Impact of fibroglandular tissue distribution and breast shape in voxelized breast models for dosimetry in mammography

Objective. This work proposes to study the impact of different voxelized heterogeneous breast models (gaussian centered - Gauss(C); gaussian lower - Gauss(L); and fitted equation patient-based on 3D realistic distribution (Fedon et al 2021) - Fit(PB)) for dosimetry in mammography compared to a well-established homogeneous approximation. Influence of breast outer shape also was investigated by comparing semicylindric and anthropomorphic breasts. Approach. By using the PENELOPE (v. 2018) + penEasy (v. 2020) MC code, simulations were performed to evaluate the normalized glandular dose (DgN) and the glandular depth dose (GDD(z)) for different breast characteristics and x-ray beam spectra. Main results. The average DgN overestimation caused by homogeneous tissue approximation was 33.0%, with the highest values attributed to Gauss(L) and Fit(PB) models, where fibroglandular tissue is concentrated deeper in the breast. The observed variation between anthropomorphic and semicylindrical breast shapes was, on average, 5.6%, legitimizing the latter approximation for breast dosimetry. Thicker breasts and lower energy beams resulted in larger overestimation caused by the homogeneous approach, while variations in DgN values among different heterogeneous models were higher for thinner breast and lower energy beams. Moreover, the depth where differences between GDD(z) for different breast models became maximum depends on the axial variation of fibroglandular tissue concentration between each model. The GDD(z) dependence results in a significant variation of the contribution of each breast depth to mean glandular dose (MGD) among the breast models studied. Significance. Intercomparison between different breast models for dosimetry can be useful for estimating more accurate MGD values for population-based dosimetry, for exploring the use of 1D gaussian distribution for breast dosimetry, and for understanding the dose distributions inside the fibroglandular tissues, which could be a novel source of information for risk estimations. (AU)