ESTRO 37 Abstract book

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ESTRO 37

being <15% (Figure 2). Combining 4D optimization with rescanning however can significantly improve optimized plan quality, with HI in the CTV to within 5% of a static 3D plan. For the ‘best-case’ rescanned 4D plans, 4D optimization could be able to provide 'zero-motion- margin” for 4D treatments (in Fig. 1), resulting in pronounced reduction of dose to the healthy liver (median 5% for V10/20/60% indexes). However, optimized 4D plans, especially those without rescanning, have been shown to be extremely sensitive to variations of the presumed (during the optimization) and actual motion conditions during delivery. Nevertheless, the robustness of 4D optimized plans could be substantially increased by combining optimization with rescanning, with comparable plan quality (within 5%), being achievable for rescanned 4D optimized plans even when allowing for phase shifts between optimization and delivery of up to 500ms, This is in contrast to the less than 200ms shifts that were observed to degrade plan quality for 4D plans optimized without rescanning.

and c) an adaptive approach, where the spot weights are exposed to a group sparsity penalty in combination with layer exclusion during optimization. Within each strategy, four levels of layer reduction are used; a) increasing constant energy increment, b) increasing energy multiplication factor, and c) an increasing removed percentage of layers. The plans are created with three treatment fields on the mid ventilation 4DCT phase to simulate gating. Optimum target and OAR constraints are found by a patient specific reference treatment plan, where the distance between the layers is 2 MeV. Identical target constraints are used for all patients and strategies. The plan quality is assessed by the homogeneity index (HI), the maximum target dose and the outcome of a robustness evaluation, where the patient is shifted 2 mm or 4 mm in the 6 major directions. Results Robustness and target coverage as a function of reduction level are similar for all strategies. Figure 1 shows the D98%, D02% and the HI for the CTV. All MFO plans are clinically acceptable, while the SFO plans starts to degrade after what corresponds to 50% layer reduction as compared to the reference plan. The robustness, however, is independent of the number of energy layers for both SFO and MFO plans. Figure 2 shows the robustness evaluation results as a D98% dose difference between the planned dose and the mean shifted dose at either 2 mm or 4 mm. The SFO plans are significantly more robust than the MFO plans with all p-values below 0.001 (Wilcoxon signed-rank). The overall mean D98% dose difference is at 2 mm: 0.7 Gy (SFO) and 1.9 Gy (MFO), and at 4 mm: 3.2 Gy (SFO) and 5.4 Gy(MFO).

Conclusion 4D plan optimization can substantially minimize ITV margins, therefore reducing dose to normal issues. Incorporating rescanning into 4D optimization is beneficial for achieving such goals, thanks to the significantly increased 4D plan robustness w.r.t. motion variations. PV-0203 Energy layer reduction strategies for single- and multi field optimization of proton lung plans M. Fuglsang Jensen 1 , L. Hoffmann 2 , J.B.B. Petersen 2 , D.S. Møller 2 , M.L. Alber 3 1 Aarhus University Hospital, Department of Oncology and Danish Centre for Particle Therapy, Aarhus C, Denmark 2 Aarhus University Hospital, Department of Medical Physics, Aarhus C, Denmark 3 Heidelberg University Hospital, Department of Radiation Oncology, Heidelberg, Germany Purpose or Objective For proton therapy treatments of lung cancer, robust delivery can be ensured by gating and rescanning techniques. This, however, increases the treatment time which translates into a higher risk of intra fractional changes. Treatment times can be reduced by limiting the number of energy layers, but this can challenge the target coverage and plan robustness. We investigate to what extend the number of layers can be reduced in single field optimization (SFO) and multi field optimization (MFO) plans using three different strategies. Material and Methods 11 advanced NSCLC patients are included in the study. The three strategies for layer selection are implemented in the treatment planning system Hyperion; a) constant energy steps, b) exponentially increasing energy steps,