Evaluation of QA dosimetry system for SRS and SBRT patient-specific QA.

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Conference Proceeding

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Med Phys


Purpose: Mobius 3D (M3D) provides a volumetric dose verification of the treatment planning system's predicted dose using an independent beam model and a collapsed cone convolution superposition algorithm. However, there is a lack of investigation into M3D's accuracy and effectiveness for stereotactic radiosurgery (SRS) and stereotactic body radiotherapy (SBRT) quality assurance (QA). Here we developed a new M3D beam model for SRS/SBRT treatments that use a 6X Flattening Filter Free (FFF) beam and high definition multiple leaf collimator (HD-MLC) on an Edge linear accelerator. Methods: Eighty SRS/SBRT cases, planned with AAA dose algorithm and validated with Gafchromic film, were compared to M3D dose predictions using 3D gamma analysis with 2% 2mm gamma criteria and a 10% threshold. A new beam model was developed by refining the HD-MLC model in M3D to improve small field dose calculation accuracy and beam profile agreement. Fifty SRS/SBRT cases were reanalyzed using the new beam model. The impact of heterogeneity corrections for lung cases was investigated by applying lung density overrides to 5 cases. Results: For the original and new beam models, respectively, the mean gamma passing rates were 94.6%±6.1% and 98.0%±1.8% (for the overall patient), 88.2%±17.3% and 98.8%±2.0% (for the brain PTV), and 71.4%±18.4% and 84.3%±10.4% (for the lung PTV). The lung PTV mean gamma passing rates improved from 74.1%±7.5% to 89.3%±7.2% with the lung density overridden. The difference in output factors for a 0.5× 0.5 cm2 MLC field relative to plastic scintillator measurements was 102.0% for the original M3D model, but reduced to 21.3% with the new model. Conclusion: Special attention needs to be paid to small field dosimetry, MLC modeling, and inhomogeneity corrections in the beam model for SRS/SBRT QA. Improvements noted in this study, and further refinements of the M3D beam model will enable M3D to become a premier SRS/SBRT QA tool.



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