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Estimation of Monte Carlos Algorithm with MapCHECK2 Diode Array for Electron Beam Radiotherapy

K Li1*, (1) Varian Medical System, Hagerstown, MD

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PO-GePV-P-12 (Sunday, 7/10/2022)   [Eastern Time (GMT-4)]

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Purpose: A MapCHECK® 2 diode array for electron beam profile consistency check was applied in evaluation of Monte Carlo Algorithm for large apertures electron beam simulation.

Methods: The MapCHECK® 2 from Sun Nuclear Cooperation was firstly scanned with a General Electric LightSpeed Plus 4 slice CT simulator. The image set was sent to Eclipse treatment planning system. A standard 15cmx15cm cone field was used for calibration based on the treatment plan simulation result with Monte Carlo algorithms. The profile absolute dose was determined in different depth of a homogeneity phantom equivalent to water. Then the measured profiles were compared to treatment plan profile exported from the Eclipse treatment planning system at different depths. A binary search algorithm was employed to select the depths to minimize the difference between measurement results with those of the treatment planning simulations. The process was done at 06MeV, 09MeV, 12MeV, 16MeV and 20MeV electron beams with both 15cmx15cm cone and 20x20 cone. The analysis were done with SunNuclear Patient software.

Results: For the selected machine model in this study, with the gamma setting at 2% dose difference tolerance and 2mm in distance at relative dose mode, the resulted pass rate between the measured and computed profiles at 6MeV, 9MeV, 12MeV, 16MeV and 20 MeV electron beam, were at 56.7%, 73.6%, 83.9%, 87.7% and 91.3%; and for 20x20 cone were 49.1%, 68.6%, 85.5%, 77.0% and 78.3%.

Conclusion: A MapCHECK® 2 diode array could be applied to electron beam profile consistency check. And analogy approach provides a tactics in evaluation the inhomogeneity for electron beam simulation based on Monte Carlo algorithm. Furthermore, profile similarity Improvement may depend on accurate calibration of diode array response. Finally, calculation options such as smoothing method and statistical setting could be developed to automatically generate an optimal application condition.

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