S2732
RTT - Patient preparation, immobilisation, and verification protocols
ESTRO 2026
Conclusion: Variability in residual motion under AC and EBH reproducibility underscores the need for flexible motion-management pathways rather than one-size- fits-all protocols. Notably, measurements represented the worst-case motion at the liver dome. The absence of clear associations with patient factors suggests that physiological, psychological, and training-related influences, including patient coaching and staff education, warrant further research. As the determinants of effectiveness remain uncertain, pre- treatment assessment of liver-dome motion and AC/EBH feasibility and reproducibility, as demonstrated in this study, offers a pragmatic interim approach to guide patient selection, optimise resource use, and inform future research toward personalised motion management. References: 1. Daly, M., et al., Radiotherapy respiratory motion management in hepatobiliary and pancreatic malignancies: a systematic review of patient factors influencing effectiveness of motion reduction with abdominal compression. Acta Oncologica, 2022. 61(7): p. 833-841.2. Webster, A., et al., A systematic review of the impact of abdominal compression and breath-hold techniques on motion, inter-fraction set- up errors, and intra-fraction errors in patients with hepatobiliary and pancreatic malignancies. Radiother Oncol, 2024. 201: p. 110581.3. Daly, M., et al., Retrospective review of patient factors impacting free- breathing respiratory motion magnitude for MR- guided radiotherapy. Tech Innov Patient Support Radiat Oncol, 2025. 35: p. 100339. Keywords: Motion management, patient factors, personalised Poster Discussion 2995 Hybrid path planning for patient positioning robots Jezdimir Milosevic 1 , Patrik Malm 1 , Rasmus Bokrantz 1 , Johannes Hopfgartner 2 1 Development, RaySearch Laboratories, Stockholm, Sweden. 2 Medical Physics, MedAustron, Wiener Neustadt, Austria Purpose/Objective: We present a novel path planning algorithm for patient positioning before external beam radiation therapy using a robotic couch. The approach combines: A flexible nondeterministic planner for transporting patients close to the treatment position from, e.g., rest or imaging positions. A deterministic planner for controlled movements into treatment positions when close to the treatment head.The study
is motivated by the clinical preference for a planner that is flexible enough to move the patient from various room positions, while simultaneously providing predictable movements around the treatment head. These predictable movements minimize the risk of collisions and increase confidence
in system operation. Material/Methods:
A hybrid path planning algorithm that combines a nondeterministic rapidly-exploring random tree planner [1] and a rule-based deterministic planner was implemented in the RayCommand treatment control system (RaySearch Laboratories) [3] to generate collision-free trajectories for a patient positioning robot (Figure 1). The algorithm was evaluated by simulation with respect to a virtual model of a treatment room at the MedAustron particle therapy center [2]. Results were recorded for planning from 4 start positions outside of the treatment head area to 40 potential treatment positions (160 simulations in total). Simulations were also performed for comparative purposes using only the purely deterministic planner, where the nondeterministic segment was replaced by a linearly interpolated segment.
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