Background: Two novel methods of image reconstruction, xSPECT Quant (xQ) and xSPECT Bone (xB), that use an ordered subset conjugate gradient minimizer (OSCGM) for SPECT/CT reconstruction have been proposed. The present study compares the performance characteristics of xQ, xB, and conventional Flash3D (F3D) reconstruction using images derived from phantoms and patients. Methods: A custom-designed body phantom for bone SPECT was scanned using a Symbia Intevo (Siemens Healthineers), and reconstructed xSPECT images were evaluated. The phantom experiments proceeded twice with different activity concentrations and sphere sizes. A phantom with 28-mm spheres containing a ^99mTc-background and tumor-to-normal bone ratios (TBR) of 1, 2, 4, and 10 were generated, and convergence property against various TBR was evaluated across 96 iterations. A phantom with four spheres (13-, 17-, 22-, and 28-mm diameters), containing a ^99mTc-background at TBR4, was also generated. The full width at half maximum of an imaged spinous process (10 mm), coefficients of variance (CV), contrast-to-noise ratio (CNR), and recovery coefficients (RC) were evaluated after reconstructing images of a spine using Flash 3D (F3D), xQ, and xB. We retrospectively analyzed images from 20 patients with suspected bone metastases (male, n = 13) which were acquired using [^99mTc]Tc-(H)MDP SPECT/CT, then CV and standardized uptake values (SUV) at the 4^th vertebral body (L4) were compared after xQ and xB reconstruction in a clinical setup. Results: Mean activity concentrations with various TBR converged according to increasing numbers of iterations. The spatial resolution of xB was considerably superior to xQ and F3D, and it approached almost the actual size regardless of the iteration numbers during reconstruction. The CV and RC were better for xQ and xB than for F3D. The CNR peaked at 24 iterations for xQ and 48 iterations for F3D and xB, respectively. The RC between xQ and xB significantly differed at lower numbers of iterations but were almost equivalent at higher numbers of iterations. The reconstructed xQ and xB images of the clinical patients showed a significant difference in the SUV_max and SUV_peak. Conclusions: The reconstructed xQ and xB images were more accurate than those reconstructed conventionally using F3D. The xB for bone SPECT imaging offered essentially unchanged spatial resolution even when the numbers of iterations did not converge. The xB reconstruction further enhanced SPECT image quality using CT data. Our findings provide important information for understanding the performance characteristics of the novel xQ and xB algorithms.

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. Visual Abstract