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An automatic pipeline for PET/MRI attenuation correction validation in the brain.

Mahdjoub Hamdi1, Chunwei Ying2, Hongyu An2,3,4,5

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Summary

This study introduces an automated pipeline for evaluating MRI-based PET attenuation correction (AC) methods in neurological imaging. The DL-DIXON method demonstrated the least quantitative bias, offering improved accuracy for PET/MRI scans.

Keywords:
FreeSurfer brain atlasPET attenuation correctionPET/CTPET/MRIQuantitative brain PETVirtual synthetic PET imaging

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Area of Science:

  • Neuroimaging
  • Medical Physics
  • Radiochemistry

Background:

  • Accurate Positron Emission Tomography (PET) attenuation correction (AC) is crucial for quantitative accuracy in neurological PET/MRI applications.
  • Existing MRI-derived PET AC methods face challenges in achieving precise quantitative results.
  • The development of robust evaluation pipelines is necessary to assess novel AC techniques.

Purpose of the Study:

  • To propose and evaluate an automated pipeline for assessing the quantitative accuracy of four MRI-derived PET AC methods.
  • To utilize analytically simulated PET brain lesions and Regions of Interest (ROIs) as ground truth for PET activity.
  • To compare the performance of DIXON, DIXONbone, UTE AC, and DL-DIXON against the gold standard PET CTAC.

Main Methods:

  • An automated pipeline was developed, integrating a synthetic lesion insertion tool and the FreeSurfer neuroimaging framework.
  • Simulated spherical lesions and ROIs were inserted into PET projection space and reconstructed using four MRI-based AC techniques.
  • Quantitative accuracy was evaluated by comparing MRI-based AC to CTAC biases in lesions and ROIs, with and without background activity.

Main Results:

  • The pipeline accurately assessed quantitative accuracy for simulated lesions and ROIs, consistent with original PET images.
  • DL-DIXON exhibited the least bias (-0.08% to 0.22%) across evaluated conditions, followed by DIXONbone (-1.85% to -2.46%), UTE AC (-2.74% to -3.56%), and DIXON (-5.41% to -7.02%).
  • The DL-DIXON method demonstrated superior quantitative accuracy compared to other MRI-derived AC techniques evaluated.

Conclusions:

  • The proposed automated pipeline accurately evaluates MRI-derived PET AC methods without requiring measured PET emission data.
  • The pipeline enables consistent generation of realistic lesion ROIs for assessing novel PET correction techniques.
  • DL-DIXON shows the most promising results for accurate PET attenuation correction in neurological applications using MRI-derived data.