Abstract
This study evaluates the implementation of volumetric‐modulated arc therapy (VMAT) using multicriteria optimization (MCO) in the RayStation treatment planning system (TPS) for complex sites, namely extremity and body sarcoma. The VMAT‐MCO algorithm implemented in RayStation is newly developed and requires an integrated, comprehensive analysis of plan generation, delivery, and treatment efficiency. Ten patients previously treated by intensity‐modulated radiation therapy (IMRT) with MCO were randomly selected and replanned using VMAT‐MCO. The plan quality was compared using homogeneity index (HI) and conformity index (CI) of the planning target volume (PTV) and dose sparing of organs at risk (OARs). Given the diversity of the tumor location, the 10 plans did not have a common OAR except for skin. The skin D50 and Dmean was directly compared between VMAT‐MCO and IMRT‐MCO. Additional OAR dose points were compared on a plan‐by‐plan basis. The treatment efficiency was compared using plan monitor units (MU) and net beam‐on time. Plan quality assurance was performed using the Sun Nuclear ArcCHECK phantom and a gamma criteria of 3%/3 mm. No statistically significant differences were found between VMAT‐ and IMRT‐MCO for HI and CI of the PTV or D50 and Dmean to the skin. The VMAT‐MCO plans showed general improvements in sparing to OARs. The VMAT‐MCO plan set showed statistically significant improvements over the IMRT‐MCO set in treatment efficiency per plan MU (p<0.05) and net beam‐on time (p<0.01). The VMAT‐MCO plan deliverability was validated. Similar gamma passing rates were observed for the two modalities. This study verifies the suitability of VMAT‐MCO for sarcoma cancer and highlighted the comparability in plan quality and improvement in treatment efficiency offered by VMAT‐MCO as compared to IMRT‐MCO.PACS number(s): separated by commas 87.55.D, 87.55.de, 87.55.Qr
Highlights
Young et al.: volumetric-modulated arc therapy (VMAT) using multicriteria optimization (MCO) for sarcomaVMAT involves dynamic gantry movement, which requires accurate synchronization of all moving components.(1) The decreased treatment time, potential increased organs at risk (OARs) dose sparing, and optimization of monitor units (MUs) afforded by VMAT over intensity-modulated radiation therapy (IMRT) planning(2) makes it ideal for clinical implementation.VMAT planning is currently available in several commercial treatment planning systems (TPS), including Pinnacle SmartArc (Philips, Inc., Andover, MA), Monaco (Elekta, Inc., Stockholm, Sweden), Eclipse (Varian Medical Systems, Inc., Palo Alto, CA), and RayStation (RaySearch Laboratories, Stockholm, Sweden)
In this study we focused on VMAT planning in RayStation, a TPS popularized by its development and implementation of multicriteria optimization (MCO)
All 10 VMAT-MCO generated treatments met physician-imposed planning target volume (PTV) coverage (100% of the PTV receiving more than 95% of prescription dose) and plan-specific OAR dose-sparing constraints
Summary
Young et al.: VMAT using MCO for sarcomaVMAT involves dynamic gantry movement, which requires accurate synchronization of all moving components.(1) The decreased treatment time, potential increased OAR dose sparing, and optimization of monitor units (MUs) afforded by VMAT over IMRT planning(2) makes it ideal for clinical implementation.VMAT planning is currently available in several commercial treatment planning systems (TPS), including Pinnacle SmartArc (Philips, Inc., Andover, MA), Monaco (Elekta, Inc., Stockholm, Sweden), Eclipse (Varian Medical Systems, Inc., Palo Alto, CA), and RayStation (RaySearch Laboratories, Stockholm, Sweden). VMAT involves dynamic gantry movement, which requires accurate synchronization of all moving components.(1) The decreased treatment time, potential increased OAR dose sparing, and optimization of monitor units (MUs) afforded by VMAT over IMRT planning(2) makes it ideal for clinical implementation. In this study we focused on VMAT planning in RayStation, a TPS popularized by its development and implementation of multicriteria optimization (MCO). The MCO algorithm increases IMRT plan quality by allowing planners to better approach an optimal plan by interactively balancing several treatment objectives and constraints.(3) Planners and physicians navigate highdimensional Pareto surfaces and weigh trade-offs between objectives in real time to improve planning and plan quality. The mathematics and utility of MCO are elucidated in greater detail by Craft and Bortfeld(4) and recent studies suggest dosimetric and efficiency advantages of MCO in generating optimal IMRT treatment plans.(5)
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