Can Robust Optimization for Range Uncertainty in Proton Therapy Act as a Surrogate for Biological Optimization?

To investigate how robust optimization (to address range uncertainties) affects the dose and linear energy transfer (LET) distribution in the target and organs at risk (OARs) compared to LET-based inverse optimization (to address relative biological effectiveness - RBE - effects) in intensity modulated proton therapy (IMPT). A GPU-based Monte Carlo code was used to calculate both physical dose and dose-averaged LET for all pencil beams for IMPT proton plans for previously treated ependymoma patients. The plans were initially optimized based on physical dose constraints. A previously developed LET-based optimization algorithm, using a prioritized optimization scheme, was then applied to modify the LET distribution while constraining the physical dose objectives within 3% of the initial plan. The objective functions for this step were based on the product of LET and physical dose (LETxD) as an approximation of the additional biological dose that is caused by high LET. For the robust optimization all pencil beam dose and dose-averaged LET calculations were repeated for patient CT image sets with modified HU values, resulting in uniform ±2.33% and ±4.77% range deviations, for a total of five different scenarios. The level of range deviation and probability of these scenarios was estimated assuming a Gaussian-shaped probability of range uncertainty, with 1.5 sigma value of 3.5%, which is the clinically used range uncertainty in our institution. The dose and LETxD distributions resulting from the initial, LET-based and robust optimizations were then compared in terms of target coverage and OAR sparing. Our results show that both LET-based and robust optimization techniques of IMPT plans resulted in significantly reduced maximum LETxD values in the OARs adjacent to the target compared to the initial plan. Robust optimization avoids dose gradients in beam direction in the dose contributions of individual beams, effectively resembling single field uniformly optimized plans. For an ependymoma patient (Table 1) this results in higher median LETxD values for both the target and brainstem, compared to the initial plan. LET-based optimization most effectively reduced the median and mean LETxD to the brainstem, however also resulted in somewhat smaller median LETxD value for the target. Both inverse LET-based and robust optimization techniques can be a realistic approach to manage biological dose hot spots in the OARs adjacent to the target. Depending on the clinical dosimetric priorities set for each patient case, each one can offer distinct benefits towards avoiding potentially increased risk of side effects from elevated RBE of proton beams near the end of range.Abstract 230; Table 1Initial planLET-reoptimized planRobustly optimized planTargetD98 (Gy)484848.2D50 (Gy)50.750.650.9Median LETxD4.64.25.5BrainstemD50 (Gy)49.749.449.5Median LETxD4.83.85.7Max LETxD (2%)9.86.78.5 Open table in a new tab