Effect of a Bayesian Penalized Likelihood PET Reconstruction Compared With Ordered Subset Expectation Maximization on
Anna K Chilcott1,2, Kevin M Bradley3, Daniel R McGowan1,4
11 Radiation Physics and Protection, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, United Kingdom.
Objective:
A study was performed to compare background liver signal-to-noise ratio (SNR) and visually assessed image quality of clinical PET/CT studies from the same PET acquisition data reconstructed by Bayesian penalized likelihood (BPL) and ordered subset expectation maximization (OSEM) over a range of patient weights.
Materials And Methods:
The effect of a BPL PET reconstruction algorithm on liver SNR and visually assessed image quality over a range of patient weights (41-196 kg; n = 108) was retrospectively compared with standard-of-care OSEM reconstruction on the same PET acquisition data after IV administration of 18F-FDG (4 MBq/kg).
Results:
BPL showed no significant change (p > 0.05) in liver SNR with increasing weight and body mass index (BMI), whereas OSEM showed increasing noise with increasing weight and BMI. The liver SNR was significantly higher using BPL than a standard OSEM reconstruction (p < 0.0002 for all BMI groups). Visually assessed image quality declined at a greater rate with increasing weight and BMI in the OSEM images than with BPL images.
Conclusion:
BPL provides a more consistent visually assessed image quality and liver background SNR than does OSEM, with the greatest benefit for the heaviest patients.
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