S1743
Physics - Dose prediction/calculation, optimisation and applications for particle therapy planning
ESTRO 2026
therapy,” Med Phys, vol. 50, no. 12, pp. 7338–7348, 2023. 2.Bazani et al., “2693 Investigation of the combined effect of dose and linear energy transfer on brain necrosis after proton therapy,” Radiotherapy and Oncology, vol. 206, pp. S3508–S3509, 2025. 3.P. Lægdsmand et al., “Variations in linear energy transfer distributions within a European proton therapy planning comparison of paediatric posterior fossa tumours,” Phys Imaging Radiat Oncol, vol. 32, p. 100675, 2024. Keywords: proton, LETd, skull-base Mini-Oral 2840 Development of a Time-of-Flight Ion Computed Tomography Demonstrator for Improved Treatment Planning in Ion Beam Therapy Feli Ulrich-Pur 1 , Ashish Bisht 2 , Thomas Bergauer 3 , Tetyana Galatyuk 4 , Henning Heggen 5 , Albert Hirtl 1 , Matthias Kausel 6 , Mladen Kis 7 , Barbara Knäusl 8 , Yevhen Kozymka 4 , Sergey Linev 5 , Jan Michel 9 , Julia Müllner 3 , Jerzy Pietraszko 9 , Christian-Joachim Schmidt 7 , Michael Träger 7 , Michael Traxler 5 , Matteo Centis Vignali 2 1 Atominstitut, TU Wien, Vienna, Austria. 2 FBK, FBK, Trento, Italy. 3 Detectordevelopment, Marietta-Blau- Institut, Vienna, Austria. 4 IKP, TU Darmstadt, Darmstadt, Germany. 5 EE, GSI, Darmstadt, Germany. 6 Accelerator Physics, MedAustron, Wiener Neustadt, Austria. 7 Detectorlaboratory, GSI, Darmstadt, Germany. 8 Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria. 9 HADES, GSI, Darmstadt, Germany Purpose/Objective: The precision of ion beam therapy critically depends on the accuracy of tissue stopping-power (SP) maps. Currently, these maps are derived from X-ray CT images via conversion from Hounsfield units, a process that introduces range uncertainties and necessitates larger safety margins around the tumour [1]. Time-of-flight ion computed tomography (TOF-iCT) offers a direct method to measure SP values and can thereby reduce range uncertainties in treatment planning [2]. We developed and tested a TOF-iCT demonstrator based on ultra-fast silicon detectors capable of tracking individual ions and measuring their TOF with high precision. The system was evaluated using sacrificed mice and tissue-equivalent materials, while in-vivo and mixed-beam experiments combining carbon therapy with helium-based TOF radiography (TOF-HeRads) are being prepared to explore its potential for online range monitoring. Material/Methods: The demonstrator employs multiple layers of low-gain avalanche diode (LGAD) detectors. Each detector layer
Figure 1. Optimized plans for a representative patient according to the described main strategies. Results: LETd optimization consistently reduced LETd in the brain and brainstem compared to clinical plans without compromising target coverage. After initial optimization, LETd in the brain decreased from 5.1 ± 0.4 to 4.5 ± 0.1keV/ μ m, and in the brainstem from 3.5 ± 0.4 to 2.6 ± 0.8keV/ μ m. Gantry geometries provided greater flexibility, enabling further LET reduction while preserving dose conformity and homogeneity. The most effective strategy (Gantry + LET 3) reduced the expected risk of brain necrosis to 5.6% vs. clinical plans, according to the NTCP curve (Figure2). LETd optimization did not affect LETd distribution within the CTV, thereby maintaining the biological effectiveness of proton therapy. All clinically acceptable plans achieved CTV coverage ≥ 95% and robustness within ±5%.
Figure 2. a)Relationship between LETd values and Robustness and b)NTCP estimation for the different optimization strategies. Conclusion: LETd-based optimization reduces brain and brainstem exposure while maintaining plan quality and robustness. Combining gantry geometries with strict LET constraints yields the greatest clinical benefit. Larger studies are needed to confirm these findings. References: 1.Fredriksson, L. Glimelius, and R. Bokrantz, “The LET trilemma: conflicts between robust target coverage, uniform dose, and dose - averaged LET in carbon
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