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Integrating mammographic breast density in glandular dose calculation

  • Moayyad E. Suleiman
  • , Patrick C. Brennan
  • , Ernest Ekpo
  • , Peter Kench
  • , Mark F. McEntee
  • University of Sydney

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: This work proposes the use of mammographic breast density (MBD) to estimate actual glandular dose (AGD), and assesses how AGD compares to mean glandular dose (MGD) estimated using Dance et al method. Methods: A retrospective sample of anonymised mammograms (52,405) was retrieved from a central database. Technical parameters and patient characteristics were exported from the Digital Imaging and Communication in Medicine (DICOM) header using third party software. LIBRA (Laboratory for Individualized Breast Radiodensity Assessment) software package (University of Pennsylvania, Philadelphia, USA) was used to estimate MBDs for each mammogram included in the data set. MGD was estimated using Dance et al method, while AGD was calculated by replacing Dance et al standard glandularities with LIBRA estimated MBDs. A linear regression analysis was used to assess the association between MGD and AGD, and a Bland-Altman analysis was performed to assess their mean difference. Results: The final data set included 31,097 mammograms from 7728 females. MGD, AGD, and MBD medians were 1.53 , 1.62 mGy and 8% respectively. When stratified per breast thickness ranges, median MBDs were lower than Dance's standard glandularities. There was a strong positive correlation (R2 = 0.987, p < 0.0001) between MGD and AGD although the Bland-Altman analysis revealed a small statistically significant bias of 0.087 mGy between MGD and AGD (p < 0.001). Conclusion: AGD estimated from MBD is highly correlated to MGD from Dance method, albeit the Dance method underestimates dose at smaller CBTs. Advances in knowledge: Our work should provide a stepping-stone towards an individualised dose estimation using automated clinical measures of MBD.

Original languageEnglish
Article number20180032
JournalBritish Journal of Radiology
Volume91
Issue number1085
DOIs
Publication statusPublished - 2018
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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