Treatment Planning System Modelling of a New Commercial Rotational Table ๐Ÿ“

Author: Michael Armstrong, Courtney R. Buckey, Quan Chen, Suzanne J. Chungbin, Mirek Fatyga, Yi Rong, Jun Tan, Xiang Sheng Yan ๐Ÿ‘จโ€๐Ÿ”ฌ

Affiliation: Mayo Clinic Arizona, Mayo Clinic ๐ŸŒ

Abstract:

Purpose: To model a commercial rotational table in treatment planning system (TPS) for accurate dose optimization and calculation.

Methods: A commercial rotational table (CDR Equilibriumยฎ) is recently available in the US for volumetric modulated arc therapy for total body irradiation (VMAT-TBI) and multi-isocenter planned patient for efficient treatment delivery. Attenuation under 6X and 10X beams were measured at various gantry angles using a centrally placed ion chamber. Table parts with and without the base plate were measured to model the HU values for the base plate and the tabletop, and to define details of the table. The model is then used for VMAT-TBI treatment planning. The impact on Gamma passing rate with and without model was evaluated using ArcCheck on five different cases.

Results: The high density of the base plate at the central part of the rotational table introduces 8.6%-24.6% attenuation. A total of 11 components of the table were identified and contoured from the CT scan and their HU # are empirically modeled. The empirical HU # for tabletop is โ€“650 and resulted in โ€“0.6% and โ€“0.1% difference between measured and calculated attenuation for 6X and 10X. Empirical HU # for base plate is 2600 and resulted in โ€“0.3% and 0.0% difference for 6X and 10X.
Gamma (3%, 2mm, >10% threshold dose) passing rate increased from 72.6% ยฑ 11.1% to 99.4% ยฑ 0.6% after the table model was used for dose calculation, which validated the HU # accuracy modelled for this table.

Conclusion: The CDR rotational table was successfully modelled in the TPS for accurate dose optimization and calculation. The model is shown to significantly improve the gamma passing rate of VMAT-TBI plans, indicating the importance of accurate table modelling. The TPS model will be uploaded to GitHub for public access.

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