Impact of γ factor in the penalty function of Bayesian penalized likelihood reconstruction (Q.Clear) to achieve high-resolution PET images.

BACKGROUND: The Bayesian penalized likelihood PET reconstruction (BPL) algorithm, Q.Clear (GE Healthcare), has recently been clinically applied to clinical image reconstruction. The BPL includes a relative difference penalty (RDP) as a penalty function. The ß value that controls the behavior of RDP determines the global strength of noise suppression, whereas the γ factor in RDP controls the degree of edge preservation. The present study aimed to assess the effects of various γ factors in RDP on the ability to detect sub-centimeter lesions. METHODS: All PET data were acquired for 10 min using a Discovery MI PET/CT system (GE Healthcare). We used a NEMA IEC body phantom containing spheres with inner diameters of 10, 13, 17, 22, 28 and 37 mm and 4.0, 5.0, 6.2, 7.9, 10 and 13 mm. The target-to-background ratio of the phantom was 4:1, and the background activity concentration was 5.3 kBq/mL. We also evaluated cold spheres containing only non-radioactive water with the same background activity concentration. All images were reconstructed using BPL + time of flight (TOF). The ranges of ß values and γ factors in BPL were 50-600 and 2-20, respectively. We reconstructed PET images using the Duetto toolbox for MATLAB software. We calculated the % hot contrast recovery coefficient (CRChot) of each hot sphere, the cold CRC (CRCcold) of each cold sphere, the background variability (BV) and residual lung error (LE). We measured the full width at half maximum (FWHM) of the micro hollow hot spheres ≤ 13 mm to assess spatial resolution on the reconstructed PET images. RESULTS: The CRChot and CRCcold for different ß values and γ factors depended on the size of the small spheres. The CRChot, CRCcold and BV increased along with the γ factor. A 6.2-mm hot sphere was obvious in BPL as lower ß values and higher γ factors, whereas γ factors ≥ 10 resulted in images with increased background noise. The FWHM became smaller when the γ factor increased. CONCLUSION: High and low γ factors, respectively, preserved the edges of reconstructed PET images and promoted image smoothing. The BPL with a γ factor above the default value in Q.Clear (γ factor = 2) generated high-resolution PET images, although image noise slightly diverged. Optimizing the ß value and the γ factor in BPL enabled the detection of lesions ≤ 6.2 mm.

Evaluation of quantitative accuracy among different scatter corrections for quantitative bone SPECT/CT imaging.

Although scatter correction improves SPECT image contrast and thus image quality, the effects of quantitation accuracy under various conditions remain unclear. The present study aimed to empirically define the conditions for the optimal scatter correction of quantitative bone SPECT/CT images. Scatter correction was performed by applying dual and triple energy windows (DEW and TEW) with different sub-energy window widths, and effective scatter source estimation (ESSE) to CT-based scatter correction. Scattered radiation was corrected on images acquired using a triple line source (TLSP) phantom and an uniform cylinder phantom. The TLSP consisted of a line source containing 74.0 MBq of 99mTc in the middle, and a background component containing air, water or a K2HPO4 solution with a density equivalent to that of bone. The sum of all pixels in air, water and the K2HPO4 solution was measured on SPECT images. Scatter fraction (SF) and normalized mean square error (NMSE) based on counts from the air background as a reference were then calculated to assess quantitative errors due to scatter correction. The uniform cylinder phantom contained the same K2HPO4 solution and 222.0 MBq of 99mTc. The coefficient of variation (CV) was calculated from the count profile of this phantom to assess the uniformity of SPECT images across scatter correction under various conditions. Both SF and NMSE in SPECT images of phantoms containing water in the background were lower at a TEW sub-window of 3% (TEW3%), than in other scatter corrections, whereas those in K2HPO4 were lower at a DEW sub-window of 20% (DEW20%). Larger DEW and smaller TEW sub-energy windows allowed more effective correction. The CV of the uniform cylinder phantom, DEW20%, was inferior to all other tested scatter corrections. The quantitative accuracy of bone SPECT images substantially differed according to the method of scatter correction. The optimal scatter correction for quantitative bone SPECT was DEW20% (k = 1), but at the cost of slightly decreased image uniformity.

Determination of optimal regularization factor in Bayesian penalized likelihood reconstruction of brain PET images using [18 F]FDG and [11 C]PiB.

