Purpose: Q.Clear is a block sequential regularized expectation maximization (BSREM) penalized-likelihood reconstruction algorithm for PET. It tries to improve image quality by controlling noise amplification during image reconstruction. In this study, the noise properties of this BSREM were compared to the ordered-subset expectation maximization (OSEM) algorithm for both phantom and patient data acquired on a state-of-the-art PET/CT. Methods: The NEMA IQ phantom and a whole-body patient study were acquired on a GE DMI 3-rings system in list mode and different datasets with varying noise levels were generated. Phantom data was evaluated using four different contrast ratios. These were reconstructed using BSREM with different β-factors of 300–3000 and with a clinical setting used for OSEM including point spread function (PSF) and time-of-flight (TOF) information. Contrast recovery (CR), background noise levels (coefficient of variation, COV), and contrast-to-noise ratio (CNR) were used to determine the performance in the phantom data. Findings based on the phantom data were compared with clinical data. For the patient study, the SUV ratio, metabolic active tumor volumes (MATVs), and the signal-to-noise ratio (SNR) were evaluated using the liver as the background region. Results: Based on the phantom data for the same count statistics, BSREM resulted in higher CR and CNR and lower COV than OSEM. The CR of OSEM matches to the CR of BSREM with β = 750 at high count statistics for 8:1. A similar trend was observed for the ratios 6:1 and 4:1. A dependence on sphere size, counting statistics, and contrast ratio was confirmed by the CNR of the ratio 2:1. BSREM with β = 750 for 2.5 and 1.0 min acquisition has comparable COV to the 10 and 5.0 min acquisitions using OSEM. This resulted in a noise reduction by a factor of 2–4 when using BSREM instead of OSEM. For the patient data, a similar trend was observed, and SNR was reduced by at least a factor of 2 while preserving contrast. Conclusion: The BSREM reconstruction algorithm allowed a noise reduction without a loss of contrast by a factor of 2–4 compared to OSEM reconstructions for all data evaluated. This reduction can be used to lower the injected dose or shorten the acquisition time.

Patients diagnosed with radioiodine refractory (RAI-R) thyroid carcinoma (TC) have a significantly worse prognosis than patients with radiosensitive TC. These refractory malignancies are often dedifferentiated, hindering the effectiveness of iodine-based imaging. Additionally, the role of metabolic imaging using [18F]FDG PET/CT is also limited in these cases, making adequate staging of RAI-R TC challenging. Recent case series have shown promising results regarding the role of the prostate-specific membrane antigen (PSMA) in TC. In this study we explored the value of [18F]AlF-PSMA-11 PET/CT in RAI-R TC. In this phase II study, lesions detected on [18F]AlF-PSMA-11 PET were compared to findings from [18F]FDG PET/CT. Additionally, the serologic soluble prostate-specific membrane antigen (sPSMA) was measured using ELISA. PSMA-expression on tumor tissue in any available resection specimens was analysed with an immunostainer. Eight patients were included, with a total of 39 identified lesions based on PET imaging. [18F]AlF-PSMA-11 PET identified 30 of 39 lesions, and [18F]FDG PET identified 33 lesions, leading to a detection rate of 76.9% and 84.6%, respectively. Interestingly, while nine lesions were solely visualized on [18F]FDG, six were uniquely seen on [18F]AlF-PSMA-11 PET. While sPSMA was immeasurable in all female patients, no correlation was found between sPSMA in male patients and disease-related factors. In five out of eight patients immunohistology showed PSMA expression on the primary tumor. Although not all lesions could be visualized, [18F]PSMA-11 PET identified multiple lesions imperceptible on [18F]FDG PET. These results display the potential additional diagnostic role of PSMA-targeted imaging in patients with RAI-R TC. Trial registration number No. EudraCT 2021-000456-19.