Purpose: Online adaptive radiotherapy (OART) has been feasible over decades of technology development and is now available in the clinical routine through dedicated platforms with on-board CT/MR imaging and integrated treatment planning system (TPS). The quality assurance (QA) of online plans has become a bottleneck in the clinical workflow, including lengthy wait for 2nd dose verification. We implemented a web-based fully automatic 2nd check for OART to address such a bottleneck. In this work, we present our beam modeling and auto-commissioning for the 2nd check platform and demonstrate it for the Ethos system.
Methods: We developed a general-purpose dose calculation server powered by the in-house GPU-based Monte Carlo particle transport engine. An auto-commissioner was also developed to facilitate beam modeling based on water tank measurements. The Ethos beam model consisted of three tuned components: 1) in-air open-field fluence, 2) energy spectrum, and 3) fluence convolution kernel such that calculated dose matched the commissioning beam data, including the open field profiles at d_DMax, PDD of 10cm×10cm, and output factors of square fields (1, 2, 4, 28cm) with SSD=90cm setup, and was calibrated to the reference point dose at d_DMax of 10cm×10cm and SSD=100cm.
Results: The auto-commissioner took ~30min to tune the beam model, which was verified extensively by the entire Ethos beam-book, including lateral profiles, depth doses, and output factors, measured for various square/rectangle fields at various depths (1.3, 5, 10, 20, 30cm) to within 1% difference. The beam model has been implemented clinically to perform 2nd dose for every Ethos plan on the whole patient volume with grid resolution 2mm×2mm×2mm finishing in 26±5sec, and the Gamma (2%/2mm) passing was >99% for >95% of plans.
Conclusion: We developed measurement-based beam modeling and auto-commissioning, which serves the purpose of fully independent verification, and have utilized it for efficient OART QA.
Not Applicable / None Entered.