Prediction of the presence of invasive disease from the measurement of extent of malignant microcalcification on mammography and ductal carcinoma in situ grade at core biopsy

• Published in: Clinical radiology 2009-02, Vol.64 (2), p.178-183
• Main Authors: O'Flynn, E.A.M, Morel, J.C, Gonzalez, J, Dutt, N, Evans, D, Wasan, R, Michell, M.J
• Format: Article
• Language: English
• Subjects: Biological and medical sciences; Biopsy; Breast Neoplasms - diagnostic imaging; Breast Neoplasms - pathology; Calcinosis - diagnostic imaging; Carcinoma, Intraductal, Noninfiltrating - diagnostic imaging; Carcinoma, Intraductal, Noninfiltrating - pathology; Carcinoma, Intraductal, Noninfiltrating - secondary; Epidemiologic Methods; Female; Genital system. Mammary gland; Humans; Investigative techniques, diagnostic techniques (general aspects); Lymphatic Metastasis; Mammography; Medical sciences; Neoplasm Invasiveness; Prognosis; Radiodiagnosis. Nmr imagery. Nmr spectrometry; Radiology
• ISSN: 0009-9260; 1365-229X
• DOI: 10.1016/j.crad.2008.08.007

Aim To determine whether the extent of microcalcification and ductal carcinoma in situ (DCIS) grade can be used to accurately predict the presence and size of invasive cancer in cases of malignant microcalcification. Materials and methods Over a 10-year period, 402 cases of malignant microcalcification from an NHS screening programme were analysed. For each case, measurement of mammographic microcalcification extent, DCIS grade, and the presence and size of invasive carcinoma from the excised surgical specimen were recorded. Results The final histological diagnosis was DCIS only in 71% (284/402) and DCIS with a focus of invasive disease in 29% (118/402). The risk of invasive disease increased with increasing size of microcalcification from 20% (27/136) for cluster size less than 11 mm, to 45% (18/40) for cluster size more than 60 mm. The risk of invasive disease also increased with increasing histological grade of DCIS from 13% (4/31) with low-grade DCIS to 36% (86/239) with high-grade DCIS. There were significant associations with the presence of invasive disease for cluster size ( p = 0.0001) and DCIS grade ( p = 0.003), and when using univariate analysis with simple [cluster size ( p = 0.01) and grade ( p = 0.01)] and multiple [cluster size ( p = 0.02) and grade (p = 0.02)] logistic regression, respectively. The Hosmer–Lemeshow goodness-of-fit test suggests that the multiple logistic regression model has a good fit ( p = 0.99). Conclusion The multidisciplinary team can use these data in individual cases to estimate the risk of invasive cancer and decide whether to carry out an axillary staging procedure.