Author: Duncan Henry Bohannon, Pretesh Patel, Sibo Tian, Yinan Wang, Xiaofeng Yang, Ahmal Jawad Zafar, Jun Zhou 👨🔬
Affiliation: Emory University, Department of Radiation Oncology and Winship Cancer Institute, Department of Radiation Oncology and Winship Cancer Institute, Emory University 🌍
Purpose:
4D robust optimization, incorporating additional images (e.g., maximum inhale/exhale phases), is commonly used to account for target motion in proton treatment planning. However, the increased number of scenarios significantly extends the optimization times. To address this, we propose a water equivalent thickness mapping (WET-MAP) technique that translates beam path changes due to motion into target contour extension/retraction on the planning CT (TPCT, on average image). By optimizing WET_MAP structures on the TPCT, coverage losses from respiratory motion can be mitigated without requiring multi-phase optimization, improving efficiency.
Methods:
WET-MAP plans were created for four lung cancer patients previously treated with 4D robust optimization. Robust coverage objectives were added to the WET structures. Plan quality for WET-MAP and 4D optimization was evaluated by comparing conformity index (CI), heterogeneity index (HI), R50, and evaluation doses across 21 robust evaluation scenarios (uniform 5mm setup uncertainty and ±5.00% density uncertainty) on the TPCT and ±5.00% density uncertainty on the maximum inhale/exhale phases. The worst-case scenario of V100, lung V20Gy, and mean lung dose were compared.
Results:
For WET-MAP vs 4D optimized plans, V100 was > 95% on all robust evaluation scenarios over all patients and images, and the average CI, HI, and R50 were (1.01, 1.28, 3.15) vs (1.00, 1.28, and 3.25), respectively. The average worst-case V100 on WET-MAP vs 4D optimized plans on the TPCT, maximum inhale and exhale images were (95.6%, 99.0%, 99.8%) vs (96.5%, 99.80%, and 99.9%), respectively. The corresponding average worst-case lung V20Gy values were 9.12%/9.48%, 8.13%/8.65%, and 8.92%/9.30%, respectively. The average worst-case mean lung doses were 5.02/5.30Gy, 4.50/4.83Gy, and 4.99/5.26Gy.
Conclusion:
Coverage was comparable between WET-MAP and 4D optimization plans, while WET-MAP plan provides better sparing of normal lung, indicating that WET-MAP could be a more efficient alternative to 4D optimization without compromising plan quality.