Room: AAPM ePoster Library
Purpose: FLASH has demonstrated normal tissue sparing effects while maintaining equivalent tumor control in vivo. Prior proton planning studies showed that achieving FLASH dose rate in large field is difficult with significant low dose (at lowered dose rate) contributions from many surrounding beam spots. In this study, we demonstrated a clustered pencil beam scanning (CPBS) technique that optimizes localized dose delivery towards ultra-high FLASH dose rate.
Methods: Reduction of rectal toxicity is one of the goals in prostate treatment. In CPBS technique, beam spots that pass through the rectum were regrouped from the original beam arrangement and delivered as separate clusters. The machine log files were obtained and extrapolated to high cyclotron current of 1000nA to simulate FLASH delivery conditions. The spot-to-spot dose contribution to the hot spot in rectum was simulated with MC2 to derive the dose-time structure and effective dose rate. The energy switching time and magnet spot positioning time were ignored in the calculation.
Results: Of the two lateral beams for proton prostate treatment, the number of spots passing through rectum were 208 and 212 out of LT LAT 1755 and RT LAT 1771 spots. Using log file derived pencil beam spot duration 256.88 ms*nA/MU and cyclotron current of 1000 nA, the individual spot contributes dose at a rate of 125.4+/-348.3 Gy/s. The effective dose rate to the rectum was 62.2 and 72.3 Gy/s. Without using the clustered PBS delivery, the effective dose rate was 13.0 Gy/s for both fields.
Conclusion: We demonstrated localized fast delivery in rectum with CPBS technique to take advantage of FLASH tissue sparing effect. Demonstrations of this technique on multiple patients are in progress. The energy switching and spot positioning time in current proton system can add >100ms in the delivery and thus achieving FLASH dose rate is not yet clinically feasible.
Protons, Monte Carlo, Treatment Techniques
TH- External Beam- Particle/high LET therapy: Proton therapy – computational dosimetry-Monte Carlo