Robust Optimization of Proton Therapy Treatments Using a Variable Range Uncertainty
M Cohilis1*, E Sterpin1,2, C Chang3, S Rivas1, L Lin4, J Lee1, K Souris1, (1) UCLouvain, Brussels, BE, (2) KU Leuven, Leuven, BE (3) Emory University, Alpharetta, GA (4) Emory Proton Therapy Center, Atlanta, GA
Presentations
WE-A-TRACK 6-3 (Wednesday, 7/28/2021) 10:30 AM - 11:30 AM [Eastern Time (GMT-4)]
Purpose: In proton therapy (PT), a range uncertainty of 2.6% is typically assumed when planning robust treatments with Monte Carlo dose engines. This number is based on a dominant contribution from tissues I-values. However, it was recently shown that expressing tissues as a mixture of water and “dry” material during the CT calibration process allowed for a significant reduction of this uncertainty.We thus propose an adapted framework for PT robust optimization. First, we move towards a spot-specific range uncertainty (SSRU) determination. Second, we use the water-based formalism to reduce range uncertainties and potentially better spare OAR. The methodology is applied to the treatment planning of a head and neck (H&N) primary tumor.
Methods: For each spot, a ray-tracing method was used to propagate I-values uncertainties and obtain the corresponding range uncertainties. These were then combined with other sources of range uncertainties.Two plans of the same patient were optimized: the first one with the classical 2.6% range uncertainty, the second one with the SSRU. These plans were compared in terms of OAR mean dose reduction. Robustness evaluations were also performed, using the SSRU for both plans in order to simulate errors as realistically as possible.
Results: The SSRU plan was found to have a very good robustness level at a 90% confidence interval while sparing OAR better than the classical plan. Mean dose reductions of 2.20 Gy and 4.27 Gy were respectively observed in the oral cavity and superior pharyngeal muscle for a similar target coverage. The classical plan showed an unnecessary robustness level, even when considering 100% of the simulated scenarios.
Conclusion: Promising results of the SSRU framework were observed on a simplified H&N case. We believe the methodology could benefit even more for a full H&N treatment where more OAR will be close to the target volume.
Funding Support, Disclosures, and Conflict of Interest: M. Cohilis is supported by the Televie grant from the Belgian fund of scientific research (F.R.S-FNRS), grant No. 7652619F. K. Souris is funded by the Walloon Region (MECHATECH/BIOWIN, Grant No. 8090). J. Lee is a senior research associate with the F.R.S-FNRS.
Handouts
Keywords
Protons, Treatment Planning, Monte Carlo
Taxonomy
TH- External Beam- Particle/high LET therapy: Proton therapy – dose optimization
Contact Email