Evaluation of Penalized-Likelihood Estimation Reconstruction on a Digital Time-of-Flight PET/CT Scanner for 18F-FDG Whole-Body Examinations

Time-synchronized 2-deoxy-2-[18F]fluoro-D-glucose PET/MRI with MR-active trigger and Bayesian penalized likelihood reconstruction: Diagnostic utility for locoregional extension of endometrial cancer

PURPOSE

Minimal misregistration of fused PET and MRI images can be achieved with simultaneous positron emission tomography/magnetic resonance imaging (PET/MRI). However, the acquisition of multiple MRI sequences during a single PET emission scan may impair fusion precision of each sequence. This study evaluated the diagnostic utility of time-synchronized PET/MRI using an MR active trigger and a Bayesian penalized likelihood reconstruction algorithm (BPL) to assess the locoregional extension of endometrial cancer.

METHODS

Fifty-five patients with endometrial cancer who underwent pelvic 2-deoxy-2-[18F]fluoro-D-glucose PET/MRI were retrospectively evaluated. The PET emission time for the BPL reconstruction was determined by the MR active trigger of each MR sequence. The concordance rates of image interpretation with pathological T-staging, diagnostic performance for deep myometrial invasion (MI), and diagnostic confidence levels were evaluated by two readers and compared between time-synchronized, overlapping (conventional and simultaneous, but not time-synchronized), and sequential (not simultaneous) PET/MRI and MRI with diffusion-weighted imaging. Misregistration of the PET/MRI-fused images was determined by evaluating the differences in bladder dimensions.

RESULTS

The T classification by time-synchronized PET/MRI was the most concordant with the pathological T classification for the two readers. Time-synchronized PET/MRI had a significantly higher diagnostic performance for deep MI and higher confidence level scores than overlapping PET/MRI for the novice reader (p = 0.033 and p = 0.038, respectively). The differences in bladder dimension on sequential PET/MRI were significantly larger than those on overlapping and time-synchronized PET/MRI (p <0.001).

CONCLUSION

Time-synchronized PET/MRI is superior to conventional PET/MRI for assessing the locoregional extension of endometrial cancer.

The value of PET/CT in the diagnosis and differential diagnosis of Parkinson's disease: a dual-tracer study

Positron emission tomography/computed tomography (PET/CT) is a molecular imaging method commonly used to diagnose and differentiate Parkinson's disease (PD). This study aimed to evaluate the performance of PET/CT with 11C-2β-Carbomethoxy-3β-(4-fluorophenyl) tropane (11C-CFT) and 18F-fluorodeoxyglucose (18F-FDG) tracers in the differential diagnosis between PD, multiple system atrophy parkinsonian type (MSA-P), progressive supranuclear palsy (PSP) and vascular parkinsonism (VP) using the data of 220 patients with clinical PD-like symptoms. Of the 220 enrolled patients, 166 (PD, n = 80; MSA-P, n = 54; PSP, n = 15; VP, n = 17) completed the motor, cognitive and PET/CT assessment and were included in this study. 11C-CFT and 18F-FDG PET/CT images were analyzed using the SNBPI toolbox and CortexID Suite software. The uptake values of 11C-CFT and 18F-FDG PET/CT were compared among the groups after controlling for covariates using generalized linear models. Receiver operating characteristic (ROC) curves were generated to estimate the diagnostic values. Patients with PSP showed the most significant reduction on 11C-CFT PET/CT, while patients with PD and MSA-P showed similar reductions, and patients with VP did not show any significant reduction in 11C-CFT uptake. The areas under the curve (AUCs) for 11C-CFT PET/CT for distinguishing PD from VP, PSP, and MSA-P were 0.902, 0.830, and 0.580, respectively, and 0.728 for distinguishing advanced-stage PD from PSP. On 18F-FDG PET/CT, the AUCs for distinguishing PD from PSP and MSA-P were 0.968 and 0.963, respectively. These results suggest that 11C-CFT and 18F-FDG PET/CT complement each other in improving the accuracy in differential diagnosis of PD.

Y-90 PET/MR imaging optimization with a Bayesian penalized likelihood reconstruction algorithm

Positron Emission Tomography (PET) imaging after90 Y liver radioembolization is used for both lesion identification and dosimetry. Bayesian penalized likelihood (BPL) reconstruction algorithms are an alternative to ordered subset expectation maximization (OSEM) with improved image quality and lesion detectability. The investigation of optimal parameters for90 Y image reconstruction of Q.Clear, a commercial BPL algorithm developed by General Electric (GE), in PET/MR is a field of interest and the subject of this study. The NEMA phantom was filled at an 8:1 sphere-to-background ratio. Acquisitions were performed on a PET/MR scanner for clinically relevant activities between 0.7 and 3.3 MBq/ml. Reconstructions with Q.Clear were performed varying the β penalty parameter between 20 and 6000, the acquisition time between 5 and 20 min and pixel size between 1.56 and 4.69 mm. OSEM reconstructions of 28 subsets with 2 and 4 iterations with and without Time-of-Flight (TOF) were compared to Q.Clear with β = 4000. Recovery coefficients (RC), their coefficient of variation (COV), background variability (BV), contrast-to-noise ratio (CNR) and residual activity in the cold insert were evaluated. Increasing β parameter lowered RC, COV and BV, while CNR was maximized at β = 4000; further increase resulted in oversmoothing. For quantification purposes, β = 1000-2000 could be more appropriate. Longer acquisition times resulted in larger CNR due to reduced image noise. Q.Clear reconstructions led to higher CNR than OSEM. A β of 4000 was obtained for optimal image quality, although lower values could be considered for quantification purposes. An optimal acquisition time of 15 min was proposed considering its clinical use.

Phantom and clinical evaluation of the Bayesian penalised likelihood reconstruction algorithm Q.Clear without PSF correction in amyloid PET images

PURPOSE

Bayesian penalised likelihood (BPL) reconstruction, which incorporates point-spread-function (PSF) correction, provides higher signal-to-noise ratios and more accurate quantitation than conventional ordered subset expectation maximization (OSEM) reconstruction. However, applying PSF correction to brain PET imaging is controversial due to Gibbs artefacts that manifest as unpredicted cortical uptake enhancement. The present study aimed to validate whether BPL without PSF would be useful for amyloid PET imaging.

METHODS

Images were acquired from Hoffman 3D brain and cylindrical phantoms for phantom study and 71 patients administered with [18F]flutemetamol in clinical study using a Discovery MI. All images were reconstructed using OSEM, BPL with PSF correction, and BPL without PSF correction. Count profile, %contrast, recovery coefficients (RCs), and image noise were calculated from the images acquired from the phantoms. Amyloid β deposition in patients was visually assessed by two physicians and quantified based on the standardised uptake value ratio (SUVR).

RESULTS

The overestimated radioactivity in profile curves was eliminated using BPL without PSF correction. The %contrast and image noise decreased with increasing β values in phantom images. Image quality and RCs were better using BPL with, than without PSF correction or OSEM. An optimal β value of 600 was determined for BPL without PSF correction. Visual evaluation almost agreed perfectly (κ = 0.91-0.97), without depending on reconstruction methods. Composite SUVRs did not significantly differ between reconstruction methods.

CONCLUSION

Gibbs artefacts disappeared from phantom images using the BPL without PSF correction. Visual and quantitative evaluation of [18F]flutemetamol imaging was independent of the reconstruction method. The BPL without PSF correction could be the standard reconstruction method for amyloid PET imaging, despite being qualitatively inferior to BPL with PSF correction for [18F]flutemetamol amyloid PET imaging.

Reduction of [68Ga]Ga-DOTA-TATE injected activity for digital PET/MR in comparison with analogue PET/CT

BACKGROUND

New digital detectors and block-sequential regularized expectation maximization (BSREM) reconstruction algorithm improve positron emission tomography (PET)/magnetic resonance (MR) image quality. The impact on image quality may differ from analogue PET/computed tomography (CT) protocol. The aim of this study is to determine the potential reduction of injected [68Ga]Ga-DOTA-TATE activity for digital PET/MR with BSREM reconstruction while maintaining at least equal image quality compared to the current analogue PET/CT protocol.

METHODS

NEMA IQ phantom data and 25 patients scheduled for a diagnostic PET/MR were included. According to our current protocol, 1.5 MBq [68Ga]Ga-DOTA-TATE per kilogram (kg) was injected. After 60 min, scans were acquired with 3 (≤ 70 kg) or 4 (> 70 kg) minutes per bedposition. PET/MR scans were reconstructed using BSREM and factors β 150, 300, 450 and 600. List mode data with reduced counts were reconstructed to simulate scans with 17%, 33%, 50% and 67% activity reduction. Image quality was measured quantitatively for PET/CT and PET/MR phantom and patient data. Experienced nuclear medicine physicians performed visual image quality scoring and lesion counting in the PET/MR patient data.

RESULTS

Phantom analysis resulted in a possible injected activity reduction of 50% with factor β = 600. Quantitative analysis of patient images revealed a possible injected activity reduction of 67% with factor β = 600. Both with equal or improved image quality as compared to PET/CT. However, based on visual scoring a maximum activity reduction of 33% with factor β = 450 was acceptable, which was further limited by lesion detectability analysis to an injected activity reduction of 17% with factor β = 450.

CONCLUSION

A digital [68Ga]Ga-DOTA-TATE PET/MR together with BSREM using factor β = 450 result in 17% injected activity reduction with quantitative values at least similar to analogue PET/CT, without compromising on PET/MR visual image quality and lesion detectability.

