Implementation of Raystion Photon Monte Carlo As a Method to Initiate Clinical Expertise for MR-Guided Adaptive Radiotherapy
Abstract
Purpose
Unity MR-guided adaptive radiotherapy (MRgART) relies on a Monte Carlo (MC) photon dose calculation algorithm. Compared with conventional algorithms such as convolution–superposition, or collapsed cone, MC methods more accurately model radiation transport in heterogeneous media. Our previously unutilized RayStation photon Monte Carlo algorithm was assessed as a tool to ease the transition to adaptive for workflow and clinical decision-making.
Methods
Photon Monte Carlo dose calculation in RayStation was evaluated in the context of common clinical scenarios, including lung, head and neck, and stereotactic treatments, where tissue heterogeneity and small field effects are significant. Twenty-five plans were compared across various anatomical sites. Comparisons were made to conventional dose calculation approaches typically used in photon planning.
Results
The use of photon Monte Carlo in RayStation resulted in clinically relevant differences in calculated dose for 84% of assessed plans, particularly in low-density tissues, at tissue–air interfaces, and for small or highly modulated fields. Target coverage was significantly different compared with the collapsed cone algorithm, while doses to organs at risk may be recalculated more accurately. These differences influenced the selection of prescription dose, plan normalization, and clinical acceptability. Advances in computing performance have reduced MC calculation times to levels compatible with clinical workflows, although they remain longer than traditional algorithms. Plan acceptability criteria were significantly different for 34% of clinical goals assessed.
Conclusion
The incorporation of photon Monte Carlo dose calculation in RayStation has the potential to improve dosimetric accuracy and confidence in treatment planning, particularly for anatomically complex cases. However, its adoption alters historical dose benchmarks and requires careful education and clinical judgment. When implemented thoughtfully, photon Monte Carlo can enhance clinical practice by supporting more accurate and patient-specific radiotherapy planning. Moving forward, this work will serve as the foundation for evaluating Monte Carlo dose calculations in the adaptive setting.