Per‐voxel constraints to minimize hot spots in linear energy transfer‐guided robust optimization for base of skull head and neck cancer patients in IMPT
Authors: Feng Hongying , Shan Jie , Anderson Justin D. , Wong William W. , Schild Steven E. , Foote Robert L. , Patrick Christopher L. , Tinnon Kathryn B. , Fatyga Mirek , Bues Martin , Patel Samir H. , Liu Wei 
Published: November 2021

Purpose

Due to the employment of quadratic programming using soft constraints to implement dose volume constraints and the “trial‐and‐error” procedure needed to achieve a clinically acceptable plan, conventional dose volume constraints (upper limit) are not adequately effective in controlling small and isolated hot spots in the dose/linear energy transfer (LET) distribution. Such hot spots can lead to adverse events. In order to mitigate the risk of brain necrosis, one of the most clinically significant adverse events in patients receiving intensity‐modulated proton therapy (IMPT) for base of skull (BOS) cancer, we propose per‐voxel constraints to minimize hot spots in LET‐guided robust optimization.

Methods and materials

Ten BOS cancer patients treated with IMPT were carefully selected by meeting one of the following conditions: (1) diagnosis of brain necrosis during follow‐up; and (2) considered high risk for brain necrosis by not meeting dose constraints to the brain. An optimizing structure (BrainOPT) and an evaluating structure (BrainROI) that both contained the aforementioned hot dose regions in the brain were generated for optimization and evaluation, respectively. Two plans were generated for every patient: one using conventional dose‐only robust optimization, the other using LET‐guided robust optimization. The impact of LET was integrated into the optimization via a term of extra biological dose (xBD). A novel optimization tool of per‐voxel constraints to control small and isolated hot spots in either the dose, LET, or combined (dose/LET) distribution was developed and used to minimize dose/LET hot spots of the selected structures. Indices from dose‐volume histogram (DVH) and xBD dose‐volume histogram (xBDVH) were used in the plan evaluation. A newly developed tool of the dose‐LET‐volume histogram (DLVH) was also adopted to illustrate the underlying mechanism. Wilcoxon signed‐rank test was used for statistical comparison of the DVH and xBDVH indices between the conventional dose‐only and the LET‐guided robustly optimized plans.

Results

Per‐voxel constraints effectively and efficiently minimized dose hot spots in both dose‐only and LET‐guided robust optimization and LET hot spots in LET‐guided robust optimization. Compared to the conventional dose‐only robust optimization, the LET‐guided robust optimization could generate plans with statistically lower xBD hot spots in BrainROI (VxBD,50 Gy[RBE], p = 0.009; VxBD,60 Gy[RBE], p = 0.025; xBD1cc, p = 0.017; xBD2cc, p = 0.022) with comparable dose coverage, dose hot spots in the target, and dose hot spots in BrainROI. DLVH analysis indicated that LET‐guided robust optimization could either reduce LET at the same dose level or redistribute high LET from high dose regions to low dose regions.

Conclusion

Per‐voxel constraint is a powerful tool to minimize dose/LET hot spots in IMPT. The LET‐guided robustly optimized plans outperformed the conventional dose‐only robustly optimized plans in terms of xBD hot spots control.