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Purpose: The Bayesian penalized likelihood (BPL) reconstruction algorithm, Q.Clear, can achieve a higher signal‐to‐noise ratio on images and more accurate quantitation than ordered subset‐expectation maximization (OSEM). The reconstruction parameter (β) in BPL requires optimization according to the radiopharmaceutical tracer. The present study aimed to define the optimal β value in BPL required to diagnose Alzheimer disease from brain positron emission tomography (PET) images acquired using 18F‐fluoro‐2‐deoxy‐D‐glucose ([18F]FDG) and 11C‐labeled Pittsburg compound B ([11C]PiB). Methods: Images generated from Hoffman 3D brain and cylindrical phantoms were acquired using a Discovery PET/computed tomography (CT) 710 and reconstructed using OSEM + time‐of‐flight (TOF) under clinical conditions and BPL + TOF (β = 20–1000). Contrast was calculated from images generated by the Hoffman 3D brain phantom, and noise and uniformity were calculated from those generated by the cylindrical phantom. Five cognitively healthy controls and five patients with Alzheimer disease were assessed using [18F]FDG and [11C]PiB PET to validate the findings from the phantom study. The β values were restricted by the findings of the phantom study, then one certified nuclear medicine physician and two certified nuclear medicine technologists visually determined optimal β values by scoring the quality parameters of image contrast, image noise, cerebellar stability, and overall image quality of PET images from 1 (poor) to 5 (excellent). Results: The contrast in BPL satisfied the Japanese Society of Nuclear Medicine (JSNM) criterion of ≥55% and exceeded that of OSEM at ranges of β = 20–450 and 20–600 for [18F]FDG and [11C]PiB, respectively. The image noise in BPL satisfied the JSNM criterion of ≤15% and was below that in OSEM when β = 150–1000 and 400–1000 for [18F]FDG and [11C]PiB, respectively. The phantom study restricted the ranges of β values to 100–300 and 300–500 for [18F]FDG and [11C]PiB, respectively. The BPL scores for gray–white matter contrast and image noise, exceeded those of OSEM in [18F]FDG and [11C]PiB images regardless of β values. Visual evaluation confirmed that the optimal β values were 200 and 450 for [18F]FDG and [11C]PiB, respectively. Conclusions: The BPL achieved better image contrast and less image noise than OSEM, while maintaining quantitative standardized uptake value ratios (SUVR) due to full convergence, more rigorous noise control, and edge preservation. The optimal β values for [18F]FDG and [11C]PiB brain PET were apparently 200 and 450, respectively. The present study provides useful information about how to determine optimal β values in BPL for brain PET imaging. [ABSTRACT FROM AUTHOR]

Background: The Bayesian penalized likelihood (BPL) algorithm Q.Clear (GE Healthcare) allows fully convergent iterative reconstruction that results in better image quality and quantitative accuracy, while limiting image noise. The present study aimed to optimize BPL reconstruction parameters for 18F-NaF PET/CT images and to determine the feasibility of 18F-NaF PET/CT image acquisition over shorter durations in clinical practice. Methods: A custom-designed thoracic spine phantom consisting of several inserts, soft tissue, normal spine, and metastatic bone tumor, was scanned using a Discovery MI PET/CT scanner (GE Healthcare). The phantom allows optional adjustment of activity distribution, tumor size, and attenuation. We reconstructed PET images using OSEM + PSF + TOF (2 iterations, 17 subsets, and a 4-mm Gaussian filter), BPL + TOF (β = 200 to 700), and scan durations of 30–120 s. Signal-to-noise ratios (SNR), contrast, and coefficients of variance (CV) as image quality indicators were calculated, whereas the quantitative measures were recovery coefficients (RC) and RC linearity over a range of activity. We retrospectively analyzed images from five persons without bone metastases (male, n = 1; female, n = 4), then standardized uptake values (SUV), CV, and SNR at the 4th, 5th, and 6th thoracic vertebra were calculated in BPL + TOF (β = 400) images. Results: The optimal reconstruction parameter of the BPL was β = 400 when images were acquired at 120 s/bed. At 90 s/bed, the BPL with a β value of 400 yielded 24% and 18% higher SNR and contrast, respectively, than OSEM (2 iterations; 120 s acquisitions). The BPL was superior to OSEM in terms of RC and the RC linearity over a range of activity, regardless of scan duration. The SUVmax were lower in BPL, than in OSEM. The CV and vertebral SNR in BPL were superior to those in OSEM. Conclusions: The optimal reconstruction parameters of 18F-NaF PET/CT images acquired over different durations were determined. The BPL can reduce PET acquisition to 90 s/bed in 18F-NaF PET/CT imaging. Our results suggest that BPL (β = 400) on SiPM-based TOF PET/CT scanner maintained high image quality and quantitative accuracy even for shorter acquisition durations. [ABSTRACT FROM AUTHOR]