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. 2017 Feb;162(1):95-103.
doi: 10.1007/s10549-016-4090-7. Epub 2016 Dec 23.

Volumetric breast density affects performance of digital screening mammography

Johanna O P Wanders  1 , Katharina Holland  2 , Wouter B Veldhuis  3 , Ritse M Mann  2 , Ruud M Pijnappel  3   4 , Petra H M Peeters  1   5 , Carla H van Gils  6 , Nico Karssemeijer  2
Affiliations

Volumetric breast density affects performance of digital screening mammography

Johanna O P Wanders et al. Breast Cancer Res Treat. 2017 Feb.

Abstract

Purpose: To determine to what extent automatically measured volumetric mammographic density influences screening performance when using digital mammography (DM).

Methods: We collected a consecutive series of 111,898 DM examinations (2003-2011) from one screening unit of the Dutch biennial screening program (age 50-75 years). Volumetric mammographic density was automatically assessed using Volpara. We determined screening performance measures for four density categories comparable to the American College of Radiology (ACR) breast density categories.

Results: Of all the examinations, 21.6% were categorized as density category 1 ('almost entirely fatty') and 41.5, 28.9, and 8.0% as category 2-4 ('extremely dense'), respectively. We identified 667 screen-detected and 234 interval cancers. Interval cancer rates were 0.7, 1.9, 2.9, and 4.4‰ and false positive rates were 11.2, 15.1, 18.2, and 23.8‰ for categories 1-4, respectively (both p-trend < 0.001). The screening sensitivity, calculated as the proportion of screen-detected among the total of screen-detected and interval tumors, was lower in higher density categories: 85.7, 77.6, 69.5, and 61.0% for categories 1-4, respectively (p-trend < 0.001).

Conclusions: Volumetric mammographic density, automatically measured on digital mammograms, impacts screening performance measures along the same patterns as established with ACR breast density categories. Since measuring breast density fully automatically has much higher reproducibility than visual assessment, this automatic method could help with implementing density-based supplemental screening.

Keywords: Breast; Breast cancer; Cancer screening; Mammographic density; Mammography.

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Conflict of interest statement

J. Wanders, K. Holland, R. Mann, P. Peeters, C. van Gils, and N. Karssemeijer report all the same grant from the European Union’s Seventh Framework Programme (FP7), during the conduct of the study. N. Karssemeijer also reports to be one of the co-founders of Volpara Solutions, who develops and markets the breast density measurement software Volpara used in this study. In addition, N. Karssemeijer has a patent pending and is co-founder of two other companies in the field of breast imaging next to his position as professor in the University. The two companies are Qview Medical (Los, Altos, CA) and ScreenPoint Medical (Nijmegen, NL). These companies develop products for computer-aided detection of breast cancer, in whole-breast ultrasound and in mammography, respectively. C. van Gils also reports a personal grant from the Dutch Cancer Society, during the conduct of the study and a grant from Bayer Healthcare, and non-financial support from Volpara Solutions outside the submitted work. In addition, R. Mann reports grants, personal fees, and non-financial support from Siemens Healthcare and grants and personal fees from Bayer Healthcare outside the submitted work. R. Mann also reports a research contract with Seno Medical, and he reports to be a scientific advisor for ScreenPoint Medical (Nijmegen, NL) outside the submitted work. W. Veldhuis and R. Pijnappel have nothing to disclose. Ethical standards The authors declare that this study complies with the current laws in The Netherlands.

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