(Sunday, 7/12/2020) [Eastern Time (GMT-4)]
Room: AAPM ePoster Library
Purpose: Proton therapy can potentially be utilized to target deep seated tumors in humans while exposing healthy tissue to FLASH dose rates. The purpose of this work is to bridge the gap between treatment planning and plan delivery to understand the relationship between dosimetric plan quality and plan properties that tend to increase dose rates, using automated tools to explore the tradeoff.
Methods: A planning scorecard consisting of multiple dosimetric objectives each with a finite point value was created based on a single fraction lung SBRT protocol (RTOG 0915). An optimization algorithm was developed to directly maximize the total score calculated from the scorecard via a set of DVH based piece-wise linear penalties. The scorecard-based optimization algorithm was then executed on multiple pencil beam scanning (PBS) proton plans for the same patient varying multiple parameters including number of fields, spot spacing, and minimum MU per spot. Each field was configured to deliver a single energy layer at 250 MeV to maximize achievable nozzle current. For each configuration, the PBS dose rate was calculated and the volume receiving above 40 Gy/s was recorded along with the score. The PBS dose rate is defined as the dose delivered to a voxel divided by the irradiation time experienced by that voxel (elapsed real time).
Results: We observed a decreasing score and increased volume receiving 40 Gy/s as a function of decreasing number of beam angles. Spot spacing and MU per spot demonstrated a less drastic impact to total score until larger threshold values were reached.
Conclusion: The impact on dosimetric plan quality was studied as a function of achievable ultra-high dose rates with FLASH proton plans using a novel scorecard optimization method.
Funding Support, Disclosures, and Conflict of Interest: All authors were supported by Varian Medical Systems as paid full-time employees at the time of contribution.
Keywords
Protons, Treatment Planning, Modeling
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