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