The EPIC-Norfolk Study
Mammographic density using two computer-based methods in an isoflavone trial.
Maturitas 2007 ; 59: 350-7.
Kataoka M, Atkinson C, Warren R, Sala E, Day NE, Highnam R, Warsi I, and Bingham SA
DOI : 10.1016/j.maturitas.2008.03.005
PubMed ID : 18495387
PMCID :
URL : https://linkinghub.elsevier.com/retrieve/pii/S0378512208001023
Abstract
Mammographic density is a useful biomarker of breast cancer risk. Computer-based methods can provide continuous data suitable for analysis. This study aimed to compare a semi-automated computer-assisted method (Cumulus) and a fully automated volumetric computer method (standard mammogram form (SMF)) for assessing mammographic density using data from a previously conducted randomised placebo-controlled trial of an isoflavone supplement.
Mammograms were obtained from participants in the intervention study. A total of 177 women completed the study. Baseline and follow-up mammograms were digitised and density was estimated using Cumulus (read by two readers) and SMF. Left-right correlation, changes in density over time, and difference between intervention and control groups were evaluated. Changes of density over time, and changes between intervention group and control group were examined using paired t-test and Student's t-test, respectively.
Inter-reader correlation coefficient by Cumulus was 0.90 for dense area, and 0.86 for percentage density. Left-right correlation of percent density was lower in SMF than in Cumulus. Among all women, percentage density by Cumulus decreased significantly over time, but no change was seen for SMF percentage density. The intervention group showed marginally significant greater reduction of percent density by Cumulus compared to controls (p=0.04), but the difference became weak after adjustment for baseline percent density (p=0.06). No other measurement demonstrated significant difference between intervention and control groups.
This comparison suggests that slightly different conclusions could be drawn from different methods used to assess breast density. The development of a more robust fully automated method is awaited.