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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.

Original publication

DOI

10.2214/AJR.17.18060

Type

Journal article

Journal

AJR Am J Roentgenol

Publication Date

01/2018

Volume

210

Pages

153 - 157

Keywords

Bayesian penalized likelihood, FDG, PET/CT, ordered subset expectation maximization, signal-to-noise ratio, Adult, Aged, Algorithms, Bayes Theorem, Body Mass Index, Body Weight, Female, Fluorodeoxyglucose F18, Humans, Image Processing, Computer-Assisted, Liver, Male, Middle Aged, Obesity, Positron Emission Tomography Computed Tomography, Retrospective Studies, Signal-To-Noise Ratio, Young Adult