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Retrospective Determination of Personalized Mean Glandular Dose Coefficients for Conventional Mammography Using Heterogeneously-Layered Breast Models


M Porras-Chaverri

M Porras-Chaverri1 2, J Vetter1, R Highnam3, (1) Department of Medical Physics, University of Wisconsin-Madison, Madison, WI. (2) School of Physics, University of Costa Rica, San Jose, Costa Rica. (3) Matakina Technology Limited, Wellington, New Zealand.

WE-G-103-8 Wednesday 4:30PM - 6:00PM Room: 103

Purpose: The heterogeneous distribution of the glandular tissue is overlooked in calculations of mean glandular dose (MGD). In this work, we introduce a methodology for the calculation of patient-oriented dose conversion coefficients. In addition, we provide an empirical relationship to use for the estimation of these coefficients in a clinical setting.

Methods: Breast density assessment software was used to obtain the breast density maps from conventional mammography four-view sets of images in a group of 31 patients. The glandular tissue distribution for each breast was estimated from the breast density maps using the Mammography-Image Based (MIB) method presented in this work. The corresponding patient-oriented dose conversion coefficients (DgN-HLB) were determined using Monte Carlo methods and a Heterogeneously-Layered Breast (HLB) geometry. This geometry models the breast core as composed of layers with different glandular percentage, as opposed to a homogeneous breast core.
The DgN-HLB were compared to the corresponding dose conversion coefficients based on a homogeneous core breast geometry (DgN).

Results: Differences as high as 49% between the DgN-HLB and their corresponding DgN were found. The difference between DgN and DgN-HLB was found to have a linear relationship with the glandular distribution index (I_dist) calculated in this work. This relationship was used to make a patient-specific correction to the DgN (k_dist) that allows for estimations of DgN-HLB, without the use of patient-based Monte Carlo simulations. Both HLB-based approaches agree within 10.5%.

Conclusion: We have developed a method to obtain estimations of the glandular tissue distribution from conventional mammography images using their corresponding breast density maps. Our work provides a methodology to incorporate anatomical information in the calculation of patient-oriented MGD, thereby overcoming one of the known limitations of the currently used mammography dosimetry methods.

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