S1729
Physics - Dose prediction/calculation, optimisation and applications for particle therapy planning
ESTRO 2026
treatment planning software: BP-only and hybrid BPTPB. For FLASH-ready treatment, three alternative strategies to hybrid BPTPB were created. To meet the FLASH conditions, all TPBs from a single beam were selected (TPB-FLASH) to be delivered separately under ultra-high dose-rates (and thus removed from other fractions).-Strategy 1: The TPB- FLASHare delivered during the first fraction, prior to the other pencil-beams scheduled for that fraction. - Strategy 2: The TPB-FLASHare delivered in a separate fraction -totaling 7 fractions.-Strategy 3: As Strategy2, but rescaled to a total of 6 fractions.To ensure the effectiveness of all treatment plans, doses were rescaled such that VWmin: CTV BED98%=BED(95%Dpres), using alpha/beta=10 GyE. Here, BED is the biologically effective dose, and BED(95%Dpres) (=53.7 GyE) is the 95% prescribed dose converted to BED.For TPB-FLASH, we assume that a pencil-beam scanning dose-rate (PBS- DR) threshold of 40 GyE/s, and a dose threshold of 4 GyEis required to trigger FLASH. The PBS-DR was optimized using delivery pattern optimization. If FLASH is triggered, the physical dose is divided by the FLASH enhancement ratio (FER). To investigate the impact of the strategies on OAR dose, we computed the EQD2 (alpha/beta=3 GyE) for OARs under increasing FER. Results: Figure 1 shows EQD2 variations for OARs in patients where at least one alternative strategy reduced the EQD2 for increasing FERs, compared to theconventional plans. Reductions of up to 2.7 GyE (FER=1) and 6.8 GyE (FER=1.8) were obtained compared to a BP-only plan. Figure 2 shows results for a patient in which FLASH-ready was not feasible for FER=1.
integration into carbon ion treatment-planning workflows. These findings highlight the importance of improved tissue-parameter estimation for quantitative and uncertainty-aware quality assurance in carbon ion
radiotherapy. References:
1. Tsujii H, Kamada T. Carbon ion radiotherapy: clinical results. Jpn J Clin Oncol. 2012.2. Mohamad O, Yamada S, Durante M. Clinical indications for carbon ion therapy. Clin Oncol. 2018.3. Schneider W, Bortfeld T, Schlegel W. CT numbers and tissue parameters for MC dose calculation. Phys Med Biol. 2000.4. Hünemohr N, Paganetti H, Greilich S, et al. Dual-energy CT tissue decomposition for particle therapy. Med Phys. 2014.5. Li Y, Li W, Yang C, et al. ML-based DECT elemental decomposition for carbon ion therapy. Med Phys. 2025.6. JCGM. Guide to the Expression of Uncertainty in Measurement (GUM). 2008.7. Peters N, Wohlfahrt P, Hofmann C, et al. Dual-energy CT for reducing proton
therapy margins. Radiother Oncol. 2022. Keywords: Carbon ion therapy, DECT, Dose uncertainty
Digital Poster 2315 FLASH-ready treatment planning for reirradiation head-and-neck IMPT using hybrid IMPT and transmission beams Manon C. van Zon 1,2 , Steven J.M. Habraken 3,2 , Wens Kong 1 , Mischa S. Hoogeman 1,2 , Sebastiaan Breedveld 1 1 Department of Radiotherapy, Erasmus MC Cancer Institute, Rotterdam, Netherlands. 2 Department of Medical Physics and Informatics, Holland Proton Therapy Center, Delft, Netherlands. 3 Department of Radiation Oncology, Leiden University Medical Center, Leiden, Netherlands Purpose/Objective: The conditions assumed to trigger the FLASH effect, pose restrictions on treatment planning. These restrictions often result in inferior treatment plan quality compared to conventional radiotherapy. Since the magnitude of the FLASH effect is unknown, it is unclear if the FLASH effect outweighs compromises in treatment plan quality. We investigated a phenomenological approach to generate FLASH-ready treatment plans for head-and-neck patients, i.e. not inferior to conventional radiotherapy but increased sparing under FLASH assumptions, by combining Bragg-Peak and Transmission Pencil-Beams (BPTPB). Material/Methods: We included four head-and-neck reirradiation patients, treated to a 6x6 GyE fractionation schedule. Two conventional proton therapy treatment plans on 21 optimization scenarios were generated using our in-house developed robust automated
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