Kinetic Modeling of Brain [18-F]FDG Positron Emission Tomography Time Activity Curves with Input Function Recovery (IR) Method

Accurate positron emission tomography (PET) data quantification relies on high-quality input plasma curves, but venous blood sampling may yield poor-quality data, jeopardizing modeling outcomes. In this study, we aimed to recover sub-optimal input functions by using information from the tail (5th-100th min) of curves obtained through the frequent sampling protocol and an input recovery (IR) model trained with reference curves of optimal shape. Initially, we included 170 plasma input curves from eight published studies with clamp [18F]-fluorodeoxyglucose PET exams. Model validation involved 78 brain PET studies for which compartmental model (CM) analysis was feasible (reference (ref) + training sets). Recovered curves were compared with original curves using area under curve (AUC), max peak standardized uptake value (maxSUV). CM parameters (ref + training sets) and fractional uptake rate (FUR) (all sets) were computed. Original and recovered curves from the ref set had comparable AUC (d = 0.02, not significant (NS)), maxSUV (d = 0.05, NS) and comparable brain CM results (NS). Recovered curves from the training set were different from the original according to maxSUV (d = 3) and biologically plausible according to the max theoretical K1 (53//56). Brain CM results were different in the training set (p < 0.05 for all CM parameters and brain regions) but not in the ref set. FUR showed reductions similarly in the recovered curves of the training and test sets compared to the original curves (p < 0.05 for all regions for both sets). The IR method successfully recovered the plasma inputs of poor quality, rescuing cases otherwise excluded from the kinetic modeling results. The validation approach proved useful and can be applied to different tracers and metabolic conditions.

Reduced count pediatric whole-body 18F-FDG PET imaging reconstruction with a Bayesian penalized likelihood algorithm

BACKGROUND

Advanced positron emission tomography (PET) image reconstruction methods promise to allow optimized PET/CT protocols with improved image quality, decreased administered activity and/or acquisition times.

OBJECTIVE

To evaluate the impact of reducing counts (simulating reduced acquisition time) in block sequential regularized expectation maximization (BSREM) reconstructed pediatric whole-body 18F-fluorodeoxyglucose (FDG) PET images, and to compare BSERM with ordered-subset expectation maximization (OSEM) reconstructed reduced-count images.

MATERIALS AND METHODS

Twenty children (16 male) underwent clinical whole-body 18F-FDG PET/CT examinations using a 25-cm axial field-of-view (FOV) digital PET/CT system at 90 s per bed (s/bed) with BSREM reconstruction (β=700). Reduced count simulations with varied BSREM β levels were generated from list-mode data: 60 s/bed, β=800; 50 s/bed, β=900; 40 s/bed, β=1000; and 30 s/bed, β=1300. In addition, a single OSEM reconstruction was created at 60 s/bed based on prior literature. Qualitative (Likert scores) and quantitative (standardized uptake value [SUV]) analyses were performed to evaluate image quality and quantitation across simulated reconstructions.

RESULTS

The mean patient age was 9.0 ± 5.5 (SD) years, mean weight was 38.5 ± 24.5 kg, and mean administered 18F-FDG activity was 4.5 ± 0.7 (SD) MBq/kg. Between BSREM reconstructions, no qualitative measure showed a significant difference versus the 90 s/bed β=700 standard (all P>0.05). SUVmax values for lesions were significantly lower from 90 s/bed, β=700 only at a simulated acquisition time of 30 s/bed, β=1300 (P=0.001). In a side-by-side comparison of BSREM versus OSEM reconstructions, 40 s/bed, β=1000 images were generally preferred over 60 s/bed TOF OSEM images.

CONCLUSION

In children who undergo whole-body 18F-FDG PET/CT on a 25-cm FOV digital PET/CT scanner, reductions in acquisition time or, by corollary, administered radiopharmaceutical activity of >50% from a clinical standard of 90 s/bed may be possible while maintaining diagnostic quality when a BSREM reconstruction algorithm is used.

First clinical experience of a ring-configured cadmium zinc telluride camera: A comparative study versus conventional gamma camera systems

BACKGROUND

A novel semiconductor cadmium zinc telluride (CZT) gamma camera system using a block sequential regularized expectation maximization (BSREM) reconstruction algorithm is now clinically available. Here we investigate how a multi-purpose ring-configurated CZT system can be safely applied in clinics and describe the initial optimization process.

METHOD

Seventy-six patients (bone-, cardiac- and lung scan) were scanned on a conventional gamma camera (planar and/or single-photon emission computed tomography [SPECT]/SPECT-CT) used in clinical routine and on the ring-configurated CZT camera Starguide (GE Healthcare). These data were used to validate and optimize the Starguide system for routine clinical use.

RESULTS

Comparable image quality for the Starguide system, to that of the conventional gamma camera, was achieved for bone scan (4 min/bed position [BP] using a relative difference prior [RDP] with gamma 2 and beta 0.4, along with 10 iterations and 10 subsets), cardiac scan (8 min [stress] and 3 min 20 s [rest] using median root prior [MRP] with beta 0.07 non attenuation corrected and 0.008 attenuation corrected and 50 interations and 10 subsets for both stress and rest) and lung scan (10 min [vent] and 5 min [perf] using RDP with gamma 0.5 and beta 0.03 [vent] and 0.02 [perf] and 20 interations and 10 subsets for both vent and perf).

CONCLUSIONS

It was possible to transition from a conventional gamma camera to the Starguide system as part of the clinical routine, with acceptable image quality. Images from the Starguide system were deemed to be at least as good as those from a conventional gamma camera.

A review of digital PET-CT technology: Comparing performance parameters in SiPM integrated digital PET-CT systems

OBJECTIVE

The objective of this study was to perform a narrative review of digital Positron emission tomography-computed tomography (PET-CT) scanners, focussing on the current development in the technology of optimized crystal size and design, the time of flight (ToF) resolution, sensitivity, and axial field of view (AFOV).

KEY FINDINGS

It was observed that significant developments were carried out on the optimization of scintillation crystal size which results in the improvement of spatial resolution. such developments include the upgrade in the AFOV after the integration of SiPM technology, which results in dynamic parametric imaging acquisition in PET and sensitivity boost. The improvement in ToF resolution and the better ToF resolution values, which result in a boost in adequate sensitivity and signal-to-noise ratio (SNR). Other upgrades include the use of the smallest crystal size of 2.76 × 2.76 mm, and the use of the lowest ToF resolution of 214 ps. The use of the largest AFOV of 194 cm with the highest observed NEMA sensitivity of 225 cps/kBq for the total body PET-CT system.

CONCLUSION

Digital PET-CT systems offer various advantages such as a reduction in radiation dose from injected radiopharmaceuticals doses and the overall PET acquisition time with an improved diagnostic certainty. This is because of the better performance of the SiPM detector. Digital PET-CT also has added benefits of the dynamic acquisition and Patlak modeling capabilities into routine clinical practice with the advancement in higher AFOV PET systems.

IMPLICATION

This will help the users choose the best system during the evaluation of the PET-CT for purchase in clinical and research applications. This review will further help in teaching the latest technology and developments in PET-CT systems.

Total variation regularized expectation maximization reconstruction improves 68Ga-FAPI-04 PET/CT image quality as compared to ordered subset expectation maximization reconstruction

BACKGROUND

This study aimed to investigate improvements in 68Ga-FAPI PET/CT image quality due to using total variation regularized expectation maximization (TVR-EM) and ordered subset expectation maximization (OS-EM) reconstruction.

METHODS

Data from a total of 24 patients were retrospectively analyzed in this study. Positron emission tomography (PET) images were reconstructed using OS-EM and TVR-EM for 2 and 3 minutes-per-bed (min/bed) acquisition. The SUVmean of a region-of-interest on the liver, image noise, signal-to-noise ratios (SNR), the SUVmax of the lesions and the tumour-to-background ratios (TBR) were measured and compared between the 2 methods. Subjective image qualities were evaluated by two experienced radiologists using a 5-point score scale (5-excellent, 1-poor).

RESULTS

In total, 132 lesions were analyzed. The image noise in TVR-EM reconstruction groups was lower than in the OS-EM groups (all P<0.05). The SNR, SUVmax of lesions and the TBR were higher for the TVR-EM reconstruction groups compared to OS-EM groups (all P<0.05). Also, the SUVmax of the lesions in the TVR-EM groups increased by at least 12% compared to OS-EM 3 min/bed group. The SUVmax for small (<10 mm) and large lesions (>10 mm) in the TVR-EM 2 min/bed group were significantly larger compared to the OS-EM 3 min/bed groups (all P<0.05). The highest image quality score resulted from the TVR-EM 3 min/bed group with a penalization factor of 0.25 (3.92±0.19).

CONCLUSIONS

TVR-EM reduces image noise and improved the SNR, SUVmax and TBR of the lesions. It also enables fast acquisition without compromising image quality compared to standard OS-EM.

Performance Characteristics of a New-Generation Digital Bismuth Germanium Oxide PET/CT System, Omni Legend 32, According to NEMA NU 2-2018 Standards

The Omni Legend 32 PET/CT system features silicon photomultiplier (SiPM)-based detectors with bismuth germanium oxide crystals and a 32-cm axial field of view (FOV). The present study aimed to determine the performance characteristics of the Omni Legend 32 PET/CT system according to National Electrical Manufacturers Association (NEMA) NU 2-2018 standards. Methods: The PET component of this system comprises 22 detector modules; each module contains 24 detector blocks with 72 bismuth germanium oxide crystals with a volume of 4.1 × 4.1 × 30 mm coupled to 18 SiPM devices with a 6 × 6 mm area, resulting in an axial FOV of 32 cm. The spatial resolution, sensitivity, count rate performance, and image quality delivered by PET were evaluated using the NEMA NU 2-2018 standard. PET images of 2 patients were evaluated to get a visual first impression of the Omni Legend 32 PET/CT system together with Precision DL. Results: The average spatial resolution at 1, 10, and 20 cm from the central axis was 4.3, 5.3, and 6.2 mm, respectively, for filtered backprojection and 3.7, 4.3, and 5.1 mm, respectively, for ordered-subset expectation maximization. The NEMA sensitivity was 47.30 and 47.05 cps/kBq at the axial center of the FOV and at a 10-cm radial offset, respectively. The scatter fraction, count rate accuracy, and peak noise-equivalent count rates were 35.4%, 1.7%, and 501.7 kcps, respectively, at 15.7 kBq/mL. Contrast recovery for the NEMA body phantom from the smallest to the largest sphere ranged from 61.3% to 93.0%, with a background variability of 5.4%-11.7% and a lung error of 5.1% for Q.Clear (β-value, 50). Good patient image quality was obtained with the Omni Legend 32. Conclusion: The Omni Legend 32 has class-leading sensitivity and count rates within the category of whole-body PET systems while maintaining spatial resolution broadly comparable to that of other current SiPM-based PET/CT systems. This combination of properties results in a very good image quality.

