Purpose: Stereotactic radiotherapy is susceptible to dose delivery errors that must be minimized by precise quality assurance, such as independent dose calculation. Recently, SciMoCa (IBA Dosimetry, DE), a commercial independent dose calculation software based on the Monte Carlo method, has become available. To the best of our knowledge, no studies have validated the independent dose recalculation using SciMoCa for brain metastases and lung cancer plans in the CyberKnife. Therefore, this study aimed to evaluate and compare the dose measured by an ion chamber for brain metastases and lung cancer plans with the dose distribution calculated by SciMoCa and the treatment planning system (TPS).
Methods: A set of 250 (200 brain metastases and 50 lung cancer) plans were retrospectively recalculated using SciMoCa. Among them, a set of 40 measurements for brain metastasis and lung cancer plans was compared to the dose measured by a PTW31010 cylindrical chamber (PTW, Freiburg, Germany). Dose distribution was assessed by the differences in gamma passing rates (GPR) from gamma analysis with 3%/1 mm and with 10% threshold criteria.
Results: All relative dose differences were within 5%, except for the five fraction brain metastases plans. The mean and standard deviation of the GPR obtained using SciMoCa were 98.7% ± 1.5% and 96.7% ± 7.8% for the brain metastases and lung cancer plans, respectively. However, 24 (15 brain metastases and 9 lung cancer) plans failed to achieve a GPR of >95%.
Conclusion: Our study demonstrated excellent agreement between the SciMoCa and TPS measurements, except for certain brain metastases and lung cancer plans. In the case of ion chamber measurements, the calculated results may differ from the actual measurements at high-dose gradients where lateral electronic equilibrium is not satisfied. Intercomparison studies with detectors in high-dose gradient regions should be used to validate our results in the future.
Monte Carlo, Stereotactic Radiosurgery, Quality Assurance
TH- External Beam- Photons: Computational dosimetry engines- Monte Carlo