Between March 17, 2019, and June 19, 2019, 65 consecutive patients underwent 68Ga-DOTA PET/CT scans at our institution. Inclusion criteria for this study were (a) images were acquired on General Electric (GE) Healthcare Discovery MI PET/CT scanner (Milwaukee WI, USA) and (b) at least one focus of pathological 68Ga-DOTA uptake was noted on the PET/CT study.
Of the 65 patients 35 patients were excluded from the study, 21 patients with normal studies without focus of pathological uptake and 14 patients performed 68Ga-DOTA PET/CT on another PET/CT system (Discovery MI-DR, GE Healthcare) at our institution. The remaining 30 patients (19 men, 11 women; mean ± SD, 58 ± 19 years old; range 11–83 years) were included in this single-center retrospective study.
All studies were performed on a Discovery MI PET/CT (GE Healthcare). The system combines a 128-slice computed tomography (CT) system and a 4-ring PET system with LightBurst digital detectors providing a 20-cm axial field-of-view and a 70-cm transaxial field-of-view. The system is TOF-capable with a timing resolution of 377 ps .
Phantom Acquisition. The National Electrical Manufacturers Association (NEMA) IEC image quality body phantom (IQBP) (Model PET/IEC-BODY/P)  was used to provide an overall assessment of the imaging capabilities of the system in different conditions. The phantom contains spheres with an internal diameter of 10, 13, 17, 22, 28, and 37 mm and a 50-mm diameter cylindrical insert mounted in its center. All the spheres were filled with radioactive material (68Ga) and lung insert provided with the phantom was filled with low-density material (polystyrene) and water. The phantom was filled to reach a target-to-background ratio of 4:1. The background region and spheres contained a 68Ga activity concentration of 2.48 kBq/mL and 9.92 kBq/mL, respectively, at the time of acquisition. The phantom images were acquired in list-mode with an acquisition time of 3.0 min/bp.
Clinical Images.68Ga-DOTA was injected intravenously following an administration protocol of 2 MBq/kg (minimum-maximum activity: 100-250 Mbq). The mean administered activity was 160.3 ± 32.0 MBq (range,103.6 – 247.9 MBq). The PET acquisition started at a mean of 68 ± 10 min (range, 53 – 91 min) after tracer injection. All PET studies were performed from the proximal femur to the base of the skull (six-eight bed positions) and were acquired in list-mode with an acquisition time of 1.5 min/bp. Patients’ characteristics, injected dose and uptake time are summarized in Table 1.
Phantom and clinical images were first reconstructed with 1.5 min/bp and using the GE VUE Point FX-S algorithm (VPFX-S), a 3D maximum likelihood ordered subset expectation maximization (3D OSEM) image reconstruction algorithm using TOF information and PSF modeling with 3 iterations, 8 subsets and 6 mm post-processing filter. These settings have been adjusted at the installation of the system by the local manufacturer field engineer according to the visual evaluation of 68Ga-DOTA PET images done by experienced physicians. The corresponding reconstructed images are defined as Hadassah OSEM reconstruction thereafter.
In addition, data were reconstructed using the Q.Clear algorithm with different values of the penalization factor β and with 1.5 min/bp, 1.0 min/bp and 0.5 min/bp acquisitions. The 1.5, 1.0 and 0.5 min/bp acquisitions were used to simulate standard, two thirds and one third acquisitions (time or injected dose). Images were reconstructed in a first time with β = 300, 400, 500, 600, 700, 800, 1000 and 1100 for the 1.5 min/bp acquisition, β = 600, 700, 800, 1000, 1100, 1200, and 1300 for the 1.0 min/bp acquisition and β = 800, 1000, 1200, 1300, 1400, 1500, 1600, 1800, 2000 and 2200 for the 0.5 min/bp acquisition. These values were chosen following an initial subjective visual assessment of clinical images performed by one of the authors (AC, who was not involved in the blinded visual assessment of the studies).
