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  • Poster presentation
  • Open Access

PB.35. How does semi-automated computer-derived CT measure of breast density compare with subjective assessments to measure mean glandular breast density in patients with breast cancer?

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Breast Cancer Research201416 (Suppl 1) :P19

  • Published:


  • Breast Cancer
  • Compute Tomography
  • Breast Cancer Patient
  • Density Measurement
  • Subjective Assessment


The objectives were to compare radiologists' breast mammographic density readings with computed tomography (CT) subjective measures; and to correlate computer-derived measurement of CT density with subjective assessments.


Retrospective review of mammograms and CT scans in 77 breast cancer patients obtained within 1 year of each other was performed. Two radiologists independently reviewed both CT and mammograms and classified each case into four categories as defined by the Breast Imaging, Reporting and Data system of the American College of Radiology. Inter-reader agreements were obtained for both mammographic and CT density subjective evaluations by using the Cohen weighted k statistic. Correlation was also sought between subjective CT density measurement and mammographic density measurements for each reader using Spearman correlation coefficient. The semi-automated computer-derived measurement of breast density was correlated with visual measurements.


Inter-reader agreements was lower for subjective CT density grades than for mammographic readings, 0.428 (CI: 0.24 to 0.89) versus 0.571 (CI 0.35 to 0.76), respectively. There was moderately good correlation between subjective CT density grades and the mammographic density grades for both readers (0.760, Reader 1; 0.913, Reader 2). The semi-automated CT density measurement correlated well with the subjective assessments, with complete agreement of the density grades in 84.9% of patients and only one-level difference in the rest.


Semi-automated CT density measurements in the evaluation of breast density correlated well with subjective mammographic density measurement. Further studies are needed to incorporate this extra information from a CT scan in the risk stratification of patients.

Authors’ Affiliations

University Hospital Llandough, Penarth, UK


© Bansal and Yapa; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.