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Introduction:This research quantifies and compares the effect of hip prostheses on dose distributions calculated using collapsed cone convolution superposition and Monte Carlo (with and without correcting for the density of the implant and surrounding tissues). The use of full volumetric modulated arc therapy arcs versus volumetric modulated arc therapy arcs avoiding the hip implants (skip arcs) was also studied.Materials and Methods:Six prostate patients with hip prostheses were included in this study. The hip prostheses and the streaking artifacts on the computed tomography images were contoured by a single physician, and full volumetric modulated arc therapy arcs were created in the Pinnacle3 TPS. Copies of each plan were made, and the doses were recalculated with the densities of the prostheses and surrounding tissues overridden. The plans were then exported to Monaco and recalculated using a Monte Carlo dose calculation algorithm, with and without densities of the prosthesis and surrounding tissues overridden.Results:With density overrides, Pinnacle3 had a 4.4% error for ion chamber measurements. Monaco was within 0.2% of ion chamber measurement when density overrides were used. On average, when density overrides were used in Pinnacle3 for patient dose calculations, the planning target volume D95 value dropped from 99.3% to 82.7%. Monaco also showed decreased planning target volume coverage when plans were recalculated with correct density information. Full arc plans (with density overrides) for the patient with a bilateral prosthesis provided significant bladder sparing and some rectal sparing compared to skip arc plans.Conclusion:When planning for prostate patients with hip prostheses, correct density information for implants and surrounding tissues should be used to optimize the plan and ensure optimal accuracy. If available, a Monte Carlo algorithm should be used as a second check. Full arcs could be used to spare dose to organs at risk, while maintaining adequate planning target volume coverage, when using a Monte Carlo dose calculation algorithm.

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