S2026
Physics - Dose prediction/calculation, optimisation and applications for photon and electron planning
ESTRO 2026
agreed well with the plan dose (Figure 1), at a maximum deviation of 1.25% inside the target, and a 0.5% fluctuation over 3 repetitions. Increased differences were observed in a central OAR, where the delivered dose was lower than planned. The head&neck SHArc plan was delivered within less than 7min at GSI and log-file based dose reconstruction agreed with the plan dose to 99.6% gamma passing rate (1%/1mm criteria, Figure 2).
Journal of Radiation Oncology, Biology, Physics, 93(2), 431-438. Keywords: SABR - Variable collimator_VMAT
Poster Discussion 5078 First prototype for dynamic carbon ion arc therapy Lennart Volz 1 , Ahmad El Beit 1 , Zixin He 1,2 , Laila El Ouali 1 , Marco Donetti 3 , Cosimo Galeone 1 , Marco Durante 1,4 , Christian Graeff 1,5 1 Biophysics, GSI Helmholtz Center for Heavy Ion Research GmbH, Darmstadt, Germany. 2 UPLIFT, Funded by the European Union under Grant Agreement No. 101168955, Darmstadt, Germany. 3 CNAO, Centro Nazionale di Adroterapia Oncologica, Pavia, Italy. 4 Institute for Condensed Matter Physics, TU Darmstadt, Darmstadt, Germany. 5 Department for Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt, Germany Purpose/Objective: Spot-scanning carbon ion arc therapy (SHArc) has been proposed as an advanced form of carbon ion radiotherapy (CIRT) against resistant cancers1. Delivery efficiency of SHArc is challenged by the spill structure of CIRT synchrotrons, limited energy- selection flexibility, and sparse availability of CIRT gantries. This work provides a prototype for dynamic SHArc delivery assuming upright patient positioning. Material/Methods: A dynamic SHArc framework was implemented in the CNAO (Pavia, IT) dose delivery system (DDS), and coupled to a rotational stage (PI, Karlsruhe, GER). Building on existing infrastructure for 4D-synchronized CIRT2, the framework divides SHArc control points into discrete motion phases. A feedback loop between the motion controller and the DDS synchronizes rotation and plan progress. Control points of the same energy are delivered dynamically within the same synchrotron spill. The prototype was benchmarked at GSI and CNAO. At GSI, energy changes were accomplished with a binary range shifter, while at CNAO, SHArc plans were divided into sub-arcs of ascending-only energy changes to permit active energy switching within the accelerator constraints. A SHArc plan (180 control points, 2° spacing) was generated for a geometrical target in a ø20cm cylindrical water phantom for 5Gy physical dose, and verified by micro-pin-point dosimetry (PTW, Freiburg, GER). A head&neck SHArc plan (5Gy biological dose, 180 control points, 2° spacing) was experimentally delivered at GSI, and verified by log-file-based dose reconstruction. Results: SHArc delivery at CNAO took ~6min, where ~2min were related to switching the sub-arc plans. Micro-pin- point measurements for the geometric phantom
Figure 1: A) Dosimetry setup at CNAO. B) Micro-pin- point measurements on the planned dose. C) central dose profile. Each point represents three measurements.
Figure 2: Planned dose (A), log-file-based dose reconstruction (B), and delivery progression (C) of a biologically optimized SHArc plan delivered at GSI. Conclusion: A dynamic SHArc platform is presented which enables to deliver carbon ion arcs at similar duration compared to conventional CIRT. The setup can readily be interfaced to patient chairs which will be tested in the MSCA doctoral network UPLIFT. References: 1 Mein, S et al. 2024 Particle arc therapy: Status and potential Radiotherapy and Oncology, Volume 199, 1104342Steinsberger T, Donetti M, Lis M, Volz L, Wolf M, Durante M and Graeff C 2023 Experimental validation of a real-time adaptive 4D-optimized particle radiotherapy approach to treat irregularly moving tumors Int. J. Radiat. Oncol.*Biol.*Phys.115 1257–6 Keywords: Particle therapy, Carbon ion arc, Dynamic delivery PortPy: An open-source planning optimization platform bridging the gap between algorithm development and clinical implementation Gourav Jhanwar 1 , Mojtaba Tefagh 2 , Linda Hong 1 , Qijie Huang 1 , Ying Zhou 1 , Hai Pham 1 , Jie Yang 1 , Vicki Trier Taasti 3 , Seppo Tuomaala 4 , Saad Nadeem 1 , Masoud Zarepisheh 1 1 Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA. 2 School of Digital Poster 5080
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