The effects of various penalty parameter values in Q.Clear algorithm for rectal cancer detection on 18F-FDG images using a BGO-based PET/CT scanner: a phantom and clinical study

BACKGROUND

The Q.Clear algorithm is a fully convergent iterative image reconstruction technique. We hypothesize that different PET/CT scanners with distinct crystal properties will require different optimal settings for the Q.Clear algorithm. Many studies have investigated the improvement of the Q.Clear reconstruction algorithm on PET/CT scanner with LYSO crystals and SiPM detectors. We propose an optimum penalization factor (β) for the detection of rectal cancer and its metastases using a BGO-based detector PET/CT system which obtained via accurate and comprehensive phantom and clinical studies.

METHODS

18F-FDG PET-CT scans were acquired from NEMA phantom with lesion-to-background ratio (LBR) of 2:1, 4:1, 8:1, and 15 patients with rectal cancer. Clinical lesions were classified into two size groups. OSEM and Q.Clear (β value of 100-500) reconstruction was applied. In Q.Clear, background variability (BV), contrast recovery (CR), signal-to-noise ratio (SNR), SUVmax, and signal-to-background ratio (SBR) were evaluated and compared to OSEM.

RESULTS

OSEM had 11.5-18.6% higher BV than Q.Clear using β value of 500. Conversely, RC from OSEM to Q.Clear using β value of 500 decreased by 3.3-7.7% for a sphere with a diameter of 10 mm and 2.5-5.1% for a sphere with a diameter of 37 mm. Furthermore, the increment of contrast using a β value of 500 was 5.2-8.1% in the smallest spheres compared to OSEM. When the β value was increased from 100 to 500, the SNR increased by 49.1% and 30.8% in the smallest and largest spheres at LBR 2:1, respectively. At LBR of 8:1, the relative difference of SNR between β value of 100 and 500 was 43.7% and 44.0% in the smallest and largest spheres, respectively. In the clinical study, as β increased from 100 to 500, the SUVmax decreased by 47.7% in small and 31.1% in large lesions. OSEM demonstrated the least SUVmax, SBR, and contrast. The decrement of SBR and contrast using OSEM were 13.6% and 12.9% in small and 4.2% and 3.4%, respectively, in large lesions.

CONCLUSIONS

Implementing Q.Clear enhances quantitative accuracies through a fully convergent voxel-based image approach, employing a penalization factor. In the BGO-based scanner, the optimal β value for small lesions ranges from 200 for LBR 2:1 to 300 for LBR 8:1. For large lesions, the optimal β value is between 400 for LBR 2:1 and 500 for LBR 8:1. We recommended β value of 300 for small lesions and β value of 500 for large lesions in clinical study.

Phantom and clinical evaluation of Block Sequential Regularized Expectation Maximization (BSREM) reconstruction algorithm in 68Ga-PSMA PET-CT studies

In this study, we aimed to examine the effect of varying β-values in the block sequential regularized expectation maximization (BSREM) algorithm under differing lesion sizes to determine an optimal penalty factor for clinical application. The National Electrical Manufacturers Association phantom and 15 prostate cancer patients were injected with 68Ga-PSMA and scanned using a GE Discovery IQ PET/CT scanner. Images were reconstructed using ordered subset expectation maximization (OSEM) and BSREM with different β-values. Then, the background variability (BV), contrast recovery, signal-to-noise ratio, and lung residual error were measured from the phantom data, and the signal-to-background ratio (SBR) and contrast from the clinical data. The increment of BV using a β-value of 100 was 120.0%, and the decrement of BV using a β-value of 1000 was 40.5% compared to OSEM. As β decreased from 1000 to 100, the [Formula: see text] increased by 59.0% for a sphere with a diameter of 10 mm and 26.4% for a sphere with a diameter of 37 mm. Conversely, [Formula: see text] increased by 140.5% and 29.0% in the smallest and largest spheres, respectively. Furthermore, the Δ[Formula: see text] and Δ[Formula: see text] were - 41.1% and - 36.7%, respectively. In the clinical study, OSEM exhibited the lowest SBR and contrast. When the β-value was reduced from 500 to 100, the SBR and contrast increased by 69.7% and 71.8% in small and 35.6% and 33.0%, respectively, in large lesions. Moreover, the optimal β-value decreased as lesion size decreased. In conclusion, a β-value of 400 is optimal for small lesion reconstruction, while β-values of 600 and 500 are optimal for large lesions in phantom and clinical studies, respectively.

Rapid Whole-Body FDG PET/MRI in Oncology Patients: Utility of Combining Bayesian Penalised Likelihood PET Reconstruction and Abbreviated MRI

This study evaluated the diagnostic value of a rapid whole-body fluorodeoxyglucose (FDG) positron emission tomography (PET)/magnetic resonance imaging (MRI) approach, combining Bayesian penalised likelihood (BPL) PET with an optimised β value and abbreviated MRI (abb-MRI). The study compares the diagnostic performance of this approach with the standard PET/MRI that utilises ordered subsets expectation maximisation (OSEM) PET and standard MRI (std-MRI). The optimal β value was determined by evaluating the noise-equivalent count (NEC) phantom, background variability, contrast recovery, recovery coefficient, and visual scores (VS) for OSEM and BPL with β100-1000 at 2.5-, 1.5-, and 1.0-min scans, respectively. Clinical evaluations were conducted for NEC_patient, NEC_density, liver signal-to-noise ratio (SNR), lesion maximum standardised uptake value, lesion signal-to-background ratio, lesion SNR, and VS in 49 patients. The diagnostic performance of BPL/abb-MRI was retrospectively assessed for lesion detection and differentiation in 156 patients using VS. The optimal β values were β600 for a 1.5-min scan and β700 for a 1.0-min scan. BPL/abb-MRI at these β values was equivalent to OSEM/std-MRI for a 2.5-min scan. By combining BPL with optimal β and abb-MRI, rapid whole-body PET/MRI could be achieved in ≤1.5 min per bed position, while maintaining comparable diagnostic performance to standard PET/MRI.

Bayesian penalized likelihood PET reconstruction impact on quantitative metrics in diffuse large B-cell lymphoma

Evaluate the quantitative, subjective (Deauville score [DS]) and reader agreement differences between standard ordered subset expectation maximization (OSEM) and Bayesian penalized likelihood (BPL) positron emission tomography (PET) reconstruction methods. A retrospective review of 104 F-18 fluorodeoxyglucose PET/computed tomography (CT) exams among 52 patients with diffuse large B-cell lymphoma. An unblinded radiologist moderator reviewed both BPL and OSEM PET/CT exams. Four blinded radiologists then reviewed the annotated cases to provide a visual DS for each annotated lesion. Significant (P < .001) differences in BPL and OSEM PET methods were identified with greater standard uptake value (SUV) maximum and SUV mean for BPL. The DS was altered in 25% of cases when BPL and OSEM were reviewed by the same radiologist. Interobserver DS agreement was higher for OSEM (>1 cm lesion = 0.89 and ≤1 cm lesion = 0.84) compared to BPL (>1 cm lesion = 0.85 and ≤1 cm lesion = 0.81). Among the 4 readers, average intraobserver visual DS agreement between OSEM and BPL was 0.67 for lesions >1cm and 0.4 for lesions ≤1 cm. F-18 Fluorodeoxyglucose PET/CT of diffuse large B-cell lymphoma reconstructed with BPL has higher SUV values, altered DSs and reader agreement when compared to OSEM. This report finds volumetric PET measurements such as metabolic tumor volume to be similar between BPL and OSEM PET reconstructions. Efforts such as adoption of European Association Research Ltd accreditation should be made to harmonize PET data with an aim at balancing the need for harmonization and sensitivity for lesion detection.

Phantom and clinical evaluation of the effect of a new Bayesian penalized likelihood reconstruction algorithm (HYPER Iterative) on 68Ga-DOTA-NOC PET/CT image quality

BACKGROUND

Bayesian penalized likelihood (BPL) algorithm is an effective way to suppress noise in the process of positron emission tomography (PET) image reconstruction by incorporating a smooth penalty. The strength of the smooth penalty is controlled by the penalization factor. The aim was to investigate the impact of different penalization factors and acquisition times in a new BPL algorithm, HYPER Iterative, on the quality of ⁶⁸Ga-DOTA-NOC PET/CT images. A phantom and 25 patients with neuroendocrine neoplasms who underwent ⁶⁸Ga-DOTA-NOC PET/CT were included. The PET data were acquired in a list-mode with a digital PET/CT scanner and reconstructed by ordered subset expectation maximization (OSEM) and the HYPER Iterative algorithm with seven penalization factors between 0.03 and 0.5 for acquisitions of 2 and 3 min per bed position (m/b), both including time-of-flight and point of spread function recovery. The contrast recovery (CR), background variability (BV) and radioactivity concentration ratio (RCR) of the phantom; The SUV_mean and coefficient of variation (CV) of the liver; and the SUV_max of the lesions were measured. Image quality was rated by two radiologists using a five-point Likert scale.

RESULTS

The CR, BV, and RCR decreased with increasing penalization factors for four "hot" spheres, and the HYPER Iterative 2 m/b groups with penalization factors of 0.07 to 0.2 had equivalent CR and superior BV performance compared to the OSEM 3 m/b group. The liver SUV_mean values were approximately equal in all reconstruction groups (range 5.95-5.97), and the liver CVs of the HYPER Iterative 2 m/b and 3 m/b groups with the penalization factors of 0.1 to 0.2 were equivalent to those of the OSEM 3 m/b group (p = 0.113-0.711 and p = 0.079-0.287, respectively), while the lesion SUV_max significantly increased by 19-22% and 25%, respectively (all p < 0.001). The highest qualitative score was attained at a penalization factor of 0.2 for the HYPER Iterative 2 m/b group (3.20 ± 0.52) and 3 m/b group (3.70 ± 0.36); those scores were comparable to or greater than that of the OSEM 3 m/b group (3.09 ± 0.36, p = 0.388 and p < 0.001, respectively).

CONCLUSIONS

The HYPER Iterative algorithm with a penalization factor of 0.2 resulted in higher lesion contrast and lower image noise than OSEM for ⁶⁸Ga-DOTA-NOC PET/CT, allowing the same image quality to be achieved with less injected radioactivity and a shorter acquisition time.

