Implementation of output prediction models for a passively double‐scattered proton therapy system. Issue 11 (24th October 2016)

• Record Type: Journal Article
• Authors: Ferguson, Sven; Ahmad, Salahuddin; Jin, Hosang
• Is Part Of: Medical physics. Volume 43:Issue 11(2016)
• Page Start: 6089
• Page End: 6097
• Publication Date: 2016-10-24
• Subjects: dosimetry -- polynomials -- radiation therapy; Therapeutic applications, including brachytherapy -- Dose‐volume analysis -- Algebraic structures and number theory; Radiation therapy; proton therapy -- output model -- compact proton therapy system; Calibration -- Computer modeling -- Proton therapy -- Field size -- Protons -- Polynomials -- Inverse scattering -- Modulators -- Medical treatment planning -- Reference fields; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4965046
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: 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: r 1 = ( R D 90 − M D 90− P 95 )/ M D 90− P 95, r 2 = [( R D 90 + Δ R 1 ) − m × ( M D 90− P 95 + Δ R 1 )]/[ m × ( M D 90− P 95 + Δ R 1 )], where Δ R 1 is an offset between R D 80 and R D 90 and m is a ratio between M D 90− P 95 and theoretical M D 100 − P 100 ′, and r 3 = [( R D 90 − 0.305) − 0.801 × M D 90− P 95 ]/(0.801 × M D 90− P 95 ), where 0.305 (Δ R 2 ) is an offset between R D 90 and R D 100 and 0.801 is a ratio between M D 90− P 95 and measured M D 100− P 100 . 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% ( r 1 ), 0.03% ± 1.53% ( r 2 ), and 0.05% ± 1.20% ( r 3 ) for model (1), and 0.27% ± 1.36% ( r 1 ), 0.71% ± 1.51% ( r 2 ), and −0.05% ± 1.20% ( r 3 ) for model (2). For a passing prediction rate with a difference threshold of ±3%, model (1) showed slightly worse results than model (2) using r 1 (91.5% vs 94.4%). In general, small ( M < 4 g/cm 2 ) and close‐to‐full modulations produced larger discrepancies. However, 100% output predictions using r 3 were 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 r 3 . Either model with r 3 thus can serve well as an output prediction calculator.