S1823
Physics - Dose prediction/calculation, optimisation and applications for photon and electron planning
ESTRO 2026
Oncol. 2021 Mar-Apr;11(2):e236-e244. Keywords: Automated planning, Model transferability
was preferred in 9/10 patients, mainly for lower organ doses.
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Implementation and evaluation of Halcyon treatment planning: A retrospective audit Molly Munro, Miranda Frizzelle, Narinder Lalli, Tom Williams Radiotherapy Physics, University College London Hospital, London, United Kingdom Purpose/Objective: Due to increasing patient numbers, an additional radiotherapy treatment machine was purchased, and in March 2025 a Varian Halcyon linear accelerator was commissioned to complement the department’s four existing TrueBeam machines. In conjunction with the new Halcyon, planning practice was updated to utilise the Monte Carlo based AcurosXB algorithm for dose calculation [1]. During the clinical rollout, a retrospective audit was conducted to evaluate the suitability of Halcyon planning using AcurosXB compared with the existing TrueBeam and AAA algorithm combination [2]. Plan quality was assessed using parameters including plan modulation, conformity, organ-at-risk (OAR) doses, and patient- specific quality assurance (QA). Material/Methods: A total of 35 patients were included in the audit, representing a mix of gynaecological and urological sites. All plans were generated in Varian Eclipse v16.1.0 according to departmental practice. Approaches and differences in generating Halcyon and TrueBeam plans are outlined in Figure 1. Halcyon plans were created with AcurosXB, and corresponding TrueBeam equivalent plans were produced with AAA for comparison.With the updated algorithm, a new method of overriding gas within the planning target volume (PTV) was required during implementation [3]. For a subset of patients, duplicate plans were created and re-optimised with and without gas overrides to evaluate the impact on plan robustness. The department’s knowledge-based automated planning system, RapidPlan, was also assessed by applying existing TrueBeam models to Halcyon plans to test their applicability and performance [4].
MU and 2D gamma passing rates were comparable to clinical plans. An optimal plan was obtained in a single iteration, with total planning time below 8 minutes.In the external validation cohort, RP_MCO plans were comparable to clinical plans in terms of dose to organs of interest and showed a statistically improved (p<0.05) target coverage, supporting reduced inter- planner variability and consistent plan quality across centres. Similar performance was observed on both linac types2 when using the same TPS and version. Conclusion: The proposed RP_MCO-based automatic VMAT workflow provides fast, high-quality prostate cancer treatment planning, reducing planning time and inter- planner variability while maintaining or improving target coverage and adherence to dose guidance for organs of interest, and can be transferred to other centres equipped with the same linac models or with different systems sharing a similar delivery geometry. References: 1. Miguel-Chumacero, E., Currie, G., Johnston, A. et al. Effectiveness of Multi-Criteria Optimization-based Trade-Off exploration in combination with RapidPlan for head & neck radiotherapy planning. Radiat Oncol 13, 229 (2018).2. Castriconi R, Cattaneo GM, Mangili P, Esposito P, Broggi S, Cozzarini C, Deantoni C, Fodor A, Di Muzio NG, Vecchio AD, Fiorino C. Clinical Implementation of Knowledge-Based Automatic Plan Optimization for Helical Tomotherapy. Pract Radiat
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