2259 - Exploring the Impact of Breathing Phase Reduction on 4D Robust Optimization in Intensity-Modulated Proton Therapy for Hepatocellular Carcinoma
Presenter(s)
S. Wang1,2, X. Fan1, W. Li2, T. Dai3, and Y. Yin2; 1Department of Graduate, Shandong First Medical University, Shandong Academy of Medical Sciences, Jinan, China, 2Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China, 3Thayer School of Engineering, Dartmouth College, Hanover, NH
Purpose/Objective(s): The motion of hepatic tumors attributable to respiratory could significantly impact the efficacy of IMPT outcomes. 4D robust optimization is a promising approach to addressing the interplay effect caused by tumor motion during IMPT. However, it is not extensively implemented in the clinic due to its computational load. The aim of this work is to lower the number of breathing phases required for the 4D robust IMPT optimization procedure for hepatocellular cancer, as well as the computing cost.
Materials/Methods: This study included 15 individuals with hepatocellular cancer with 4DCT data. Different 4D optimization strategies were developed according to the selected number of breathing phases (10, 6EX, 6IN, 3 and 2 phases, respectively). The 3DCT-based optimization strategy (denoted as 3D) was also performed. All patients had their 4D dynamic doses (4DDD) calculated for all optimization strtegies. Dosimetric parameters for tumor target and organs at risk were investigated. The required optimization durations for all strategies were recorded.
Results: The 3D optimization strategy performed worse in terms of target coverage. The five 4D optimization strategies showed similar protection of the organs at risk (p=0.05). The HI for 2 phases and 6IN phases was higher than that of 10 phases (p=0.05). For CI, the more optimized the selected phases, the smaller and closer to the value of CI for the full-time phases. Optimization durations for 6EX phases, 6IN phases, 3 phases and 2 phases decreased by 36.07%, 32.18%, 61.20% and 69.72%, respectively, in comparison to 10 phases.
Conclusion: The two strategies (6EX phases and 6IN phases) showed promising dosimetric parameters and robustness among all optimization strategies investigated in this work, which is potential to shorten the 4D robust optimization time. Consequently, the 6EX phases and 6IN phases strategies may replace a highly computationally costly optimization approach of 10 phases.