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Transmission imaging for integrated PET-MR systems.

Spencer L Bowen1, Niccolò Fuin, Michael A Levine

  • 1Athinoula A. Martinos Center for Biomedical Imaging, Bldg. 149, Rm. 2301, 13th St., Charlestown, MA 02129, USA.

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This study introduces a novel emission-free transmission imaging method for PET-MR systems, enhancing attenuation correction accuracy. The new technique improves quantitative accuracy and reduces artifacts, particularly for challenging imaging scenarios like patient implants.

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Area of Science:

  • Medical Physics
  • Nuclear Medicine
  • Biomedical Imaging

Background:

  • Attenuation correction in PET-MR is challenging, especially outside the head.
  • Integrated PET-MR systems offer opportunities for validating MR-based attenuation correction algorithms.
  • Conventional transmission scanning is impractical on the Biograph mMR due to hardware limitations.

Purpose of the Study:

  • To develop and validate an emission-free transmission imaging method for the Biograph mMR PET-MR system.
  • To improve MR-based attenuation correction (μ-map) algorithms, particularly for implants and scanner hardware.
  • To assess the performance of a novel source geometry and reconstruction technique.

Main Methods:

  • Optimized a single torus radioactive source geometry for emission-free coincidence transmission imaging.
  • Employed a Bayesian reconstruction algorithm with scatter correction for μ-map generation.
  • Validated the method using Monte Carlo simulations and phantom scans (pelvis, hip implant, uniform cylinder).

Main Results:

  • The single torus source achieved higher noise equivalent count rates than conventional configurations.
  • Reconstructed μ-maps showed low bias (≤4% soft tissue, ≤11% bone).
  • The method demonstrated improved quantitative accuracy and reduced artifacts compared to CT-derived μ-maps, especially for implants and the patient table.

Conclusions:

  • The proposed emission-free transmission imaging method with a fixed torus geometry provides highly quantitative μ-maps for PET-MR.
  • This approach is expected to yield higher signal-to-noise ratio images compared to other fixed geometries.
  • The method is crucial for validating and improving MR-based attenuation correction algorithms in challenging clinical scenarios.