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A Simple Virtual Source Model for Monte Carlo Simulation of Helical TomoTherapy


J Yuan

J Yuan1*, Q Chen2, (1) University Hospitals Case Medical Center, Solon, OH, (2) University of Virginia, Charlottesville, VA

SU-E-T-374 Sunday 3:00PM - 6:00PM Room: Exhibit Hall

Purpose: To present a methodology based on a simplified source, jaw, and MLC model to simulate helical TomoTherapy with the MC method without using detailed phase-space files (PSFs).
Methods and Materials: Current studies on Monte Carlo (MC) simulation for helical TomoTherapy adopt a full MC model and use PSFs at different scoring planes to facilitate patient dose calculations. The purpose of this work is to develop a simple virtual source model (VSM) to calculate the patient dose for helical TomoTherapy with the MC method. The VSM is based on the commissioning data of helical TomoTherapy unit, which can be exported from the treatment planning station (TPS). To calculate the patient dose distribution, the TPS-generated sinogram is first extracted from an archived patient XML file. Next, a fluence map is created by incorporating the open-close leaf time contained in the sinogram file with leaf filter, jaw penumbra, and leaf latency. The VSM was validated for various geometrical set-ups including open fields, heterogeneous media, and clinical DQA cases.
Results: Good agreement was achieved for both transverse and longitudinal profiles between MC calculations and measurements with differences within 2%/2 mm. For MLC validation that compared MC calculations with film measurement, the passing rate was 96.4% using a gamma index analysis tool (2%/1 mm acceptance criteria). A DQA plan was simulated for a clinical head-and-neck plan. The patient dose from the MC simulation agrees with the TPS result very well (γavg [1%, 2mm] = 0.7). Good agreements between the planar patient dose distributions from the MC simulations and the TPS were observed as well (γavg [3%, 2mm] = 0.4, passing rate = 94.7%).
Conclusion: A simple VSM can be used in the MC method to accurately simulate the patient dose distributions for helical TomoTherapy.


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