Abstract

To speed-up the absorbed dose (AD) computation while accounting for tissue heterogeneities, a Collapsed Cone (CC) superposition algorithm was developed and validated for 90Y. The superposition was implemented with an Energy Deposition Kernel scaled with the radiological distance, along with CC acceleration. The validation relative to Monte Carlo simulations was performed on 6 phantoms involving soft tissue, lung and bone, a radioembolisation treatment and a simulated bone metastasis treatment. As a figure of merit, the relative AD difference (ΔAD) in low gradient regions (LGR), distance to agreement (DTA) in high gradient regions and the γ(1%,1 mm) criterion were used for the phantoms. Mean organ doses and γ(3%,3 mm) were used for the patient data. For the semi-infinite sources, ΔAD in LGR was below 1%. DTA was below 0.6 mm. All profiles verified the γ(1%,1 mm) criterion. For both clinical cases, mean doses differed by less than 1% for the considered organs and all profiles verified the γ(3%,3 mm). The calculation time was below 4 min on a single processor for CC superposition and 40 h on a 40 nodes cluster for MCNP (108 histories). Our results show that the CC superposition is a very promising alternative to MC for 90Y dosimetry, while significantly reducing computation time.

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