Abstract
Purpose:Dynamic electron radiation therapies such as dynamic electron arc radiotherapy (DEAR) utilize small fields to provide target conformity and fluence modulation. The purpose of this study is to demonstrate the feasibility of virtual scanning mode using small fields.Methods:Monte Carlo simulations (EGSnrc/BEAMnrc/DOSXYZnrc) were performed using validated Varian TrueBeam phase space files for electron beam energies of 6, 9, 12, and 16 MeV and square/circular fields (1×1/1, 2×2/2, 3×3/3, 4×4/4, 5×5/5 cm2/cm diameter). Resulting dose distributions (kernels) were used for subsequent calculations. The following analyses were performed: (1) Comparison of composite square fields and reference 10×10 cm2 dose distributions and (2) Scanning beam deliveries for square and circular fields realized as the convolution of kernels and scanning pattern. Preliminary beam weight and pattern optimization were also performed. Two linear scans of 10 cm with/without overlap were modeled. Comparison metrics included depth and orthogonal profiles at dmax.Results:(1) Composite fields regained reference depth dose profiles for most energies and fields within 5%. Smaller kernels and higher energies increased dose in the build‐up and Bremsstrahlung region (30%, 16MeV and 1×1 cm2), while reference dmax was maintained for all energies and composite fields. Smaller kernels (<2×2 cm2) maintained penumbra and field size within 0.2 cm, and flatness within 2%. Deterioration of penumbra for larger kernels (5×5 cm2) were observed. Balancing desirable dosimetry and efficiencies suggests that smaller kernels are used at edges and larger kernels in the center of the target. (2) Beam weight optimization improved cross‐plane penumbra (0.2 cm) and increased the field size (0.4 cm) on average. In‐plane penumbra and field size remained unchanged. Overlap depended on kernel size and optimal overlap resulted in flatness ±2%.Conclusion:Dynamic electron beam therapy in virtual scanning mode is feasible by employing small fields to achieve desired dose distributions and acceptable efficiencies.
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