Online dose reconstruction for tracked volumetric arc therapy: Real-time implementation and offline quality assurance for prostate SBRT.
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<h4>Purpose</h4>Firstly, this study provides a real-time implementation of online dose reconstruction for tracked volumetric arc therapy (VMAT). Secondly, this study describes a novel offline quality assurance tool, based on commercial dose calculation algorithms.<h4>Methods</h4>Online dose reconstruction for VMAT is a computationally challenging task in terms of computer memory usage and calculation speed. To potentially reduce the amount of memory used, we analyzed the impact of beam angle sampling for dose calculation on the accuracy of the dose distribution. To establish the performance of the method, we planned two single-arc VMAT prostate stereotactic body radiation therapy cases for delivery with dynamic MLC tracking. For quality assurance of our online dose reconstruction method we have also developed a stand-alone offline dose reconstruction tool, which utilizes the RayStation treatment planning system to calculate dose.<h4>Results</h4>For the online reconstructed dose distributions of the tracked deliveries, we could establish strong resemblance for 72 and 36 beam co-planar equidistant beam samples with less than 1.2% deviation for the assessed dose-volume indicators (clinical target volume D98 and D2, and rectum D2). We could achieve average runtimes of 28-31 ms per reported MLC aperture for both dose computation and accumulation, meeting our real-time requirement. To cross-validate the offline tool, we have compared the planned dose to the offline reconstructed dose for static deliveries and found excellent agreement (3%/3 mm global gamma passing rates of 99.8%-100%).<h4>Conclusion</h4>Being able to reconstruct dose during delivery enables online quality assurance and online replanning strategies for VMAT. The offline quality assurance tool provides the means to validate novel online dose reconstruction applications using a commercial dose calculation engine.
The Institute of Cancer Research (Grant ID: Unspecified)
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Radiotherapy Planning, Computer-Assisted
Radiotherapy Physics Modelling
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Medical physics, 2017, 44 (11), pp. 5997 - 6007