Patient-specific Monte Carlo dose calculations for 103Pd breast brachytherapy

Abstract

This work retrospectively investigates patient-specific Monte Carlo (MC) dose calculations for 103Pd permanent implant breast brachytherapy, exploring various necessary assumptions for deriving virtual patient models: post-implant CT image metallic artifact reduction (MAR), tissue assignment schemes (TAS), and elemental tissue compositions. Three MAR methods (thresholding, 3D median filter, virtual sinogram) are applied to CT images; resulting images are compared to each other and to uncorrected images. Virtual patient models are then derived by application of different TAS ranging from TG-186 basic recommendations (mixed adipose and gland tissue at uniform literature-derived density) to detailed schemes (segmented adipose and gland with CT-derived densities). For detailed schemes, alternate mass density segmentation thresholds between adipose and gland are considered. Several literature-derived elemental compositions for adipose, gland and skin are compared. MC models derived from uncorrected CT images can yield large errors in dose calculations especially when used with detailed TAS. Differences in MAR method result in large differences in local doses when variations in CT number cause differences in tissue assignment. Between different MAR models (same TAS), PTV and skin each vary by up to 6%. Basic TAS (mixed adipose/gland tissue) generally yield higher dose metrics than detailed segmented schemes: PTV and skin are higher by up to 13% and 9% respectively. Employing alternate adipose, gland and skin elemental compositions can cause variations in PTV of up to 11% and skin of up to 30%. Overall, AAPM TG-43 overestimates dose to the PTV ( on average 10% and up to 27%) and underestimates dose to the skin ( on average 29% and up to 48%) compared to the various MC models derived using the post-MAR CT images studied herein. The considerable differences between TG-43 and MC models underline the importance of patient-specific MC dose calculations for permanent implant breast brachytherapy. Further, the sensitivity of these MC dose calculations due to necessary assumptions illustrates the importance of developing a consensus modelling approach.