lesion or malignancy.