Deep progressive learning achieves whole-body low-dose 18F-FDG PET imaging

Objectives

To validate a total-body PET-guided deep progressive learning reconstruction method (DPR) for low-dose 18F-FDG PET imaging.

Methods

List-mode data from the retrospective study (n = 26) were rebinned into short-duration scans and reconstructed with DPR. The standard uptake value (SUV) and tumor-to-liver ratio (TLR) in lesions and coefficient of variation (COV) in the liver in the DPR images were compared to the reference (OSEM images with full-duration data). In the prospective study, another 41 patients were injected with 1/3 of the activity based on the retrospective results. The DPR images (DPR_1/3(p)) were generated and compared with the reference (OSEM images with extended acquisition time). The SUV and COV were evaluated in three selected organs: liver, blood pool and muscle. Quantitative analyses were performed with lesion SUV and TLR, furthermore on small lesions (≤ 10 mm in diameter). Additionally, a 5-point Likert scale visual analysis was performed on the following perspectives: contrast, noise and diagnostic confidence.

Results

In the retrospective study, the DPR with one-third duration can maintain the image quality as the reference. In the prospective study, good agreement among the SUVs was observed in all selected organs. The quantitative results showed that there was no significant difference in COV between the DPR_1/3(p) group and the reference, while the visual analysis showed no significant differences in image contrast, noise and diagnostic confidence. The lesion SUVs and TLRs in the DPR_1/3(p) group were significantly enhanced compared with the reference, even for small lesions.

Conclusions

The proposed DPR method can reduce the administered activity of 18F-FDG by up to 2/3 in a real-world deployment while maintaining image quality.

Detection of lymph node metastases in patients with prostate cancer: Comparing conventional and digital [18 F]-fluorocholine PET-CT using histopathology as a reference

BACKGROUND

Positron emission tomography-computed tomography (PET-CT) with [¹⁸ F]-fluorocholine (FCH) is used to detect and stage metastatic lymph nodes in patients with prostate cancer. Improvements to hardware and software have recently been made. We compared the capability of detecting regional lymph node metastases using conventional and digital silicon photomultiplier (SiPM)-based PET-CT technology for FCH. Extended pelvic lymph node dissection (ePLND) histopathology was used as a reference method.

METHODS

The study retrospectively examined 177 patients with intermediate or high-risk prostate cancer who had undergone staging with FCH PET-CT before ePLND. Images were obtained with either the conventional Philips Gemini PET-CT (n = 93) or the digital SiPM-based GE Discovery MI PET-CT (n = 84) and compared.

RESULTS

Images that were obtained using the Philips Gemini PET-CT system showed 19 patients (20%) with suspected lymph node metastases, whereas the GE Discovery MI PET-CT revealed 36 such patients (43%). The sensitivity, specificity, and positive and negative predictive values were 0.3, 0.84, 0.47, and 0.72 for the Philips Gemini, while they were 0.58, 0.62, 0.31, and 0.83 for the GE Discovery MI, respectively. The areas under the curves in a receiver operating characteristic curve analysis were similar between the two PET-CT systems (0.57 for Philips Gemini and 0.58 for GE Discovery MI, p = 0.89).

CONCLUSIONS

Marked differences in sensitivity and specificity were found for the different PET-CT systems, although the overall diagnostic performance was similar. These differences are probably due to differences in both hardware and software, including reconstruction algorithms, and should be considered when new technology is introduced.

BSREM for Brain Metastasis Detection with 18F-FDG-PET/CT in Lung Cancer Patients

The aim of the study was to analyze the use of block sequential regularized expectation maximization (BSREM) with different β-values for the detection of brain metastases in digital fluorine-18 labeled 2-deoxy-2-fluoro-D-glucose (18F-FDG) PET/CT in lung cancer patients. We retrospectively analyzed staging/restaging 18F-FDG PET/CT scans of 40 consecutive lung cancer patients with new brain metastases, confirmed by MRI. PET images were reconstructed using BSREM (β-values of 100, 200, 300, 400, 500, 600, 700) and OSEM. Two independent blinded readers (R1 and R2) evaluated each reconstruction using a 4-point scale for general image quality, noise, and lesion detectability. SUVmax of metastases, brain background, target-to-background ratio (TBR), and contrast recovery (CR) ratio were recorded for each reconstruction. Among all reconstruction techniques, differences in qualitative parameters were analyzed using non-parametric Friedman test, while differences in quantitative parameters were compared using analysis of variances for repeated measures. Cohen's kappa (k) was used to measure inter-reader agreement. The overall detectability of brain metastases was highest for BSREM200 (R1: 2.83 ± 1.17; R2: 2.68 ± 1.32) and BSREM300 (R1: 2.78 ± 1.23; R2: 2.68 ± 1.36), followed by BSREM100, which had lower accuracy owing to noise. The highest median TBR was found for BSREM100 (R1: 2.19 ± 1.05; R2: 2.42 ± 1.08), followed by BSREM200 and BSREM300. Image quality ratings were significantly different among reconstructions (p < 0.001). The median quality score was higher for BSREM100-300, and both noise and metastases' SUVmax decreased with increasing β-value. Inter-reader agreement was particularly high for the detectability of photopenic metastases and blurring (all k > 0.65). BSREM200 and BSREM300 yielded the best results for the detection of brain metastases, surpassing both BSREM400 and OSEM, typically used in clinical practice.

The Impact of Total Variation Regularized Expectation Maximization Reconstruction on 68Ga-DOTA-TATE PET/CT Images in Patients With Neuroendocrine Tumor

Objective

The aim of this study was to investigate the effects of the total variation regularized expectation maximization (TVREM) reconstruction on improving 68Ga-DOTA-TATE PET/CT images compared to the ordered subset expectation maximization (OSEM) reconstruction.

Method

A total of 17 patients with neuroendocrine tumors who underwent clinical 68Ga-DOTA-TATE PET/CT were involved in this study retrospectively. The PET images were acquired with either 3 min-per-bed (min/bed) acquisition time and reconstructed with OSEM (2 iterations, 20 subsets, and a 3.2-mm Gaussian filter) and TVREM (seven penalization factors = 0.01, 0.07, 0.14, 0.21, 0.28, 0.35, and 0.42) for 2 and 3 min-per-bed (min/bed) acquisition time using list-mode. The SUVmean of the liver, background variability (BV), signal-to-noise ratios (SNR), SUVmax of the lesions and tumor-to-background ratios (TBR) were measured. The mean percentage difference in the SNR and TBR between TVREM with difference penalization factors and OSEM was calculated. Qualitative image quality was evaluated by two experienced radiologists using a 5-point score scale (5-excellent, 1-poor).

Results

In total, 63 lesions were analyzed in this study. The SUVmean of the liver did not differ significantly between TVREM and OSEM. The BV of all TVREM groups was lower than OSEM groups (all p &lt; 0.05), and the BV of TVREM 2 min/bed group with penalization factor of 0.21 was considered comparable to OSEM 3 min/bed group (p = 0.010 and 0.006). The SNR, SUVmax and TBR were higher for all TVREM groups compared to OSEM groups (all p &lt; 0.05). The mean percentage difference in the SNR and TBR was larger for small lesions (&lt;10 mm) than that for medium (≥10 mm but &lt; 20 mm) and large lesions (≥20 mm). The highest image quality score was given to TVREM 2 min/bed group with penalization factor of 0.21 (3.77 ± 0.26) and TVREM 3 min/bed group with penalization factor of 0.35 (3.77 ± 0.26).

Conclusion

TVREM could reduce image noise, improve the SNR, SUVmax and TBR of the lesions, and has the potential to preserves the image quality with shorter acquisition time.

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 (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 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/CT 710 and reconstructed using OSEM + time-of-flight (TOF) under clinical conditions and BPL + TOF (β = 20-1,000). 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 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 [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 β = 150-1000 and 400-1,000 for [¹⁸ F]FDG and [¹¹ C]PiB, respectively. The phantom study restricted the ranges of β values to 100-300 and 300-500 for [¹⁸ F]FDG and [¹¹ C]PiB, respectively. The BPL scores for grey-white matter contrast and image noise, exceeded those of OSEM in [¹⁸ F]FDG and [¹¹ C]PiB images regardless of β values. Visual evaluation confirmed that the optimal β 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 SUVR due to full convergence, more rigorous noise control and edge preservation. The optimal β 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 β values in BPL for brain PET imaging. This article is protected by copyright. All rights reserved.

Effect of Bayesian penalty likelihood algorithm on 18F-FDG PET/CT image of lymphoma

OBJECTIVE

Recently, a new Bayesian penalty likelihood (BPL) reconstruction algorithm has been applied in PET, which is expected to provide better image resolution than the widely used ordered subset expectation maximization (OSEM). The purpose of this study is to compare the differences between these two algorithms in terms of image quality and effects on clinical diagnostics and quantification of lymphoma.

METHODS

A total of 246 FDG-positive lesions in 70 patients with lymphoma were retrospectively analyzed by using BPL and OSEM + time-of-flight + point spread function algorithms. Visual analysis was used to evaluate the effects of different reconstruction algorithms on clinical image quality and diagnostic certainty. Quantitative analysis was used to compare the differences between pathology and lesion size.

RESULTS

There were significant differences in lesion-related SUVmax, total-lesion-glycolysis (TLG), and signal-to-background ratio (SBR) (P < 0.01). The variation Δ SUVmax% and Δ SBR% caused by the two reconstruction algorithms were negatively correlated with tumor diameter, while Δ MTV% and Δ TLG% were positively correlated with tumor diameter. In the grouped analysis based on pathology, there were significant differences in lesion SUVmax, lesion SUVmean, and SBR. In non-Hodgkin's lymphoma (diffuse large B cells and follicular lymphoma), diversities were significantly found in SUVmax, SUVmean, SBR, and TLG of the lesions (P < 0.05). According to the grouped analysis based on lesion size, for lesions smaller than 1 cm and 2 cm, there was a significant difference in SUVmean, SUVmax, SBR, and MTV, but not in lesions larger than or equal to 2 cm (P > 0.05), and the liver background SUVmean (P > 0.05) remained unchanged.

CONCLUSION

BPL reconstruction algorithm could effectively improve clinical image quality and diagnostic certainty. In quantitative analysis, there were no significant differences among different pathological groups, but there were significant diversities in lesion sizes. Especially for small lesions, lesion SUVmax increased and SBR was significantly improved, which may better assist in the diagnosis of small lesions of lymphoma.

