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A maximum likelihood proton path formalism for application in proton computed tomography.

R W Schulte1, S N Penfold, J T Tafas

  • 1Department of Radiation Medicine, Loma Linda University Medical Center, Loma Linda, California 92354, USA. rschulte@dominion.llumc.edu

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This study introduces a new mathematical model for proton computed tomography (pCT) to improve image resolution. The most likely path (MLP) formalism accurately predicts proton paths, enhancing pCT imaging capabilities.

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Area of Science:

  • Medical Physics
  • Radiological Imaging
  • Computational Physics

Background:

  • Proton computed tomography (pCT) offers potential advantages over x-ray CT but is limited by spatial resolution.
  • Multiple Coulomb scattering (MCS) of protons within the patient is a primary cause of reduced pCT resolution.
  • Accurate modeling of proton trajectories is crucial for reconstructing high-resolution pCT images.

Purpose of the Study:

  • To develop a compact and flexible mathematical formalism for modeling MCS effects in pCT.
  • To present a matrix-based most likely path (MLP) formalism using Bayesian statistics and a Gaussian approximation of MCS.
  • To evaluate the accuracy of the MLP formalism in predicting proton paths.

Main Methods:

  • Development of a matrix-based MLP formalism incorporating Bayesian statistics and Gaussian MCS approximation.
  • Utilizing GEANT4 simulations to model proton transport through a homogeneous 20 cm water cube.
  • Applying 3-sigma cuts on relative exit angle and energy to filter proton tracks.

Main Results:

  • The MLP formalism accurately predicted Monte Carlo proton tracks with an average error of 0.6 mm for 200 MeV protons.
  • The applied 3-sigma cuts effectively removed outlier proton tracks inconsistent with the Gaussian MCS model.
  • The developed formalism provides a computationally efficient method for pCT reconstruction.

Conclusions:

  • The matrix-based MLP formalism is a viable and accurate method for modeling proton scattering in pCT.
  • This approach has the potential to significantly improve spatial resolution in pCT imaging.
  • The MLP formalism facilitates efficient image reconstruction for advanced pCT systems.