After a first quantitative analysis and visual assessment of the images reconstructed with the previous parameters, it seemed that higher β values are to be included in the analysis. Thus, an additional analysis adding β values of 1200, 1300, 1400, 1500 for 1.5 min/bp, 1400, 1500, 1600, 1700 for 1.0 min/bp and 2400, 2600, 2800, 3000 for 0.5 min/bp was performed for a random group of 8 patients. OSEM reconstruction recommended by the manufacturer to be used in clinical setting (3 iterations, 16 subsets, 5 mm post-processing filter) [18,19] was also added to this additional analysis and defined as GE OSEM reconstruction.
All data were corrected for scatter, random events, dead time, and attenuation (using CT).
Images were analyzed as detailed below and previously proposed by Lindström et al.  .
Phantom Data. Background variability (BV) and contrast-to-noise ratio (CNR) were calculated and compared. BV was defined as the SD of the activity concentration in large ROIs (about 4 cm2) located away from the axial plane containing the sphere centers, divided by the mean activity concentration in these background ROIs. CNR was calculated as contrast recovery (CR) divided by BV as follows:
with CH and CB, counts and aH and aB, activities in hot spheres and background ROIs, respectively. Image analysis was done on a GE Healthcare Advantage Workstation (AW 3.2 Ext. 3.2, 2019).
Clinical Images. Level of noise, signal-to-noise ratio (SNR) and signal-to-background ratio (SBR) were calculated and compared. Level of noise was defined as SUVstd of a large spherical VOI in normal liver normalized to SUVmean of the same VOI. SNR was calculated as lesion SUVmax divided by noise level. SBR was defined as lesion SUVmax divided by SUVmean of the normal liver VOI. For this analysis up to three lesions per study (for a total of 75 in the first analysis and 19 in the addiotnal one) were delineated on the AW Workstation using a 41% SUVmax threshold. Lesions VOIs were first built on the Hadassah OSEM images and bookmarks containing the location of these lesions were used to propagate and build new VOIs on reconstructed images with 41% thresholding. Also, lesions SUVmax values obtained for Hadassah OSEM and the reconstructed algorithms leading to similar level of noise were also analyzed and compared. The correlation of the SNR and SBR with the lesion size, penalization factor value, injected activity and patient weight has been evaluated for the three acquisition times.
Blinded Visual Assessment. In the first analysis, whether for the standard acquisition or for each of the simulated reduced injected activity studies, the five Q.Clear reconstructions leading to the best results in phantom and clinical images evaluations were visually compared with the Hadassah OSEM reconstruction by two blinded experienced nuclear medicine physicians (EG and SBH). A total of 90 image sets were assessed; every set consisted of 5 different reconstructions for 1.5, 1.0 and 0.5 min/bp, for each of the 30 patients included in the study. For the additional analysis, the four additional Q.Clear reconstructions and the manufacturer reference GE OSEM, were visually compared with the Hadassah OSEM reconstruction by an experienced reader (SBH). All data were anonymized regarding the reconstruction method and numbers were randomly assigned. PET datasets were rated on a 4-point scale (1 = very poor/nondiagnostic; 2 = poor; 3 = good and 4= very good) for contrast, sharpness, noise, liver homogeneity, tumor detectability and overall image quality.
The mean values for each of the rated parameters by the two readers and the mean values of all scores were summarized. A non-parametric test, Friedman test, for multiple comparisons was performed to evaluate the differences between the various image reconstruction algorithms. When necessary, a correction for ties was applied . When Friedman-Test indicated significance (p < 0.05) it was followed by post-hoc pairwise comparisons (between a given algorithm and Hadassah OSEM) according to Conover , with Bonferroni adjustment. Bonferroni corrected p values lower than 0.05 were considered statistically significant. For the quantitative analysis, algorithms with significant Bonferroni corrected p values for SNR, SBR and noise were considered to outperform Hadassah OSEM. For the visual analysis, algorithms leading to significant Bonferroni corrected p values for the mean of all the rated parameters were considered superior to Hadassah OSEM.