This Article Figures Only Full Text Full Text (PDF) Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Jeffreys, M Articles by Davey Smith, G Search for Related Content PubMed PubMed Citation Articles by Jeffreys, M Articles by Davey Smith, G

Initial experiences of using an automated volumetric measure of breast density: the standard mammogram form

¹ Centre for Public Health Research, Massey University, Private Box 756, Wellington, New Zealand, ² Addenbrooke's Hospital, Cambridge, ³ Mirada Solutions Ltd, Oxford, ⁴ Department of Social Medicine, University of Bristol, UK

Limitations of area based measures of breast density have led several research groups to develop volumetric measures of breast density, for use in predicting risk and in epidemiological research. In this paper, we describe our initial experiences using an automated algorithm (standard mammogram form, SMF) to estimate the volume of the breast that is dense from digitized film mammograms. We performed analyses on 3816 mammograms of 626 women, who were part of the Glasgow Alumni Cohort and had mammograms taken within the Scottish Breast Screening Programme between 1989 and 2002. Absolute volume of dense breast tissue (SMF volume) and the percentage of the volume of the breast that is dense (SMF%) were calculated. The median (interquartile range) of SMF volume was 66 cm³ (48 to 98), and of SMF% was 23.4% (18.6 to 29.7). SMF%, but not SMF volume, was positively related to a six category classification (SCC) of visually assigned area-based breast density (increase in ln(SMF%) per category increase in SCC: 0.04% (95%CI: 0.03–0.05). The SMF algorithm produced lower SMF volume for craniocaudal (CC) compared with mediolateral oblique (MLO) views, but CC/MLO differences for SMF% were small. The mean right/left difference for ln(SMF volume) was –0.027 cm³ (95% confidence interval (CI) –0.044 to –0.009) and of ln(SMF%) was 0.005% (95% CI –0.008% to 0.019%). We present these initial data as a background for future analytical work using SMF.

This article has been cited by other articles:

				J. Ding, R. Warren, I. Warsi, N. Day, D. Thompson, M. Brady, C. Tromans, R. Highnam, and D. Easton Evaluating the Effectiveness of Using Standard Mammogram Form to Predict Breast Cancer Risk: Case-Control Study Cancer Epidemiol. Biomarkers Prev., May 1, 2008; 17(5): 1074 - 1081. [Abstract] [Full Text] [PDF]

				V. A. McCormack, R. Highnam, N. Perry, and I. dos Santos Silva Comparison of a New and Existing Method of Mammographic Density Measurement: Intramethod Reliability and Associations with Known Risk Factors Cancer Epidemiol. Biomarkers Prev., June 1, 2007; 16(6): 1148 - 1154. [Abstract] [Full Text] [PDF]