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Purpose  Treatment planning system (TPS) dose calculations have previously been shown to be sensitive to modeling errors, especially when treating with complex strategies like intensity‐modulated radiation therapy (IMRT). This work investigates the dosimetric impact of several dosimetric and nondosimetric beam modeling parameters, based on their distribution in the radiotherapy community, in two commercial TPSs in order to understand the realistic potential for dose deviations and their clinical effects.    Methods and materials  Beam models representing standard 120‐leaf Varian Clinac‐type machines were developed in Eclipse 13.5 (AAA algorithm) and RayStation 9A (v8.99, collapsed‐cone algorithm) based upon median values of dosimetric measurements from Imaging and Radiation Oncology Core (IROC) Houston site visit data and community beam modeling parameter survey data in order to represent a baseline linear accelerator. Five clinically acceptable treatment plans (three IMRT, two VMAT) were developed for the IROC head and neck phantom. Dose distributions for each plan were recalculated after individually modifying parameters of interest (e.g., MLC transmission, percent depth doses [PDDs], and output factors) according to the 2.5th to 97.5 th  percentiles of community survey and machine performance data to encompass the realistic extent of variance in the radiotherapy community. The resultant dose distributions were evaluated by examining relative changes in average dose for thermoluminescent dosimeter (TLD) locations across the two target volumes and organ at risk (OAR). Interplay was also examined for parameters generating changes in target dose greater than 1%.    Results  For Eclipse, dose calculations were sensitive to changes in the dosimetric leaf gap (DLG), which resulted in differences from −5% to +3% to the targets relative to the baseline beam model. Modifying the MLC transmission factor introduced differences up to ± 1%. For RayStation, parameters determining MLC behaviors likewise contributed substantially; the MLC offset introduced changes in dose from −4% to +7%, and the MLC transmission caused changes of −4% to +2%. Among the dosimetric qualities examined, changes in PDD implementation resulted in the most substantial changes, but these were only up to ±1%. Other dosimetric factors had &lt;1% impact on dose accuracy. Interplay between impactful parameters was found to be minimal.    Conclusion  Factors related to the modeling of the MLC, particularly relating to the leaf offset, can cause clinically significant changes in the calculated dose for IMRT and VMAT plans. This should be of concern to the radiotherapy community because the clinical effects of poor TPS commissioning were based on reported data from clinically implemented beam models. These results further reinforce that dose errors caused by poor TPS calculations are often involved in IROC phantom failures.

Sensitivity of IROC phantom performance to radiotherapy treatment planning system beam modeling parameters based on community‐driven data