Development of a Monte Carlo Based Prediction Tool for Cherenkov Emission for Breast Radiotherapy
Abstract
Purpose
Cherenkov imaging enables real-time visualization of radiation delivery by capturing Cherenkov emission from patient tissue at the beam location. Although this signal can be compared to the expected dose distribution, no established method currently exists to compare Cherenkov emission with a patient-specific prediction of Cherenkov distribution. Such a comparison tool would strengthen the clinical utility of Cherenkov imaging, particularly for highly modulated treatments with numerous small beamlets, where an observed reduction of Cherenkov signal and increased setup complexity make real-time interpretation more challenging.
Methods
A Monte Carlo based prediction tool was developed to estimate Cherenkov emission at each control point of a treatment plan using patient CT data and corresponding beam parameters. The tool leverages the radiation and optical transport capabilities of the Tool for Particle Simulation (TOPAS). Predicted treatment plan dose distributions and Cherenkov emissions were evaluated for multiple breast radiotherapy techniques, including a simple two-tangent plan and a highly modulated VMAT plan. Predicted Cherenkov images were compared with experimentally acquired Cherenkov images for validation.
Results
The Monte Carlo tool accurately predicted Cherenkov emission patterns across a range of breast treatment techniques. Agreement between predicted and clinically imaged Cherenkov distributions demonstrated that patient-specific CT geometry and treatment plan information can be used to generate realistic Cherenkov emission maps, even for complex, modulated deliveries.
Conclusion
Predicting Cherenkov emission for individual treatment plans provides a reference for real-time Cherenkov imaging, enhancing its value for treatment verification. This capability is especially beneficial for highly modulated plans with small beamlets, where reduced signal and complex fluence patterns make real-time interpretation more challenging. Incorporating predicted Cherenkov emission into clinical workflows may improve treatment safety, support more robust verification, and strengthen confidence in delivery accuracy for complex radiotherapy techniques.