S1723
Physics - Dose prediction/calculation, optimisation and applications for particle therapy planning
ESTRO 2026
Digital Poster 1941 Introducing a new Spot-Scanning Proton Arc optimization algorithm with a Variable Tolerance Window to improve plan quality for bilateral breast cancer Xiaoda Cong 1 , zerun zhang 1 , Gang Liu 2 , peilin liu 1 , Xi Cao 3 , xiaoqiang li 1 , Peter Chen 1 , Joshua Dilworth 1 , xuanfeng ding 1 1 radiation oncology, corewell health, Royal Oak, USA. 2 cancer center, Huazhong University of Science and Technology, wuhan, China. 3 residency, corewell health, royal oak, USA Purpose/Objective: Breast cancer is the most common non-cutaneous cancer in women. Despite state-of-the-art Intensity Modulated Proton Therapy (IMPT), achieving satisfactory performance of target coverage and OAR dose remains a challenge, especially for complex target geometries such as bilateral breast cancer1. Recently, Spot-scanning Proton Arc (SPArc) therapy has shown potential clinical benefits compared to IMPT; however, it has been challenged by the energy layer selection in evenly-distributed control points, which results in suboptimal plan quality. We hypothesize that giving more degrees of freedom by allowing extra energy layers across specific arc trajectories will improve treatment delivery. Therefore, we introduce a new SPArc algorithm with a variable tolerance window (SPArc-variable) to further improve plan quality for patients receiving bilateral breast and regional nodal irradiation. Material/Methods: The SPArc-variable optimization algorithm is based on 0-1 knapsack problem in dynamic programming (DP)2. Based on multifield-IMPT plan with 20 degrees apart, the algorithm iteratively selects a subset of energy layers under decreasing energy layer filtration factor. Then it resamples the energy layers based on the gantry’s movement and irradiation sequence. Finally, spot weighting optimization is applied to fine-tune the dose distribution sequentially. Five cases with bilateral breast and lymph nodes treatment are retrospectively selected. Three treatment planning groups were generated, including IMPT with 2-isos and corresponding treatment fields, SPArc planning with a fixed distance of 2.5 degrees between adjacent control points(SPArc-original), and SPArc planning with non- fixed distance between adjacent control points(SPArc- variable), with a prescription of 5000cGy(RBE). DVH metrics are included to evaluate performance over OARs and targets, and dynamic delivery is simulated via a published dynamic arc system controller3. Results: Both SPArc-original and SPArc-variable plans showed slightly superior target coverage compared to IMPT
Conclusion: Despite superior OAR sparing, PAT demands more frequent replanning to ensure plan robustness against anatomical variations and uncertainties. References: [1] de Jong, B. A., Korevaar, E. W., Maring, A., Werkman, C. I., Scandurra, D., Janssens, G., ... & Langendijk, J. A. (2023). Proton arc therapy increases the benefit of proton therapy for oropharyngeal cancer patients in the model based clinic. Radiotherapy and Oncology, 184, 109670.[2] Rojo-Santiago, J., Korevaar, E., Perkó, Z., Both, S., Habraken, S. J., & Hoogeman, M. S. (2023). PTV-based VMAT vs. robust IMPT for head-and- neck cancer: A probabilistic uncertainty analysis of clinical plan evaluation with the Dutch model-based selection. Radiotherapy and Oncology, 186, 109729. Keywords: Probabilistic planning, Proton arc therapy
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