Implementation of output prediction models for a passively double-scattered proton therapy system.
OBJECTIVE
Two output (cGy/MU) prediction models (one existing and one newly developed) for a passively double-scattered proton therapy system are implemented and investigated for clinical use. Variations of each model are tested for accuracy in order to determine the most viable prediction model.


METHODS
The first output prediction model [model (1)] is a semianalytical model proposed by Kooy et al. [Phys. Med. Biol. 50, 5847-5856 (2005)], which employs three main factors. The first factor (basic output prediction) uses a unique combined parameter [r = (R - M)/M] of range (R) and modulation [M; spread-out Bragg peak (SOBP) width] along with option specific fitting parameters. The second factor takes into account minor source shifts using a linear fit due to varying beamline configurations for different options. The final factor accounts for a condition where the point of measurement is not at the isocenter or away from the middle of the SOBP based on an inverse-square correction. The second model [model (2)] is a novel quartic polynomial fit of the basic output prediction whose idea was inspired by the first model. Different variations in the definition of R and M at distal (D) and proximal (P) ends resulted in the exploration of three variations of r for both models: r1= (RD90- MD90-P95)/MD90-P95, r2= [(RD90+ ΔR1) - m × (MD90-P95+ ΔR1)]/[m × (MD90-P95+ ΔR1)], where ΔR1is an offset between RD80and RD90and m is a ratio between MD90-P95and theoretical MD100-P100', and r3= [(RD90- 0.305) - 0.801 × MD90-P95]/(0.801 × MD90-P95), where 0.305 (ΔR2) is an offset between RD90and RD100and 0.801 is a ratio between MD90-P95and measured MD100-P100. Output measurements for 177 sets of R and M from all 24 options are compared to outputs predicted by both the models of three variations of r.


RESULTS
The mean differences between measurements and predictions ([predicted - measured]/measured × 100%) were -0.41% ± 1.78% (r1), 0.03% ± 1.53% (r2), and 0.05% ± 1.20% (r3) for model (1), and 0.27% ± 1.36% (r1), 0.71% ± 1.51% (r2), and -0.05% ± 1.20% (r3) for model (2). For a passing prediction rate with a difference threshold of ±3%, model (1) showed slightly worse results than model (2) using r1(91.5% vs 94.4%). In general, small (M < 4 g/cm2) and close-to-full modulations produced larger discrepancies. However, 100% output predictions using r3were confined within ±3% of measurements for both models and the difference between the models was not substantial (mean difference: 0.05% vs -0.05%).


CONCLUSIONS
The first existing model has proven to be a successful predictor of output for our compact double-scattering proton therapy system. The new model performed comparably to the first model and showed better performance in some options due to a great degree of flexibility of a polynomial fit. Both models performed well using r3. Either model with r3thus can serve well as an output prediction calculator.
Department of Radiation Oncology, Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma 73104.
Sven
S
Ferguson
Department of Radiation Oncology, Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma 73104.
Salahuddin
S
Ahmad
Department of Radiation Oncology, Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma 73104.
Hosang
H
Jin
D006801:Humans; D008954:Models, Biological; D061766:Proton Therapy; D011879:Radiotherapy Dosage; D012542:Scattering, Radiation