Chilcott, Anna K., Bradley, Kevin M. ORCID: https://orcid.org/0000-0003-1911-3382 and McGowan, Daniel R.
2018.
Effect of a Bayesian penalized likelihood PET reconstruction compared with ordered subset expectation maximization on clinical image quality over a wide range of patient weights.
American Journal of Roentgenology
210
(1)
, pp. 152-157.
10.2214/AJR.17.18060
|
Abstract
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.
| Item Type: | Article |
|---|---|
| Date Type: | Publication |
| Status: | Published |
| Schools: | Schools > Medicine |
| Publisher: | American Roentgen Ray Society (ARRS) |
| ISSN: | 0361-803X |
| Date of Acceptance: | 12 July 2017 |
| Last Modified: | 07 Nov 2022 10:21 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/132000 |
Citation Data
Cited 19 times in Scopus. View in Scopus. Powered By Scopus® Data
Actions (repository staff only)
![]() |
Edit Item |





Altmetric
Altmetric