ESTRO 2020 Abstract book
S138 ESTRO 2020
Conclusion A simulator of proton PBS delivery was developed and shown to predict the timing of PBS delivery accurately. It has useful applications in the clinic where the lower MU limit defines the treatment time and in the design of rescanning techniques and evaluation of proton plans for breath-hold treatments. It could also play an important role in optimization of FLASH proton plans, where accurate dose rate predictions are crucial. PH-0242 Maximizing the benefit of limited proton therapy resources through combined proton-photon treatments N. Loizeau 1 , S. Fabiano 2 , D. Papp 3 , A. Jakobi 4 , K. Stützer 4 , C. Richter 4 , J. Unkelbach 2 1 Universität Zürich, Physik-Institut, Zürich, Switzerland ; 2 University Hospital Zürich- University of Zürich, Department of Radiation Oncology, Zürich, Switzerland ; 3 North Carolina State University, Department of Mathematics, Raleigh, USA ; 4 Faculty of Medicine and University Hospital Carl Gustav Carus- Technische Universität Dresden- Helmholtz-Zentrum Dresden - Rossendorf, OncoRay-National Center for Radiation Research in Oncology, Dresden, Germany Purpose or Objective Although rapidly growing, proton therapy (PT) is a limited resource, which is not available to all patients who may benefit from it. Here, we investigate combined proton- photon treatments as an approach to optimally use the limited PT resources and maximize the benefit of PT at a population level. As an example, we consider a clinic offering both photons and protons and a scenario, in which only limited PT slots are available per day for treating head and neck cancer (HNC) patients. Material and Methods We assume a fixed number of available proton slots per day and, on average, 2 new HNC patients per week, each receiving 30 fractions over 6 weeks. We designed a slot allocation model that selects, on a daily basis, those patients currently under treatment who benefit the most from a proton treatment on the respective day. The remaining patients on that day receive a photon fraction.
Results Figures 1.B and 1.C show the waiting time of spots as function of energy and distance from the preceding spot logged during delivery of a training dataset plan. The cyclotron current in an energy layer varied from 74nA to 550 nA and was predicted with a root-mean-square (RMS) error of 1.6% (Figure 2.A). The duration of individual layers varied from 0.003s to 3.0s. Figures 2.B-2.D compares the simulated layer durations with the logged durations. The layer duration was predicted with RMS errors of 0.081 s (total layer duration), 0.003 s (total time of spot shifts in the layer) and 0.080 s (total beam-on time in the layer).
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