Influences on PET Quantification and Interpretation

Various factors have been identified that influence quantitative accuracy and image interpretation in positron emission tomography (PET). Through the continuous introduction of new PET technology-both imaging hardware and reconstruction software-into clinical care, we now find ourselves in a transition period in which traditional and new technologies coexist. The effects on the clinical value of PET imaging and its interpretation in routine clinical practice require careful reevaluation. In this review, we provide a comprehensive summary of important factors influencing quantification and interpretation with a focus on recent developments in PET technology. Finally, we discuss the relationship between quantitative accuracy and subjective image interpretation.

The effect of Q.Clear reconstruction on quantification and spatial resolution of 18F-FDG PET in simultaneous PET/MR

Background

Q.Clear is a block sequential regularized expectation maximization penalized-likelihood reconstruction algorithm for Positron Emission Tomography (PET). It has shown high potential in improving image reconstruction quality and quantification accuracy in PET/CT system. However, the evaluation of Q.Clear in PET/MR system, especially for clinical applications, is still rare. This study aimed to evaluate the impact of Q.Clear on the ¹⁸F-fluorodeoxyglucose (FDG) PET/MR system and to determine the optimal penalization factor β for clinical use.

Methods

A PET National Electrical Manufacturers Association/ International Electrotechnical Commission (NEMA/IEC) phantom was scanned on GE SIGNA PET/MR, based on NEMA NU 2-2012 standard. Metrics including contrast recovery (CR), background variability (BV), signal-to-noise ratio (SNR) and spatial resolution were evaluated for phantom data. For clinical data, lesion SNR, signal to background ratio (SBR), noise level and visual scores were evaluated. PET images reconstructed from OSEM + TOF and Q.Clear were visually compared and statistically analyzed, where OSEM + TOF adopted point spread function as default procedure, and Q.Clear used different β values of 100, 200, 300, 400, 500, 800, 1100 and 1400.

Results

For phantom data, as β value increased, CR and BV of all sizes of spheres decreased in general; images reconstructed from Q.Clear reached the peak SNR with β value of 400 and generally had better resolution than those from OSEM + TOF. For clinical data, compared with OSEM + TOF, Q.Clear with β value of 400 achieved 138% increment in median SNR (from 58.8 to 166.0), 59% increment in median SBR (from 4.2 to 6.8) and 38% decrement in median noise level (from 0.14 to 0.09). Based on visual assessment from two physicians, Q.Clear with β values ranging from 200 to 400 consistently achieved higher scores than OSEM + TOF, where β value of 400 was considered optimal.

Conclusions

The present study indicated that, on ¹⁸F-FDG PET/MR, Q.Clear reconstruction improved the image quality compared to OSEM + TOF. β value of 400 was optimal for Q.Clear reconstruction.

Compared to conventional PET/CT scanners, silicon-photomultiplier-based PET/CT scanners show higher arterial 18F-FDG uptake in whole-body 18F-FDG-PET/CT

OBJECTIVES

To clarify differences in arterial 18F-FDG (fluorodeoxyglucose) uptake between silicon photomultiplier (SiPM)-based and conventional PET/CT scanners, and to compare clinical and phantom results.

PATIENTS AND METHODS

Twenty-six patients with lung tumours underwent serial SiPM-based and conventional PET/CT scans on the same day. We compared the target-to-background ratios [TBRsi (SiPM), TBRc (conventional)] and the percentage difference between TBRsi and TBRc (ΔTBR) in the carotid artery, aorta and peripheral arteries. The correlation between ΔTBR and vessel size was also investigated. In the carotid artery, active segment analyses were performed with the threshold (TBR ≥1.6), and we compared each scanner's ratio of active segments and TBR values. We compared the clinical results with the recovery coefficients (RCs).

RESULTS

The TBRsi was significantly higher than the TBRc in the carotid artery, aorta and peripheral arteries (1.63 ± 0.22 vs. 1.43 ± 0.22, 1.65 ± 0.19 vs. 1.53 ± 0.15 and 1.37 ± 0.31 vs. 1.11 ± 0.27, mean ± SD, P ≤ 0.0001 for all), and the peripheral arteries showed the highest ΔTBR (24.4 ± 16.8%). The small (10-15 mm) vessels (26.9 ± 15.9%) showed significantly higher ΔTBRs than the larger vessels (7.3 ± 8.5% for 15-20 mm, 8.0 ± 12.8% for ≥20 mm, P < 0.0001 for both). The carotid artery showed significantly higher ratios of active segment (54.5 vs. 20.5%, P < 0.0001) and TBR values (1.85 ± 0.25 vs. 1.76 ± 0.15, P = 0.0006) for TBRsi vs. TBRc. The differences in RCs were similar to those of ΔTBR for each vessel size.

CONCLUSIONS

SiPM-based PET/CT scanners showed higher arterial 18F-FDG uptake (especially in vessels <15 mm) than conventional scanners, and the threshold TBR ≥1.6 is not applicable for the carotid artery for SiPM-based PET/CT systems.

Digital PET vs Analog PET: Clinical Implications?

Positron emission tomography (PET) is a functional imaging technique introduced in 1970s. Over the years, PET was used alone but is in 2000 when the first hybrid PET/CT device was clinically introduced. Since then, PET has continuously been marked by technological developments, being the most recent one the introduction of silicon photomultipliers (SiPMs) as an alternative to standard photomultiplier tubes used in analog PET/CT systems. SiPMs, the basis for the so called digital PET/CT systems, are smaller than standard photomultiplier tubes (enabling higher spatial resolution) and provide up to 100% coverage of the crystal area, as well as high sensitivity, low noise, and fast timing resolution. SiPMs in combination with optimized acquisition and reconstruction parameters improve the localization of the annihilation events, provide high definition PET images, and offer higher sensitivity and higher diagnostic performance. This article summarizes the evidence about the superior performance of the state of the art digital PET and highlights its potential clinical implications. Digital PET opens new perspectives in the quantification and characterization of small lesions, which are mostly undetectable using analog PET systems, potentially changing patient management and improving outcomes in oncological and non-oncological diseases. Moreover, digital PET offers the possibility to reduce radiation dose and scan times which may facilitate the implementation of PET to address unmet clinical needs.

Evaluation of the Accuracy of Standardized Uptake Values of 18F-fluorodeoxyglucose in Lung Lesions Based on Phantom Studies

The aim of the study was to estimate the accuracy of standardized uptake values of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) in lung lesions during positron emission tomography combined with computed tomography (PET/CT) imaging, based on phantom studies performed for different PET/CT scanners.

A dedicated paediatric [18F]FDG PET/CT dosage regimen

BACKGROUND

The role of 2-[¹⁸F]fluoro-2-deoxy-D-glucose ([¹⁸F]FDG) positron emission tomography/computed tomography (PET/CT) in children is still expanding. Dedicated paediatric dosage regimens are needed to keep the radiation dose as low as reasonably achievable and reduce the risk of radiation-induced carcinogenesis. The aim of this study is to investigate the relation between patient-dependent parameters and [¹⁸F]FDG PET image quality in order to propose a dedicated paediatric dose regimen.

METHODS

In this retrospective analysis, 102 children and 85 adults were included that underwent a diagnostic [¹⁸F]FDG PET/CT scan. The image quality of the PET scans was measured by the signal-to-noise ratio (SNR) in the liver. The SNR liver was normalized (SNRnorm) for administered activity and acquisition time to apply curve fitting with body weight, body length, body mass index, body weight/body length and body surface area. Curve fitting was performed with two power fits, a nonlinear two-parameter model α p^-d and a linear single-parameter model α p^-0.5. The fit parameters of the preferred model were combined with a user preferred SNR to obtain at least moderate or good image quality for the dosage regimen proposal.

RESULTS

Body weight demonstrated the highest coefficient of determination for the nonlinear (R² = 0.81) and linear (R² = 0.80) models. The nonlinear model was preferred by the Akaike's corrected information criterion. We decided to use a SNR of 6.5, based on the expert opinion of three nuclear medicine physicians. Comparison with the quadratic adult protocol confirmed the need for different dosage regimens for both patient groups. In this study, the amount of administered activity can be considerably reduced in comparison with the current paediatric guidelines.

CONCLUSION

Body weight has the strongest relation with [¹⁸F]FDG PET image quality in children. The proposed nonlinear dosage regimen based on body mass will provide a constant and clinical sufficient image quality with a significant reduction of the effective dose compared to the current guidelines. A dedicated paediatric dosage regimen is necessary, as a universal dosing regimen for paediatric and adult is not feasible.

[Influence of Reconstruction FOV and Matrix Size on the Quantitative Accuracy of FDG-PET: Comparison between OSEM and Bayesian Penalized Likelihood]

PURPOSE

Field of view (FOV) and matrix size determine the pixel size of positron emission tomography (PET) images; however, the effect of any variation in these parameters on the quantitative accuracy is unclear. The FOV and matrix size of PET images are adjusted as per each clinical objective. Therefore, this study aimed to evaluate the quantitative accuracy of PET images under different FOV and matrix sizes.

METHOD

A National Electrical Manufacturers Association (NEMA) body phantom set was filled with ¹⁸F-FDG solution, and imaging data were acquired for 30 min. Images were reconstructed using ordered subset expectation maximization (OSEM) and Bayesian penalized likelihood (BPL), both of which were combined with point spread function (PSF) and time of flight (TOF). In each reconstruction method, the image parameters were set to the following: FOV, 20-70 cm; matrix size, 128×128 to 384×384; and pixel size, 1-3 mm. The images were evaluated by physical assessment of the recovery coefficient (RC) and maximum standardized uptake value ratio (SUV_{max ratio}).

RESULT

The RC of OSEM images was not affected by changes in FOV, whereas the RC of BPL images decreased in small spheres, when FOV was 20 and 30 cm. The SUV_{max ratio} of the OSEM images was not affected by the difference in pixel size. However, the SUV_{max ratio} of BPL images degraded in the 1-mm pixel size; this influence was observed only when the FOV was changed. Conclusion: BPL images reconstructed using a small FOV might degrade the quantitative accuracy of small spheres.

