Author: Chang Chang, Mohammad Kanber, Stephen Kenneth Northway 👨🔬
Affiliation: East Carolina University, California Protons Cancer Therapy Center, California Proton Cancer Therapy Center 🌍
Purpose:
Proton therapy treatment planning involves the consideration of unique physical quantities such as Linear Energy Transfer (LET) and spot location maps that do not exist in photon treatment planning. Visualization of these treatment-related dosimetric parameters can help planners in their design of treatment plans to enhance patient outcomes. This study presents a tool designed to visualize LET and spot distributions in 3D, overlaid within a patient’s CT volume. The LET values were derived from Monte Carlo simulations, and spot maps were calculated from the proton treatment plan using ray-tracing.
Methods:
The tool integrates a fast ray-tracing algorithms in C with the OpenTPS toolkit written in Python. Ray tracing, with divergent beams of finite source-to-axis distance (SAD), iteratively calculated voxel-specific water-equivalent depth (WED) along the ray path until the spot reaches the 80% range (R80) of the designed proton energy. Clinical relative stopping power (RSP) to Hounsfield unit (HU) calibration curve calibrated to our simulation CT is used to calculate the WED.
LET distributions were computed using a Monte Carlo engine based on OpenMCSquare. Spot visualization is constructed based on the spot’s monitor unit (MU) values, with the spot’s radius proportional to its MU. Spot computation is parallelized with OpenMP, enabling simultaneous updates and faster display of 3D grid data. The final spot map was superimposed on the CT image, providing a complete visualizations of proton spot distributions.
Results:
The tool provided accurate 3D spot maps aligned with CT, Dose and LET distributions, with options to visualize spot locations per proton energy layer. An interactive user interface also enables real-time adjustments of user preferences.
Conclusion:
The visualization tool displays the physical quantities of LET, spot locations, dose and contours together within CT volumes. This tool aids proton therapy treatment planning and evaluation, improving clinical workflows.