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 (ß) in BPL requires optimization according to the radiopharmaceutical tracer. The present study aimed to define the optimal ß value in BPL required to diagnose Alzheimer disease from brain positron emission tomography (PET) images acquired using 18 F-fluoro-2-deoxy-D-glucose ([18 F]FDG) and 11 C-labeled Pittsburg compound B ([11 C]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 (ß = 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 [18 F]FDG and [11 C]PiB PET to validate the findings from the phantom study. The ß 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 ß 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 ß = 20-450 and 20-600 for [18 F]FDG and [11 C]PiB, respectively. The image noise in BPL satisfied the JSNM criterion of ≤15% and was below that in OSEM when ß = 150-1000 and 400-1000 for [18 F]FDG and [11 C]PiB, respectively. The phantom study restricted the ranges of ß values to 100-300 and 300-500 for [18 F]FDG and [11 C]PiB, respectively. The BPL scores for gray-white matter contrast and image noise, exceeded those of OSEM in [18 F]FDG and [11 C]PiB images regardless of ß values. Visual evaluation confirmed that the optimal ß values were 200 and 450 for [18 F]FDG and [11 C]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 ß values for [18 F]FDG and [11 C]PiB brain PET were apparently 200 and 450, respectively. The present study provides useful information about how to determine optimal ß values in BPL for brain PET imaging.

Optimization of a Bayesian penalized likelihood algorithm (Q.Clear) for 18F-NaF bone PET/CT images acquired over shorter durations using a custom-designed phantom.

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 (ß = 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 (ß = 400) images. RESULTS: The optimal reconstruction parameter of the BPL was ß = 400 when images were acquired at 120 s/bed. At 90 s/bed, the BPL with a ß 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 (ß = 400) on SiPM-based TOF PET/CT scanner maintained high image quality and quantitative accuracy even for shorter acquisition durations.

Detection of sub-centimeter lesions using digital TOF-PET/CT system combined with Bayesian penalized likelihood reconstruction algorithm.

OBJECTIVE: Many advances in PET/CT technology can potentially improve image quality and the ability to detect small lesions. A new digital TOF-PET/CT scanner based on silicon photomultipliers (SiPM) integrated with a Bayesian penalized likelihood (BPL) PET reconstruction algorithm (Q.Clear; GE Healthcare) has been introduced into clinical practice. The present study aimed to quantify the ability of a digital TOF-PET/CT scanner combined with BPL reconstruction to detect small lesions, and to determine the optimal penalization factor (ß) in BPL to accurately detect such lesions. METHODS: All PET data were acquired from a NEMA body phantom using a Discovery MI (DMI) PET/CT system (GE Healthcare). The phantom included six spheres with diameters of 4, 5, 6, 8, 10, and 13 mm, and contained a background activity level of 5.3 kBq/mL, with target-to-background ratios (TBR) of 4:1 and 8:1. Images were reconstructed using a baseline OSEM algorithm, with OSEM + PSF, OSEM + TOF, OSEM + PSF + TOF, and BPL + PSF + TOF (ß: 50-400). The matrix size was 192 × 192 and 384 × 384. Data acquired in 100-min list mode were re-binned into acquisition times ranging from 2 to 100 min. The quantitative accuracy and detectability of small hot spheres were evaluated by physical assessment of a recovery coefficient (RC) and a detectability index (DI), as well as visual assessment of PET images at each acquisition time. RESULTS: The RC and DI of sub-centimeter spheres were improved, because the digital TOF-PET/CT scanner has a larger TOF performance gain due to better timing resolution. The RC and DI were higher with BPL in sub-centimeter spheres, than with other OSEM-based types of reconstruction. The BPL for an 8-mm sphere overestimated uptake due to edge artifact overshoot induced by PSF modeling. The variability of RC and DI for acquisition times and TBR differed considerably according to ß values. The RC for ~ 8-mm spheres were > 1 at ß values between 50 and 100, but were close to 1 at ß value of 200. The visual scores for ß = 200 in BPL were maximal, whereas those for spheres that were ≥ 6 mm exceeded the criterion of 3. CONCLUSION: The BPL in the digital TOF-PET/CT scanner improved the quantitation and detectability of sub-centimeter spheres compared with OSEM-based reconstruction. Optimization of the ß value in BPL might allow the detection of lesions ≤ 6 mm, although detectability depended on the TBR of lesions. A ß value of 200 seemed optimal for detecting sub-centimeter lesions.

Differences in the binding modes of phytochelatin to cadmium(II) and zinc(II) ions.

An 1H NMR (nuclear magnetic resonance) spectroscopic structural analysis of Cd2+ complexes formed with the pentapeptide phytochelatin, (NH3)+-(gamma-Glu-Cys)2-Gly-COO- (PC2), at a pH of 7.5 showed that the two thiol groups of the Cys residues and either the carbonyl or amide group of the peptide bond between Glu1 and Cys1 act as possible donor groups in the complexes at Cd2+/PC2 ratios up to 0.4. As the ratio increases, the carboxylate group of Glu2 and either the carbonyl or amide group of the peptide bond between Cys1 and Glu2 comes to serve as a donor group. The manner in which Cd2+ forms complexes with PC2 is distinctly different from Zn2+ and might account for the role of phytochelatin in Cd2+ detoxification. Electron absorption spectrometry demonstrated that the Cd2+ complexes are coordinated in a tetrahedral fashion by four thiol groups and that several sulfur atoms might bridge Cd2+ ions, resulting in the formation of polynuclear complexes. This contrasts with Zn2+ complex formation, which consists exclusively of a 1:1 complex.