Phantom and clinical assessment of small pulmonary nodules using Q.Clear reconstruction on a silicon-photomultiplier-based time-of-flight PET/CT system

To evaluate the quantification accuracy of different positron emission tomography-computed tomography (PET/CT) reconstruction algorithms, we measured the recovery coefficient (RC) and contrast recovery (CR) in phantom studies. The results played a guiding role in the partial-volume-effect correction (PVC) for following clinical evaluations. The PET images were reconstructed with four different methods: ordered subsets expectation maximization (OSEM), OSEM with time-of-flight (TOF), OSEM with TOF and point spread function (PSF), and Bayesian penalized likelihood (BPL, known as Q.Clear in the PET/CT of GE Healthcare). In clinical studies, SUVmax and SUVmean (the maximum and mean of the standardized uptake values, SUVs) of 75 small pulmonary nodules (sub-centimeter group: < 10 mm and medium-size group: 10-25 mm) were measured from 26 patients. Results show that Q.Clear produced higher RC and CR values, which can improve quantification accuracy compared with other methods (P < 0.05), except for the RC of 37 mm sphere (P > 0.05). The SUVs of sub-centimeter fludeoxyglucose (FDG)-avid pulmonary nodules with Q.Clear illustrated highly significant differences from those reconstructed with other algorithms (P < 0.001). After performing the PVC, highly significant differences (P < 0.001) still existed in the SUVmean measured by Q.Clear comparing with those measured by the other algorithms. Our results suggest that the Q.Clear reconstruction algorithm improved the quantification accuracy towards the true uptake, which potentially promotes the diagnostic confidence and treatment response evaluations with PET/CT imaging, especially for the sub-centimeter pulmonary nodules. For small lesions, PVC is essential.

Post-reconstruction enhancement of [18F]FDG PET images with a convolutional neural network

BACKGROUND

The aim of the study was to develop and test an artificial intelligence (AI)-based method to improve the quality of [18F]fluorodeoxyglucose (FDG) positron emission tomography (PET) images.

METHODS

A convolutional neural network (CNN) was trained by using pairs of excellent (acquisition time of 6 min/bed position) and standard (acquisition time of 1.5 min/bed position) or sub-standard (acquisition time of 1 min/bed position) images from 72 patients. A test group of 25 patients was used to validate the CNN qualitatively and quantitatively with 5 different image sets per patient: 4 min/bed position, 1.5 min/bed position with and without CNN, and 1 min/bed position with and without CNN.

RESULTS

Difference in hotspot maximum or peak standardized uptake value between the standard 1.5 min and 1.5 min CNN images fell short of significance. Coefficient of variation, the noise level, was lower in the CNN-enhanced images compared with standard 1 min and 1.5 min images. Physicians ranked the 1.5 min CNN and the 4 min images highest regarding image quality (noise and contrast) and the standard 1 min images lowest.

CONCLUSIONS

AI can enhance [18F]FDG-PET images to reduce noise and increase contrast compared with standard images whilst keeping SUVmax/peak stability. There were significant differences in scoring between the 1.5 min and 1.5 min CNN image sets in all comparisons, the latter had higher scores in noise and contrast. Furthermore, difference in SUVmax and SUVpeak fell short of significance for that pair. The improved image quality can potentially be used either to provide better images to the nuclear medicine physicians or to reduce acquisition time/administered activity.

Impact of the Noise Penalty Factor on Quantification in Bayesian Penalized Likelihood (Q.Clear) Reconstructions of 68Ga-PSMA PET/CT Scans

Functional imaging with ⁶⁸Ga prostate-specific membrane antigen (PSMA) and positron emission tomography (PET) can fulfill an important role in treatment selection and adjustment in prostate cancer. This article focusses on quantitative assessment of ⁶⁸Ga-PSMA-PET. The effect of various parameters on standardized uptake values (SUVs) is explored, and an optimal Bayesian penalized likelihood (BPL) reconstruction is suggested. PET acquisitions of two phantoms consisting of a background compartment and spheres with diameter 4 mm to 37 mm, both filled with solutions of ⁶⁸Ga in water, were performed with a GE Discovery 710 PET/CT scanner. Recovery coefficients (RCs) in multiple reconstructions with varying noise penalty factors and acquisition times were determined and analyzed. Apparent recovery coefficients of spheres with a diameter smaller than 17 mm were significantly lower than those of spheres with a diameter of 17 mm and bigger (p < 0.001) for a tumor-to-background (T/B) ratio of 10:1 and a scan time of 10 min per bed position. With a T/B ratio of 10:1, the four largest spheres exhibit significantly higher RCs than those with a T/B ratio of 20:1 (p < 0.0001). For spheres with a diameter of 8 mm and less, alignment with the voxel grid potentially affects the RC. Evaluation of PET/CT scans using (semi-)quantitative measures such as SUVs should be performed with great caution, as SUVs are influenced by scanning and reconstruction parameters. Based on the evaluation of multiple reconstructions with different β of phantom scans, an intermediate β (600) is suggested as the optimal value for the reconstruction of clinical ⁶⁸Ga-PSMA PET/CT scans, considering that both detectability and reproducibility are relevant.

Impact of total variation regularized expectation maximization reconstruction on the image quality of 68Ga-PSMA PET: a phantom and patient study

OBJECTIVES

To investigate the impact of total variation regularized expectation maximization (TVREM) reconstruction on the image quality of 68Ga-PSMA-11 PET/CT using phantom and patient data.

METHODS

Images of a phantom with small hot sphere inserts and 20 prostate cancer patients were acquired with a digital PET/CT using list-mode and reconstructed with ordered subset expectation maximization (OSEM) and TVREM with seven penalisation factors between 0.01 and 0.42 for 2 and 3 minutes-per-bed (m/b) acquisition. The contrast recovery (CR) and background variability (BV) of the phantom, image noise of the liver, and SUVmax of the lesions were measured. Qualitative image quality was scored by two radiologists using a 5-point scale (1-poor, 5-excellent).

RESULTS

The performance of CR, BV, and image noise, and the gain of SUVmax was higher for TVREM 2 m/b groups with the penalization of 0.07 to 0.28 compared to OSEM 3 m/b group (all p < 0.05). The image noise of OSEM 3 m/b group was equivalent to TVREM 2 and 3 m/b groups with a penalization of 0.14 and 0.07, while lesions' SUVmax increased 15 and 20%. The highest qualitative score was attained at the penalization of 0.21 (3.30 ± 0.66) for TVREM 2 m/b groups and the penalization 0.14 (3.80 ± 0.41) for 3 m/b group that equal to or greater than OSEM 3 m/b group (2.90 ± 0.45, p = 0.2 and p < 0.001).

CONCLUSIONS

TVREM improves lesion contrast and reduces image noise, which allows shorter acquisition with preserved image quality for PSMA PET/CT.

ADVANCES IN KNOWLEDGE

TVREM reconstruction with optimized penalization factors can generate higher quality PSMA-PET images for prostate cancer diagnosis.

Improved detection of in-transit metastases of malignant melanoma with BSREM reconstruction in digital [18F]FDG PET/CT

OBJECTIVES

To compare block sequential regularized expectation maximization (BSREM) and ordered subset expectation maximization (OSEM) for the detection of in-transit metastasis (ITM) of malignant melanoma in digital [¹⁸F]FDG PET/CT.

METHODS

We retrospectively analyzed a cohort of 100 [¹⁸F]FDG PET/CT scans of melanoma patients with ITM, performed between May 2017 and January 2020. PET images were reconstructed with both OSEM and BSREM algorithms. SUVmax, target-to-background ratio (TBR), and metabolic tumor volume (MTV) were recorded for each ITM. Differences in PET parameters were analyzed with the Wilcoxon signed-rank test. Differences in image quality for different reconstructions were tested using the Man-Whitney U test.

RESULTS

BSREM reconstruction led to the detection of 287 ITM (39% more than OSEM). PET parameters of ITM were significantly different between BSREM and OSEM reconstructions (p < 0.001). SUVmax and TBR were higher (76.5% and 77.7%, respectively) and MTV lower (49.5%) on BSREM. ITM missed with OSEM had significantly lower SUVmax (mean 2.03 vs. 3.84) and TBR (mean 1.18 vs. 2.22) and higher MTV (mean 2.92 vs. 1.01) on OSEM compared to BSREM (all p < 0.001).

CONCLUSIONS

BSREM detects significantly more ITM than OSEM, owing to higher SUVmax, higher TBR, and less blurring. BSREM is particularly helpful in small and less avid lesions, which are more often missed with OSEM.

KEY POINTS

• In melanoma patients, [¹⁸F]FDG PET/CT helps to detect in-transit metastases (ITM), and their detection is improved by using BSREM instead of OSEM reconstruction. • BSREM is particularly useful in small lesions.

Does the beta regularization parameter of bayesian penalized likelihood reconstruction always affect the quantification accuracy and image quality of positron emission tomography computed tomography?

Purpose

This study aims to provide a detailed investigation on the noise penalization factor in Bayesian penalized likelihood (BPL)‐based algorithm, with the utilization of partial volume effect correction (PVC), so as to offer the suitable beta value and optimum standardized uptake value (SUV) parameters in clinical practice for small pulmonary nodules.

Methods

A National Electrical Manufacturers Association (NEMA) image‐quality phantom was scanned and images were reconstructed using BPL with beta values ranged from 100 to 1000. The recovery coefficient (RC), contrast recovery (CR), and background variability (BV) were measured to assess the quantification accuracy and image quality. In the clinical assessment, lesions were categorized into sub‐centimeter (<10 mm, n = 7) group and medium size (10–30 mm, n = 16) group. Signal‐to‐noise ratio (SNR) and contrast‐to‐noise ratio (CNR) were measured to evaluate the image quality and lesion detectability. With PVC was performed, the impact of beta values on SUVs (SUVmax, SUVmean, SUVpeak) of small pulmonary nodules was evaluated. Subjective image analysis was performed by two experienced readers.

Results

With the increasing of beta values, RC, CR, and BV decreased gradually in the phantom work. In the clinical study, SNR and CNR of both groups increased with the beta values (P < 0.001), although the sub‐centimeter group showed increases after the beta value reached over 700. In addition, highly significant negative correlations were observed between SUVs and beta values for both lesion‐size groups before the PVC (P < 0.001 for all). After the PVC, SUVpeak measured from the sub‐centimeter group was no significantly different among different beta values (P = 0.830).

