Validation of spline modeling for calculation of electron insert factors for varian linear accelerators

Abstract

There are several methods available in the literature for predicting the insert factor for clinical electron beams. The purpose of this work was to build on a previously published technique that uses a bivariate spline model generated from elliptically parameterized empirical measurements. The technique has been previously validated for Elekta linear accelerators for limited clinical electron setups. The same model is applied to Varian machines to test its efficacy for use with these linear accelerators. Insert factors for specifically designed elliptical cutouts were measured to create spline models for 6, 9, 12, 16, and 20 MeV electron energies for four different cone sizes at source-to-surface distances (SSD) of 100, 105, and 110 cm. Insert factor validation measurements of patient cutouts and clinical standard cutouts were acquired to compare to model predictions. Agreement between predicted insert factors and validation measurements averaged 0.8% over all energies, cones, and clinical SSDs, with an uncertainty of 0.6% (1SD), and maximum deviation of 2.1%. The model demonstrated accurate predictions of insert factors using the minimum required amount of input data for small cones, with more input measurements required for larger cones. The results of this study provide expanded validation of this technique to predict insert factors for all energies, cones, and SSDs that would be used in most clinical situations. This level of accuracy and the ease of creating the model necessary for the insert factor predictions demonstrate its acceptability to use clinically for Varian machines.

PyMedPhys: A community effort to develop an open, Python-based standard library for medical physics applications

“…Many of these tools are in use clinically at affiliated sites, and additionally, aspects of PyMedPhys are implemented around the world for some applications. Many parties have embraced the gamma analysis module (Castle et al, 2022;Cronholm et al, 2020;Gajewski et al, 2021;Galić et al, 2020;Lysakovski et al, 2021;Milan et al, 2019;Pastor-Serrano & Perkó, 2021;Rodrıǵuez et al, 2020;Spezialetti et al, 2021;Tsuneda et al, 2021;Yang et al, 2022), while implementations of the electron cutout factor module and others (Baltz & Kirsner, 2021;Douglass & Keal, 2021;Rembish, 2021) have also been reported. Additionally, the work has been recognized by the European Society for Radiotherapy and Oncology (ESTRO) and referenced as recommended literature in their 3rd Edition of Core Curriculum for Medical Physics Experts in Radiotherapy (Bert et al, 2021).…”