Impact of photoelectric cross section data on systematic uncertainties for Monte Carlo breast dosimetry in mammography

Abstract

Monte Carlo (MC) simulations are employed extensively in breast dosimetry studies. In the energy interval of interest in mammography energy deposition is predominantly caused by the photoelectric effect, and the corresponding cross sections used by the MC codes to model this interaction process have a direct influence on the simulation results. The present work compares two photoelectric cross section databases in order to estimate the systematic uncertainty, related to breast dosimetry, introduced by the choice of cross sections for photoabsorption. The databases with and without the so-called normalization screening correction are denoted as ‘renormalized’ or ‘un-normalized’, respectively. The simulations were performed with the PENELOPE/penEasy code system, for a geometry resembling a mammography examination. The mean glandular dose (MGD), incident air kerma (K air), normalized glandular dose (DgN) and glandular depth-dose (GDD(z)) were scored, for homogeneous breast phantoms, using both databases. The AAPM Report TG-195 case 3 was replicated, and the results were included. Moreover, cases with heterogeneous and anthropomorphic breast phantoms were also addressed. The results simulated with the un-normalized cross sections are in better overall agreement with the TG-195 data than those from the renormalized cross sections; for MGD the largest discrepancies are 0.13(6)% and 0.74(5)%, respectively. The MGD, K air and DgN values simulated with the two databases show differences that diminish from approximately 10%/3%/6.8% at 8.25 keV down to 1.5%/1.7%/0.4% at 48.75 keV, respectively. For polyenergetic spectra, deviations up to 2.5% were observed. The disagreement between the GDDs simulated with the analyzed databases increases with depth, ranging from −1% near the breast entrance to 4% near the bottom. Thus, the choice of photoelectric cross section database affects the MC simulation results of breast dosimetry and adds a non-negligible systematic uncertainty to the dosimetric quantities used in mammography.