S1926
Physics - Dose prediction/calculation, optimisation and applications for photon and electron planning
ESTRO 2026
comparable and depended primarily on computing resources. Table 1 summarizes the time per step for both workflows.
which predicts achievable DVHs and generates optimization objectives. The plan is then optimized, and the final dose distribution calculated automatically.AutoTPS was evaluated using 20 endometrial cancer cases previously treated with VMAT photon radiotherapy on a TrueBeam (Clinical Plan). The AutoTPS generated plans were compared dosimetrically against the corresponding clinical plans. Additionally, planners with varying experience manually repeated the same workflow steps as the AutoTPS, recording the time required for each step. These were then compared with the automated workflow. Results: AutoTPS produced treatment plans with dosimetry closely matching clinical plans; 9/20 plans were immediately clinically acceptable. For the remaining plans, small manual adjustments would be required due to the Rapidplan prioritising OAR sparing over PTV coverage [1].Key dose metrics for the PTV, bladder, rectum, and bowel sac are shown in Figure 1. When comparing the medians, PTV coverage was slightly lower (D98% -0.43 Gy), and the near maximum dose was slightly higher (D2% +0.21 Gy), while the Dmean was marginally reduced for the bladder (- 0.48 Gy) and rectum (-0.47 Gy). Small increases in median D0.1cc were observed for the bladder (+0.28 Gy) and bowel sac (+0.52 Gy). All median differences were within 2% of clinical plans. Overall, AutoTPS created plans with dosimetry comparable to the clinical plans.
Conclusion: AutoTPS provides an automated workflow for back-up radiotherapy planning across treatment machines, enabling fast photon plan generation. The software achieves clinically comparable dosimetry with minimal user input, supporting efficient, standardized planning that can be readily scaled across anatomical sites. References: [1] Frizzelle, M., Pediaditaki, A., Thomas, C., South, C., Vanderstraeten, R., Wiessler, W., Adams, E., Jagadeesan, S. and Lalli, N. (2022) 'Using multi- centre data to train and validate a knowledge-based model for planning radiotherapy of the head and neck', Physica Medica, 21, pp. 18-23. doi: 10.1016/j.phro.2022.01.003. Keywords: Automated treatment planning; Backup plans; ESAPI; Establishing Plan Quality Benchmarks for on-line adaptive Prostate SABR: Utilising Efficiency indices as a tool for plan quality assessment Alexis Dimitriadis 1 , Joe Drabble 2 , Peter Maungwe 2 , Ebison Chinherende 1 , Asadullah Khan 3 , Addalin Huynh 1 , Dan Murray 2 , Edward Ilsley 2 , Daniel Johnson 2 , Philip Wai 3 , Derya Yucel 1 , Ben George 2 , Paul Laycock 1 , Alex Morris 1 1 Centre for Radiotherapy at Cromwell Hospital, GenesisCare UK, London, United Kingdom. 2 Radiotherapy, GenesisCare UK, Oxford, United Kingdom. 3 Radiotherapy, GenesisCare UK, Guildford, United Kingdom Purpose/Objective: MR-guided online adaptive radiotherapy (MRgART) for prostate stereotactic ablative body radiotherapy (SABR) requires rapid plan quality evaluation to minimise patient time on-table and mitigate intra- fractional organ motion. This analysis aimed to establish standardised plan quality benchmarks for prostate SABR across a network of MR-Linac (MRL) centres using a unified treatment protocol. Efficiency Index ( η ₅₀ %) and OAR Efficiency Indices (OAR η ₅₀ %) Digital Poster 3232
AutoTPS reduced user input time on average by seven minutes. The greatest time savings were observed during structure creation and plan setup. Optimization and dose calculation times were
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