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Purpose: A solid-state PET/CT system uses bismuth germanium oxide (BGO) scintillating crystals coupled to silicon photomultipliers over an extended 32 cm axial field-of-view (FOV) to provide high spatial resolution and very high sensitivity. Performance characteristics were determined for this digital-BGO system, including NEMA and EARL standards. Methods: Spatial resolution, scatter fraction (SF), noise equivalent count rate (NECR), sensitivity, count rate accuracy, and image quality (IQ) were evaluated for the digital-BGO system as per NEMA NU 2-2018, at 2 sites of first clinical install. System energy resolution was measured. Bayesian penalized-likelihood reconstruction (BPL) was used for IQ. EARL Standards 2 studies were reconstructed by BPL combined with a contrast-enhancing deep learning algorithm. An Esser PET phantom was evaluated. Three patient examples were obtained with low-dose radiotracer activity: 2 MBq/kg of [18F]FDG ([18F]-2-fluoro-2-deoxy-d-glucose), 2.3 MBq/kg [68Ga]Ga-DOTA-TATE ([dodecane tetra-acetic acid,Tyr3]-octreotate), and 14.5 MBq/kg [82Rb]RbCl ([82Rb]-rubidium-chloride). Total scan times were ≤ 8 min. Results: NEMA sensitivity was 47.6 cps/kBq at the axial center. Spatial resolution at 1 cm from the center axis was ≤4.5 mm (filtered back projection) and ≤3.8 mm (ordered subset expectation maximization). SF was 35.6%, count rate accuracy was 2.16%, and peak NECR was 485.2 kcps at 16.9 kBq/mL. Contrast for IQ was 61.1 to 90.7% (smallest to largest sphere) with background variations from 7.6 to 2.1%, and a "lung" error of 4.7%. The average detector energy resolution was 9.67%. Image quality for patient scans was good. EARL Standards 2 criteria were robustly met and Esser phantom features ≥4.8 mm were resolved at 2 min per bed position. Conclusion: A solid-state 32 cm axial FOV digital-BGO PET/CT system provides good spatial and energy resolution, high count rates, and superior NEMA sensitivity in its class, enabling fast clinical acquisitions with low-dose radiotracer activity. [ABSTRACT FROM AUTHOR]

Background: Performance assessment of positron emission tomography (PET) scanners is crucial to guide clinical practice with efficiency. We have already introduced and experimentally evaluated a simulation method allowing the creation of a controlled ground truth for system performance assessment. In the current study, the goal was to validate the method using patient data and demonstrate its relevance to assess PET performances accuracy in clinical conditions. Methods: Twenty-four patients were recruited and sorted into two groups according to their body mass index (BMI). They were administered with a single dose of 2 MBq/kg 18F-FDG and scanned using clinical protocols consecutively on two PET systems: the Discovery-IQ (DIQ) and the Discovery-MI (DMI). For each BMI group, sixty synthetic lesions were dispatched in three subgroups and inserted at relevant anatomical locations. Insertion of synthetic lesions (ISL) was performed at the same location into the two consecutive exams. Two nuclear medicine physicians evaluated individually and blindly the images by qualitatively and semi-quantitatively reporting each detected lesion and agreed on a consensus. We assessed the inter-system detection rates of synthetic lesions and compared it to an initial estimate of at least 1.7 more targets detected on the DMI and the detection rates of natural lesions. We determined the inter-reader variability, evaluated according to the inter-observer agreement (IOA). Adequate inter-reader variability was found for IOA above 80%. Differences in standardized uptake value (SUV) metrics were also studied. Results: In the BMI ≤ 25 group, the relative true positive rate (RTPR) for synthetic and natural lesions was 1.79 and 1.83, respectively. In the BMI > 25 group, the RTPR for synthetic and natural lesions was 2.03 and 2.27, respectively. For each BMI group, the detection rate using ISL was consistent to our estimate and with the detection rate measured on natural lesions. IOA above 80% was verified for any scenario. SUV metrics showed a good agreement between synthetic and natural lesions. Conclusions: ISL proved relevant to evaluate performance differences between PET scanners. Using these synthetically modified clinical images, we can produce a controlled ground truth in a realistic anatomical model and exploit the potential of PET scanner for clinical purposes. [ABSTRACT FROM AUTHOR]

Background: Performance assessment of positron emission tomography (PET) scanners is crucial to guide clinical practice with efficiency. Even though clinical data are the final target, their use to characterize systems response is constrained by the lack of ground truth. Phantom tests overcome this limitation by controlling the object of study, but remain simple and are not representative of patient complexity. The objective of this study is to evaluate the accuracy of a simulation method using synthetic spheres inserted into acquired raw data prior to reconstruction, simulating multiple scenarios in comparison with equivalent physical experiments. Methods: We defined our experimental framework using the National Electrical Manufacturers Association NU-2 2018 Image Quality standard, but replaced the standard sphere set with more appropriate sizes (4, 5, 6, 8, 10 and 13 mm) better suited to current PET scanner performance. Four experiments, with different spheres-to-background ratios (2:1, 4:1, 6:1 and 8:1), were performed. An additional dataset was acquired with a radioactive background but no activity within the spheres (water only) to establish a baseline. Then, we artificially simulated radioactive spheres to reproduce other experiments using synthetic data inserted into the original sinogram. Images were reconstructed following standard guidelines using ordered subset expectation maximization algorithm along with a Bayesian penalized likelihood algorithm. We first visually compared experimental and simulated images. Afterward, we measured the activity concentration values into the spheres to calculate the mean and maximum recovery coefficients (RCmean and RCmax) which we used in a quantitative analysis. Results: No significant visual differences were identified between experimental and simulated series. Mann–Whitney U tests comparing simulated and experimental distributions showed no statistical differences for both RCmean (P value = 0.611) and RCmax (P value = 0.720). Spearman tests revealed high correlation for RCmean (ρ = 0.974, P value < 0.001) and RCmax (ρ = 0.974, P value < 0.001) between both datasets. From Bland–Altman plots, we highlighted slight shifts in RCmean and RCmax of, respectively, 2.1 ± 16.9% and 3.3 ± 22.3%. Conclusions: We evaluated the efficiency of our hybrid method in faithfully mimicking practical situations producing satisfactory results compared to equivalent experimental data. [ABSTRACT FROM AUTHOR]