Validation of the dosimetry of total skin irradiation techniques by Monte Carlo simulation

摘要

Purpose To validate the dose measurements for two total skin irradiation techniques with Monte Carlo simulation, providing more information on dose distributions, and guidance on further technique optimization. Methods Two total skin irradiation techniques (stand‐up and lay‐down) with different setup were simulated and validated. The Monte Carlo simulation was primarily performed within the EGSnrc environment. Parameters of jaws, MLCs, and a customized copper (Cu) filter were first tuned to match the profiles and output measured at source‐to‐skin distance (SSD) of 100?cm where the secondary source is defined. The secondary source was rotated to simulate gantry rotation. VirtuaLinac, a cloud‐based Monte Carlo package, was used for Linac head simulation as a secondary validation. The following quantities were compared with measurements: for each field/direction at the treatment SSDs, the percent depth dose (PDD), the profiles at the depth of maximum, and the absolute dosimetric output; the composite dose distribution on cylindrical phantoms of 20 to 40?cm diameters. Results Cu filter broadened the FWHM of the electron beam by 44% and degraded the mean energy by 0.7?MeV. At SSD?=?100?cm, MC calculated PDDs agreed with measured data within 2%/2?mm (except for the surface voxel) and lateral profiles agreed within 3%. At the treatment SSD, profiles and output factors of individual field matched within 4%; dmax and R80 of the simulated PDDs also matched with measurement within 2?mm. When all fields were combined on the cylindrical phantom, the dmax shifted toward the surface. For lay‐down technique, the maximum x‐ray contamination at the central axis was (MC: 2.2; Measurement: 2.1)% and reduced to 0.2% at 40?cm off the central axis. Conclusions The Monte Carlo results in general agree well with the measurement, which provides support in our commissioning procedure, as well as the full three‐dimensional dose distribution of the patient phantom.