Updated breast CT dose coefficients (DgN CT ) using patient-derived breast shapes and heterogeneous fibroglandular distributions.

Purpose The purpose of this work was to generate uncompressed heterogeneous breast phantom models using size-dependent fibroglandular distributions derived from a large cohort of breast CT (bCT) datasets, and to compare differences in normalized glandular dose coefficients for bCT "DgN(CT)" when the realistic heterogeneous model is considered relative to the simple, homogeneous model used in the past. Methods A cohort of 274 segmented bCT datasets were used to quantify the fibroglandular tissue distribution within the breast parenchyma. Each dataset was interpolated to an isotropic voxel size of 0.25 mm and the breast center-of-mass was aligned for all coronal slices. Each aligned dataset was converted into two binarized volumes representing voxels containing only glandular tissue "G(x,y,z)" and voxels containing glandular or adipose tissue "AG(x,y,z)". The datasets were classified by volume in accordance with previously reported size-dependent, breast-shaped phantoms. Within the five groups - each containing on average 55 datasets, all G(x,y,z) and AG(x,y,z) volumes were summed separately representing the cumulative distribution of glandular tissue or breast parenchyma (glandular + adipose), respectively. G(x,y,z) was divided by AG(x,y,z) on a voxel-by-voxel basis resulting in a glandular fraction "GF(x,y,z)" distribution for each phantom size. The GF(x,y,z) distributions were used to construct heterogeneous mathematical phantoms for the small, median, and large breast sizes with a 1.5 mm skin thickness - based on previously reported measurements from bCT, and a 5 mm skin thickness for comparison with outdated assumptions of skin thickness. A subset of 15 bCT datasets from the cohort (five for each breast size) were used to construct voxelized patient models for validation of the heterogeneous phantom models. Monte Carlo techniques were used to estimate monoenergetic DgN(E)(CT) values for photon energies from 9 to 70 keV (in 1 keV intervals) using the mathematical phantoms composed of either heterogeneous or homogeneous breast parenchyma. Polyenergetic (pDgN(CT)) coefficients were determined by weighting the DgN(E)(CT) values by x-ray spectra tuned to the beam characteristic of breast CT. Dose coefficients were compared between the two breast compositions for each volume class, breast density, and skin thickness. Results For photon energies less than or similar to 45 keV, the homogeneous model overestimates DgN(E) values relative to the realistic heterogeneous model sorted into five volume classes. The 5 mm skin thickness underestimates DgN(E) values relative to the realistic 1.5 mm thickness for lower energies and the differences diminish up to 70 keV. Averaged across all phantom sizes the homogeneous model overestimates pDgN(CT) by 5.7% and 23.3% for the 60 kV W/Cu and 49 kV W/Al spectra, respectively. The heterogeneous model was also found to be in agreement with the voxelized bCT patient models with pDgN(CT) differences less than 2.3% and 5.2% for the 60 kV W/Cu and 49 kV W/Al spectra, respectively, across all phantom sizes. Conclusion Anatomically accurate heterogeneous phantom models were developed using bCT image-derived fibroglandular tissue distributions. These new models improve the accuracy of bCT dosimetry, and in conjunction with previous models for mammography, may help in providing a more universally accepted breast dosimetry model.