Conclusion

Our study suggests using SUVpeak as the quantification parameter with PVC performed to mitigate the effects of beta regularization. Beta values between 300 and 400 were preferred for pulmonary nodules smaller than 30 mm.

Head-to-head comparison of a Si-photomultiplier-based and a conventional photomultiplier-based PET-CT system

BACKGROUND

A novel generation of PET scanners based on silicon (Si)-photomultiplier (PM) technology has recently been introduced. Concurrently, there has been development of new reconstruction methods aimed at increasing the detectability of small lesions without increasing image noise. The combination of new detector technologies and new reconstruction algorithms has been found to increase image quality. However, it is unknown to what extent the demonstrated improvement of image quality is due to scanner hardware development or improved reconstruction algorithms. To isolate the contribution of the hardware, this study aimed to compare the ability to detect small hotspots in phantoms using the latest generation SiPM-based PET/CT scanner (GE Discovery MI) relative to conventional PM-based PET/CT scanner (GE Discovery 690), using identical reconstruction protocols.

MATERIALS AND METHODS

Two different phantoms (NEMA body and Jasczcak) with fillable spheres (31 μl to 26.5 ml) and varying sphere-to-background-ratios (SBR) were scanned in one bed position for 15-600 s on both scanners. The data were reconstructed using identical reconstruction parameters on both scanners. The recovery-coefficient (RC), noise level, contrast (sphere_peak/background_peak-value), and detectability of each sphere were calculated and compared between the scanners at each acquisition time.

RESULTS

The RC-curves for the NEMA phantom were near-identical for both scanners at SBR 10:1. For smaller spheres in the Jaszczak phantom, the contrast was 1.22 higher for the DMI scanner at SBR 15:1. The ratio decreased for lower SBR, with a ratio of 1.03 at SBR 3.85:1. Regarding the detectability of spheres, the sensitivity was 98% and 88% for the DMI and D690, respectively, for SBR 15:1. For SBR 7.5, the sensitivity was 75% and 83% for the DMI and D690, respectively. For SBR 3.85:1, the sensitivity was 43% and 30% for the DMI and D690, respectively.

CONCLUSION

Marginally higher contrast in small spheres was seen for the SiPM-based scanner but there was no significant difference in detectability between the scanners. It was difficult to detect differences between the scanners, suggesting that the SiPM-based detectors are not the primary reason for improved image quality.

Can a penalized-likelihood estimation algorithm be used to reduce the injected dose or the acquisition time in 68Ga-DOTATATE PET/CT studies?

Background

Image quality and quantitative accuracy of positron emission tomography (PET) depend on several factors such as uptake time, scanner characteristics and image reconstruction methods. Ordered subset expectation maximization (OSEM) is considered the gold standard for image reconstruction. Penalized-likelihood estimation (PL) algorithms have been recently developed for PET reconstruction to improve quantitation accuracy while maintaining or even improving image quality. In PL algorithms, a regularization parameter β controls the penalization of relative differences between neighboring pixels and determines image characteristics. In the present study, we aim to compare the performance of Q.Clear (PL algorithm, GE Healthcare) and OSEM (3 iterations, 8 subsets, 6-mm post-processing filter) for ⁶⁸Ga-DOTATATE (⁶⁸Ga-DOTA) PET studies, both visually and quantitatively.

Thirty consecutive whole-body ⁶⁸Ga-DOTA studies were included. The data were acquired in list mode and were reconstructed using 3D OSEM and Q.Clear with various values of β and various acquisition times per bed position (bp), thus generating images with reduced injected dose (1.5 min/bp: β = 300–1100; 1.0 min/bp: β = 600–1400 and 0.5 min/bp: β = 800–2200). An additional analysis adding β values up to 1500, 1700 and 3000 for 1.5, 1.0 and 0.5 min/bp, respectively, was performed for a random sample of 8 studies. Evaluation was performed using a phantom and clinical data. Two experienced nuclear medicine physicians blinded to the variables assessed the image quality visually.

Results

Clinical images reconstructed with Q.Clear, set at 1.5, 1.0 and 0.5 min/bp using β = 1100, 1300 and 3000, respectively, resulted in images with noise equivalence to 3D OSEM (1.5 min/bp) with a mean increase in SUV_max of 14%, 13% and 4%, an increase in SNR of 30%, 24% and 10%, and an increase in SBR of 13%, 13% and 2%. Visual assessment yielded similar results for β values of 1100–1400 and 1300–1600 for 1.5 and 1.0 min/bp, respectively, although for 0.5 min/bp there was no significant improvement compared to OSEM.

Conclusion

⁶⁸Ga-DOTA reconstructions with Q.Clear, 1.5 and 1.0 min/bp, resulted in increased tumor SUV_max and in improved SNR and SBR at a similar level of noise compared to 3D OSEM. Q.Clear with β = 1300–1600 enables one-third reduction of acquisition time or injected dose, with similar image quality compared to 3D OSEM.

Impact of PET data driven respiratory motion correction and BSREM reconstruction of 68Ga-DOTATATE PET/CT for differentiating neuroendocrine tumors (NET) and intrapancreatic accessory spleens (IPAS)

To evaluate whether quantitative PET parameters of motion-corrected ⁶⁸Ga-DOTATATE PET/CT can differentiate between intrapancreatic accessory spleens (IPAS) and pancreatic neuroendocrine tumor (pNET). A total of 498 consecutive patients with neuroendocrine tumors (NET) who underwent ⁶⁸Ga-DOTATATE PET/CT between March 2017 and July 2019 were retrospectively analyzed. Subjects with accessory spleens (n = 43, thereof 7 IPAS) and pNET (n = 9) were included, resulting in a total of 45 scans. PET images were reconstructed using ordered-subsets expectation maximization (OSEM) and a fully convergent iterative image reconstruction algorithm with β-values of 1000 (BSREM₁₀₀₀). A data-driven gating (DDG) technique (MOTIONFREE, GE Healthcare) was applied to extract respiratory triggers and use them for PET motion correction within both reconstructions. PET parameters among different samples were compared using non-parametric tests. Receiver operating characteristics (ROC) analyzed the ability of PET parameters to differentiate IPAS and pNETs. SUVmax was able to distinguish pNET from accessory spleens and IPAs in BSREM₁₀₀₀ reconstructions (p < 0.05). This result was more reliable using DDG-based motion correction (p < 0.003) and was achieved in both OSEM and BSREM₁₀₀₀ reconstructions. For differentiating accessory spleens and pNETs with specificity 100%, the ROC analysis yielded an AUC of 0.742 (sensitivity 56%)/0.765 (sensitivity 56%)/0.846 (sensitivity 62%)/0.840 (sensitivity 63%) for SUVmax 36.7/41.9/36.9/41.7 in OSEM/BSREM₁₀₀₀/OSEM + DDG/BSREM₁₀₀₀ + DDG, respectively. BSREM₁₀₀₀ + DDG can accurately differentiate pNET from accessory spleen. Both BSREM₁₀₀₀ and DDG lead to a significant SUV increase compared to OSEM and non-motion-corrected data.

Direct comparison of brain [18F]FDG images acquired by SiPM-based and PMT-based PET/CT: phantom and clinical studies

Background

Silicon photomultiplier-positron emission tomography (SiPM-PET) has better sensitivity, spatial resolution, and timing resolution than photomultiplier tube (PMT)-PET. The present study aimed to clarify the advantages of SiPM-PET in ¹⁸F-fluoro-2-deoxy-D-glucose ([¹⁸F]FDG) brain imaging in a head-to-head comparison with PMT-PET in phantom and clinical studies.

Methods

Contrast was calculated from images acquired from a Hoffman 3D brain phantom, and image noise and uniformity were calculated from images acquired from a pool phantom using SiPM- and PMT-PET. Sequential PMT-PET and SiPM-PET [¹⁸F]FDG images were acquired over a period of 10 min from 22 controls and 10 patients. All images were separately normalized to a standard [¹⁸F]FDG PET template, then the mean standardized uptake values (SUV_mean) and Z-score were calculated using MIMneuro and CortexID Suite, respectively.

Results

Image contrast, image noise, and uniformity in SiPM-PET changed 19.2, 3.5, and − 40.0% from PMT-PET, respectively. These physical indices of both PET scanners satisfied the criteria for acceptable image quality published by the Japanese Society of Nuclear Medicine of contrast > 55%, CV ≤ 15%, and SD ≤ 0.0249, respectively. Contrast was 70.0% for SiPM-PET without TOF and 59.5% for PMT-PET without TOF. The TOF improved contrast by 3.5% in SiPM-PET. The SUV_mean using SiPM-PET was significantly higher than PMT-PET and did not correlate with a time delay. Z-scores were also significantly higher in images acquired from SiPM-PET (except for the bilateral posterior cingulate) than PMT-PET because the peak signal that was extracted by the calculation of Z-score in CortexID Suite was increased. The hypometabolic area in statistical maps was reduced and localized using SiPM-PET. The trend was independent of whether the images were derived from controls or patients.

Conclusions

The improved spatial resolution and sensitivity of SiPM-PET contributed to better image contrast and uniformity in brain [¹⁸F]FDG images. The SiPM-PET offers better quality and more accurate quantitation of brain PET images. The SUV_mean and Z-scores were higher in SiPM-PET than PMT-PET due to improved PVE. [¹⁸F]FDG images acquired using SiPM-PET will help to improve diagnostic outcomes based on statistical image analysis because SiPM-PET would localize the distribution of glucose metabolism on Z-score maps.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40658-020-00337-4.

Procedural recommendations of cardiac PET/CT imaging: standardization in inflammatory-, infective-, infiltrative-, and innervation (4Is)-related cardiovascular diseases: a joint collaboration of the EACVI and the EANM

With this document, we provide a standard for PET/(diagnostic) CT imaging procedures in cardiovascular diseases that are inflammatory, infective, infiltrative, or associated with dysfunctional innervation (4Is). This standard should be applied in clinical practice and integrated in clinical (multicenter) trials for optimal procedural standardization. A major focus is put on procedures using [¹⁸F]FDG, but 4Is PET radiopharmaceuticals beyond [¹⁸F]FDG are also described in this document. Whilst these novel tracers are currently mainly applied in early clinical trials, some multicenter trials are underway and we foresee in the near future their use in clinical care and inclusion in the clinical guidelines. Finally, PET/MR applications in 4Is cardiovascular diseases are also briefly described. Diagnosis and management of 4Is-related cardiovascular diseases are generally complex and often require a multidisciplinary approach by a team of experts. The new standards described herein should be applied when using PET/CT and PET/MR, within a multimodality imaging framework both in clinical practice and in clinical trials for 4Is cardiovascular indications.

