Performance evaluation of the Q.Clear reconstruction framework versus conventional reconstruction algorithms for quantitative brain PET-MR studies

EJNMMI Physics

Adriana A. S. Tavares¹  William Hallett²  Daniela Ribeiro³ 

[1] Edinburgh Imaging, University of Edinburgh, Edinburgh, UK;University/BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK;Invicro, Centre for Imaging Sciences, Hammersmith Hospital, London, United Kingdom;Invicro, Centre for Imaging Sciences, Hammersmith Hospital, London, United Kingdom;Edinburgh Imaging, University of Edinburgh, Edinburgh, UK;

关键词: PET-MR;    Reconstruction;    Bayesian;    Brain imaging;   

DOI  :  10.1186/s40658-021-00386-3

来源: Springer

【 摘 要 】

BackgroundQ.Clear is a Bayesian penalized likelihood (BPL) reconstruction algorithm that presents improvements in signal-to-noise ratio (SNR) in clinical positron emission tomography (PET) scans. Brain studies in research require a reconstruction that provides a good spatial resolution and accentuates contrast features however, filtered back-projection (FBP) reconstruction is not available on GE SIGNA PET-Magnetic Resonance (PET-MR) and studies have been reconstructed with an ordered subset expectation maximization (OSEM) algorithm. This study aims to propose a strategy to approximate brain PET quantitative outcomes obtained from images reconstructed with Q.Clear versus traditional FBP and OSEM.MethodsContrast recovery and background variability were investigated with the National Electrical Manufacturers Association (NEMA) Image Quality (IQ) phantom. Resolution, axial uniformity and SNR were investigated using the Hoffman phantom. Both phantoms were scanned on a Siemens Biograph 6 TruePoint PET-Computed Tomography (CT) and a General Electric SIGNA PET-MR, for FBP, OSEM and Q.Clear. Differences between the metrics obtained with Q.Clear with different β values and FBP obtained on the PET-CT were determined.ResultsFor in plane and axial resolution, Q.Clear with low β values presented the best results, whereas for SNR Q.Clear with higher β gave the best results. The uniformity results are greatly impacted by the β value, where β < 600 can yield worse uniformity results compared with the FBP reconstruction.ConclusionThis study shows that Q.Clear improves contrast recovery and provides better resolution and SNR, in comparison to OSEM, on the PET-MR. When using low β values, Q.Clear can provide similar results to the ones obtained with traditional FBP reconstruction, suggesting it can be used for quantitative brain PET kinetic modelling studies.

【 授权许可】

CC BY