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Positron Emission Tomography (PET) is a medical imaging technique that provides crucial insights into the body's physiological functions at a molecular level. It is an indispensable resource for diagnosing, staging, and monitoring various illnesses, notably cancer, neurological disorders, and cardiovascular conditions.
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First application of the GPU-based software framework TIGRE for proton CT image reconstruction.

Stefanie Kaser1, Thomas Bergauer1, Wolfgang Birkfellner2

  • 1Institute of High Energy Physics, Austrian Academy of Sciences, Vienna, Austria.

Physica Medica : PM : an International Journal Devoted to the Applications of Physics to Medicine and Biology : Official Journal of the Italian Association of Biomedical Physics (AIFB)
|April 13, 2021
PubMed
Summary

This study demonstrates that the TIGRE software toolkit can reconstruct proton computed tomography (pCT) images quickly using a simplified proton path approximation. This method enables rapid pCT image generation for proton therapy planning.

Keywords:
Image reconstructionProton computed tomographyTIGRE

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Area of Science:

  • Medical Physics
  • Computational Imaging
  • Radiotherapy Physics

Background:

  • Accurate proton stopping power determination is crucial for proton therapy planning.
  • Proton computed tomography (pCT) offers direct measurement of stopping power but faces reconstruction challenges.
  • Proton path variability complicates pCT image reconstruction.

Purpose of the Study:

  • To evaluate the applicability of the GPU-based TIGRE software toolkit for proton computed tomography (pCT) image reconstruction.
  • To assess the feasibility of using a straight-line proton path approximation within TIGRE for pCT.
  • To determine the reconstruction speed and potential for clinical application of TIGRE in pCT.

Main Methods:

  • Utilized the TIGRE (Tomographic Reconstruction toolkit) software, originally for X-ray CT, for pCT reconstruction.
  • Employed a straight-line approximation for proton paths to simplify the reconstruction problem.
  • Performed Monte Carlo simulations of a pCT setup with Catphan® phantoms.
  • Implemented Ordered-Subset Simultaneous Algebraic Reconstruction Technique (OS-SART) and Adaptive-Steepest-Descent Projection Onto Convex Sets (ASD-POCS) algorithms.

Main Results:

  • Demonstrated that TIGRE can perform pCT image reconstruction within seconds using the straight-line proton path approach.
  • Validated the TIGRE toolkit's capability to reconstruct images from simulated pCT data.
  • Identified limitations due to the straight-line approximation, suggesting areas for future software enhancement.

Conclusions:

  • The TIGRE toolkit is a viable option for rapid pCT image reconstruction, offering potential for faster treatment planning.
  • Further development of TIGRE is needed to incorporate more accurate proton path modeling for improved accuracy in pCT.
  • The straight-line approach provides a fast baseline for pCT reconstruction, paving the way for more sophisticated algorithms.