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 (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 SUV_max 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.

[Examination of Optimal Window Size and Acquisition Time of Respiratory-gated PET Image: Phantom Study with a SiPM-based PET/CT Scanner]

PURPOSE

This phantom study aimed to determine the optimal acquisition window size for phase-based respiratory gating in silicon photomultiplier (SiPM)-based fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) and its acquisition time in respiratory-gated imaging with the optimal window size.

METHODS

Images of a moving NEMA IEC Body Phantom Set^TM with hot spheres were acquired. First, the tumor volume and the maximum standardized uptake value (SUV_max) of images reconstructed using a different window size were evaluated to define the optimal window size. Second, the quality of the images reconstructed using the optimal window size and different acquisition times was evaluated using the detectability score of the 10-mm hot sphere and physical indices.

RESULTS

The volume and the SUV_max of the 10-mm hot sphere were improved when the window size was narrow, and there were no significant differences among images reconstructed using a window size narrower than 20%. To reconstruct an image using the 20% window size, an acquisition time of 5 min was required to visualize the 10-mm hot sphere.

CONCLUSIONS

The optimal window size for phase-based respiratory gating is 20%. Further, an acquisition time of 5 min should be taken for respiratory-gated imaging with the 20% window size on SiPM-based FDG-PET/CT.

Image reconstruction methods affect software-aided assessment of pathologies of [18F]flutemetamol and [18F]FDG brain-PET examinations in patients with neurodegenerative diseases

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[¹⁸F]Flutemetamol and [¹⁸F]FDG image reconstruction.

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Software-aided assessment of neurodegenerative disease patients.

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New developments in brain PET image reconstruction affect quantitative measures.

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Evaluation of SUVR and z-score measures.

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Normalizing to pons and whole brain induced greater absolute differences between reconstructions.

Purpose

To assess how some of the new developments in brain positron emission tomography (PET) image reconstruction affect quantitative measures and software-aided assessment of pathology in patients with neurodegenerative diseases.

Methods

PET data were grouped into four cohorts: prodromal Alzheimer’s disease patients and controls receiving [¹⁸F]flutemetamol, and neurodegenerative disease patients and controls receiving [¹⁸F]FDG PET scans. Reconstructed images were obtained by ordered-subsets expectation maximization (OSEM; 3 iterations (i), 16/34 subsets (s), 3/5-mm filter, ±time-of-flight (TOF), ±point-spread function (PSF)) and block-sequential regularized expectation maximization (BSREM; TOF, PSF, β-value 75–300). Standardized uptake value ratios (SUVR) and z-scores were calculated (CortexID Suite, GE Healthcare) using cerebellar gray matter, pons, whole cerebellum and whole brain as reference regions.

Results

In controls, comparable results to the normal database were obtained with OSEM 3i/16 s 5-mm reconstruction. TOF, PSF and BSREM either increased or decreased the relative uptake difference to the normal subjects’ database within the software, depending on the tracer and chosen reference area, i.e. resulting in increased absolute z-scores. Normalizing to pons and whole brain for [¹⁸F]flutemetamol and [¹⁸F]FDG, respectively, increased absolute differences between reconstructions methods compared to normalizing to cerebellar gray matter and whole cerebellum when applying TOF, PSF and BSREM.

Conclusions

Software-aided assessment of patient pathologies should be used with caution when employing other image reconstruction methods than those used for acquisition of the normal database.

Evaluation of block-sequential regularized expectation maximization reconstruction of 68Ga-DOTATOC, 18F-fluoride, and 11C-acetate whole-body examinations acquired on a digital time-of-flight PET/CT scanner

Background

Block-sequential regularized expectation maximization (BSREM) is a fully convergent iterative image reconstruction algorithm. We hypothesize that tracers with different distribution patterns will result in different optimal settings for the BSREM algorithm. The aim of this study was to evaluate the image quality with variations in the applied β-value and acquisition time for three positron emission tomography (PET) tracers. NEMA image quality phantom measurements and clinical whole-body digital time-of-flight (TOF) PET/computed tomography (CT) examinations with ⁶⁸Ga-DOTATOC (n = 13), ¹⁸F-fluoride (n = 10), and ¹¹C-acetate (n = 13) were included. Each scan was reconstructed using BSREM with β-values of 133, 267, 400, and 533, and ordered subsets expectation maximization (OSEM; 3 iterations, 16 subsets, and 5-mm Gaussian post-processing filter). Both reconstruction methods included TOF and point spread function (PSF) recovery. Quantitative measures of noise, signal-to-noise ratio (SNR), and signal-to-background ratio (SBR) were analysed for various acquisition times per bed position (bp).

Results

The highest β-value resulted in the lowest level of noise, which in turn resulted in the highest SNR and lowest SBR. Noise levels equal to or lower than those of OSEM were found with β-values equal to or higher than 400, 533, and 267 for ⁶⁸Ga-DOTATOC, ¹⁸F-fluoride, and ¹¹C-acetate, respectively. The specified β-ranges resulted in increased SNR at a minimum of 25% (P < 0.0001) and SBR at a maximum of 23% (P < 0.0001) as compared to OSEM. At a reduced acquisition time by 25% for ⁶⁸Ga-DOTATOC and ¹⁸F-fluoride, and 67% for ¹¹C-acetate, BSREM with β-values equal to or higher than 533 resulted in noise equal to or lower than that of OSEM at full acquisition duration (2 min/bp for ⁶⁸Ga-DOTATOC and ¹⁸F-fluoride, 3 min/bp for ¹¹C-acetate). The reduced acquisition time with β 533 resulted in increased SNR (16–26%, P < 0.003) and SBR (6–18%, P < 0.0001 (P = 0.07 for ¹¹C-acetate)) compared to the full acquisition OSEM.

Conclusions

Within tracer-specific ranges of β-values, BSREM reconstruction resulted in increased SNR and SBR with respect to conventional OSEM reconstruction. Similar SNR, SBR, and noise levels could be attained with BSREM at relatively shorter acquisition times or, alternatively, lower administered dosages, compared to those attained with OSEM.

Clinical evaluation of reconstruction and acquisition time for pediatric 18F-FDG brain PET using digital PET/CT

BACKGROUND

¹⁸F-2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) plays an important role in the diagnosis, evaluation and treatment of childhood epilepsy. The selection of appropriate acquisition and reconstruction parameters, however, can be challenging with the introduction of advanced hardware and software functionalities.

OBJECTIVE

To quantify the diagnostic performance of a block-sequential regularized expectation maximization (BSREM) tool and reduced effective counts in brain PET/CT for pediatric epilepsy patients on a digital silicon photomultiplier system.

MATERIALS AND METHODS

We included 400 sets of brain PET/CT images from 25 pediatric patients (0.5-16 years old) in this retrospective study. Patient images were reconstructed with conventional iterative techniques or BSREM with varied penalization factor (β), at varied acquisition time (45 s, 90 s, 180 s, 300 s) to simulate reduced count density. Two pediatric nuclear medicine physicians reviewed images in random order - blinded to patient, reconstruction method and imaging time - and scored technical quality (noise, spatial resolution, artifacts), clinical quality (image quality of the cortex, basal ganglia and thalamus) and overall diagnostic satisfaction on a 5-point scale.

RESULTS

Reconstruction with BSREM improved quality and clinical scores across all count levels, with the greatest benefits in low-count conditions. Image quality scores were greatest at 300-s acquisition times with β=500 (overall; noise; artifacts; image quality of the cortex, basal ganglia and thalamus) or β=200 (spatial resolution). No statistically significant difference in the highest graded reconstruction was observed between imaging at 180 s and 300 s with an appropriately implemented penalization factor (β=350-500), indicating that a reduction in dose or acquisition time is feasible without reduction in diagnostic satisfaction.

CONCLUSION

Clinical evaluation of pediatric ¹⁸F-FDG brain PET image quality was shown to be diagnostic at reductions of count density by 40% using BSREM with a penalization factor of β=350-500. This can be accomplished while maintaining confidence of achieving a diagnostic-quality image.

Optimization of [18F]PSMA-1007 PET-CT using regularized reconstruction in patients with prostate cancer

BACKGROUND

Prostate-specific membrane antigen (PSMA) radiotracers such as [¹⁸F]PSMA-1007 used with positron emission tomography-computed tomography (PET-CT) is promising for initial staging and detection of recurrent disease in prostate cancer patients. The block-sequential regularization expectation maximization algorithm (BSREM) is a new PET reconstruction algorithm, which provides higher image contrast while also reducing noise. The aim of the present study was to evaluate the influence of different acquisition times and different noise-suppressing factors in BSREM (β values) in [¹⁸F]PSMA-1007 PET-CT regarding quantitative data as well as a visual image quality assessment. We included 35 patients referred for clinical [¹⁸F]PSMA-1007 PET-CT. Four megabecquerels per kilogramme were administered and imaging was performed after 120 min. Eighty-four image series per patient were created with combinations of acquisition times of 1-4 min/bed position and β values of 300-1400. The noise level in normal tissue and the contrast-to-noise ratio (CNR) of pathological uptakes versus the local background were calculated. Image quality was assessed by experienced nuclear medicine physicians.

RESULTS

The noise level in the liver, spleen, and muscle was higher for low β values and low acquisition times (written as activity time products (ATs = administered activity × acquisition time)) and was minimized at maximum AT (16 MBq/kg min) and maximum β (1400). There was only a small decrease above AT 10. The median CNR increased slowly with AT from approximately 6 to 12 and was substantially lower at AT 4 and higher at AT 14-16. At AT 4-6, many images were regarded as being of unacceptable quality. For AT 8, β values of 700-900 were considered of acceptable quality.

CONCLUSIONS

An AT of 8 (for example as in our study, 4 MB/kg with an acquisition time of 2 min) with a β value of 700 performs well regarding noise level, CNR, and visual image quality assessment.