Characterizing devices for validation of dose, dose rate, and LET in ultra high dose rate proton irradiations

Abstract

Background

Ultra high dose rate (UHDR) radiotherapy using ridge filter is a new treatment modality known as conformal FLASH that, when optimized for dose, dose rate (DR), and linear energy transfer (LET), has the potential to reduce damage to healthy tissue without sacrificing tumor killing efficacy via the FLASH effect.

Purpose

Clinical implementation of conformal FLASH proton therapy has been limited by quality assurance (QA) challenges, which include direct measurement of UHDR and LET. Voxel DR distributions and LET spectra at planning target margins are paramount to the DR/LET-related sparing of organs at risk. We hereby present a methodology to achieve experimental validation of these parameters.

Methods

Dose, DR, and LET were measured for a conformal FLASH treatment plan involving a 250-MeV proton beam and a 3D-printed ridge filter designed to uniformly irradiate a spherical target. We measured dose and DR simultaneously using a 4D multi-layer strip ionization chamber (MLSIC) under UHDR conditions. Additionally, we developed an “under-sample and recover (USRe)” technique for a high-resolution pixelated semiconductor detector, Timepix3, to avoid event pile-up and to correct measured LET at high-proton-flux locations without undesirable beam modifications. Confirmation of these measurements was done using a MatriXX PT detector and by Monte Carlo (MC) simulations.

Results

MC conformal FLASH computed doses had gamma passing rates of >95% (3 mm/3% criteria) when compared to MatriXX PT and MLSIC data. At the lateral margin, DR showed average agreement values within 0.3% of simulation at 100 Gy/s and fluctuations ∼10% at 15 Gy/s. LET spectra in the proximal, lateral, and distal margins had Bhattacharyya distances of <1.3%.

Conclusion

Our measurements with the MLSIC and Timepix3 detectors shown that the DR distributions for UHDR scenarios and LET spectra using USRe are in agreement with simulations. These results demonstrate that the methodology presented here can be used effectively for the experimental validation and QA of FLASH treatment plans.