Bragg peak prediction from quantitative proton computed tomography using different path estimates.

Area of Science:

• Medical Physics
• Radiological Imaging
• Computational Science

Background:

• Proton computed tomography (pCT) is crucial for radiation therapy planning.
• Accurate proton path estimation is essential for high-quality pCT reconstruction.
• Comparing different path estimation methods is vital for optimizing pCT performance.

Purpose of the Study:

• To evaluate the performance of straight-line path (SLP) and cubic spline path (CSP) as proton path estimates in pCT reconstruction.
• To compare SLP and CSP against the most-probable path (MPP) using GEANT4 simulations.
• To assess the impact of these path estimates on Bragg peak prediction and image accuracy.

Main Methods:

• Simulated proton transport through an imaging phantom using GEANT4.
• Constructed SLP, CSP, and MPP based on proton entrance and exit points.
• Calculated physical deviations and relative probabilities for each path estimate.
• Reconstructed pCT images and evaluated depth dose and Bragg peak accuracy.

Main Results:

• Cubic spline path (CSP) performance is comparable to the most-probable path (MPP), while straight-line path (SLP) is slightly inferior.
• Approximately 99% of CSP pixels and 90% of SLP pixels fall within the 99% probability envelope of the MPP.
• Bragg peak prediction with 1 mm accuracy is achievable even at low imaging doses (~0.1 mGy).

Conclusions:

• SLP and CSP are adequate path estimates for pCT reconstruction, similar to MPP.
• These methods can be selected for pCT reconstruction, facilitating treatment planning and range prediction in proton therapy.
• The findings support the use of simpler path estimation methods for efficient and accurate pCT.