Evaluation of the GE Q.Clear reconstruction algorithm for quantitative brain PET-MR studies. Abstract: Introduction: In recent years, there have been significant advances in reconstruction algorithms. Q.Clear is a Bayesian penalized likelihood (BPL) reconstruction algorithm available in General Electric (GE) Positron Emission Tomography-Magnetic Resonance (PET-MR) scanners that presents improvements in signal to noise ratio (SNR) in clinical scans. This study aims to evaluate the performance of Q.Clear against the ordered subset expectation maximization (OSEM) and filtered back-projection (FBP) algorithms, in low count brain images in the PET-MR. Methods: Contrast Recovery and Background Variability were investigated with the NEMA Image Quality (IQ) phantom and Resolution, Axial Uniformity and SNR were investigated with the Hoffman phantom, in Siemens Biograph 6 TruePoint PET-Computed Tomography (CT) and GE SIGNA PET-MR, for FBP, OSEM and Q.Clear. The binding potential relative to non-displaceable volume (BPND) obtained for the Substantia Nigra (SN), Striatum (St), Globus Pallidus (GP), Thalamus (Th), Caudate (Cd) and Putamen (Pt) from seven [11C]PHNO PET-MR datasets were investigated. Intraclass correlation coefficients (ICC), repeatability coefficients (RC), coefficients of variation (CV) and bias from Bland-Altman plots were reported. Statistical analysis was conducted using a 2-way ANOVA model with correction for multiple comparisons. Results: For the Q.Clear reconstruction, as β increases the contrast recovery and background variability decrease. Additionally, low β levels provide the best resolution and high β levels provide the best uniformity and SNR results. When comparing a standard OSEM reconstruction of 6 iterations/16 subsets and 5mm filter with Q.Clear with different β values, the bias and RC were lower for Q.Clear with β100 for the SN, Th and GP and with β200 for the St, Cd and Pt. The p-values in the 2-way ANOVA model corroborate these findings. Conclusion: Quantitative brain PET studies using [11C]PHNO are more accurate when using Q.Clear with β levels lower than β400 which is the value used for clinical 18F-FDG whole-body studies. Project type: Analysis of existing data Imaging keywords: Positron emission tomography-magnetic resonance (PET-MR) Positron emission tomorography-computed tomography (PET-CT) Positron emission tomography (PET) Magnetic resonance (MR) Application / disease keywords: Medical physics Analysis & processing Supervisor(s): Dr Adriana Tavares Programme: Neuroimaging for research MSc Year: 18-19 This article was published on 2024-08-22
