ESTRO 2024 - Abstract Book

S4657

Physics - Optimisation, algorithms and applications for ion beam treatment planning

ESTR0 2024

5. Brighi C, Keall PJ, Holloway LC, et al. An investigation of the conformity, feasibility, and expected clinical benefits of multiparametric MRI-guided dose painting radiotherapy in glioblastoma. Neuro-Oncology Adv. 2022;4(1):1-10. doi:10.1093/noajnl/vdac134

6. Paganetti H. Mechanisms and Review of Clinical Evidence of Variations in Relative Biological Effectiveness in Proton Therapy. Int J Radiat Oncol. 2022;112(1):222-236. doi:10.1016/j.ijrobp.2021.08.015

1860

Proffered Paper

Inclusion of delivery dynamics into optimization reduces delivery time for liver IMPT treatments

Michael P. Butkus, Daniel J. Bastawros, Robert Kaderka

University of Miami, Radiation Oncology, Miami, USA

Purpose/Objective:

Integrating energy layer-spacing and minimum deliverable MUs into intensity modulated proton therapy (IMPT) optimization has the potential to reduce beam-on times. If plan quality is unaffected, this would represent a meaningful improvement in treatment efficiency. In this study, we investigated a prototype beam optimization algorithm that includes these delivery dynamics. IMPT has the potential to substantially reduce normal tissue dose for liver patients. However, liver targets are subject to breathing motion and are thus at risk of poor dose distribution due to the interplay effect. Liver patients treated with IMPT may therefore require motion mitigation strategies such as abdominal compression, deep inspiration breath hold (DIBH) or phase gating which all reduce patient comfort and prolong treatment. At our institution patients undergo DIBH and can hold their breath typically for 20-30 seconds. Some patients exhibit reduced tolerance, particularly as they get fatigued resulting in prolonged and uncomfortable treatments. Reducing delivery time could reduce the number of breath holds needed, and therefore decrease total treatment time, increase patient comfort and better ensure reproducibility.

Material/Methods:

A cohort of 10 consecutive liver DIBH patients previously treated at our institution was identified. Six treatment plans were made for each of these patients with a Varian Medical Systems prototype treatment plan optimization algorithm called RapidScan. In RapidScan, the user can specify desired minimum Monitor Units (MU) per spot and energy layer spacing as additional optimization parameters. Using a knowledge-based planning solution for liver IMPT, nominal plans were re-planned to match setup and plan quality of the clinically delivered plan. These nominal plans were created using Eclipse NUPO V.18 which optimizes proton fluence with a preset fixed layer-spacing. After optimization, a post-processing step adjusts the spots according to machine limitations/settings (3 MeV fixed layer-spacing and minimum MU of 1.0 at our institution). Then, 5 plans per patient were created using RapidScan with spot optimization and different combinations of layer-spacing and minimum MU: 1MU/1MeV, 1MU/3MeV, 1MU/5MeV, 3MU/3MeV, and