Introdution: [68Ga]Ga-prostate specific membrane antigen (PSMA)-11 showed a clear gain in sensitivity for lesion detection in the biological recurrence of prostate cancer as compared to the standard [18F]fluorocholine radiopharmaceutical. To meet the strong demand for [68Ga]Ga-PSMA-11, we aimed to optimize an automated radiolabeling process by evaluating the influence of different key parameters on radiochemical purity and radiochemical yield. Methods: The radiosynthesis of [68Ga]Ga PSMA-11 was performed using a Trasis MiniAio synthesizer and a 68Ge/68Ga GalliaPharm generator supplied by Eckert & Ziegler, Berlin, Germany. Optimized labeling parameters were evaluated by variation of sodium acetate concentrations and temperature of radiolabeling as well as the purification process. Results: For each condition tested, radiochemical purity was higher than 99% in the final vial without batch failure, indicating a robust and fast radiosynthesis process. Radiosynthesis without the solid phase extraction purification process at room temperature in less than 5 min resulted in a radiolabeling efficiency of over 99% and remained stable at least 4 h without manual processing to limit operator radiation exposure. Conclusion: The procedure was completely automated and provided a high radiochemical yield. It can be performed several times a day, facilitating the clinical demand of this radiopharmaceutical.

Background PET imaging of 90Y-microsphere distribution following radioembolisation is challenging due to the count-starved statistics from the low branching ratio of e+/e− pair production during 90Y decay. PET systems using silicon photo-multipliers have shown better 90Y image quality compared to conventional photo-multiplier tubes. The main goal of the present study was to evaluate reconstruction parameters for different phantom configurations and varying listmode acquisition lengths to improve quantitative accuracy in 90Y dosimetry, using digital photon counting PET/CT. Methods Quantitative PET and dosimetry accuracy were evaluated using two uniform cylindrical phantoms specific for PET calibration validation. A third body phantom with a 9:1 hot sphere-to-background ratio was scanned at different activity concentrations of 90Y. Reconstructions were performed using OSEM algorithm with varying parameters. Time-of-flight and point-spread function modellings were included in all reconstructions. Absorbed dose calculations were carried out using voxel S-values convolution and were compared to reference Monte Carlo simulations. Dose-volume histograms and root-mean-square deviations were used to evaluate reconstruction parameter sets. Using listmode data, phantom and patient datasets were rebinned into various lengths of time to assess the influence of count statistics on the calculation of absorbed dose. Comparisons between the local energy deposition method and the absorbed dose calculations were performed. Results Using a 2-mm full width at half maximum post-reconstruction Gaussian filter, the dosimetric accuracy was found to be similar to that found with no filter applied but also reduced noise. Larger filter sizes should not be used. An acquisition length of more than 10 min/bed reduces image noise but has no significant impact in the quantification of phantom or patient data for the digital photon counting PET. 3 iterations with 10 subsets were found suitable for large spheres whereas 1 iteration with 30 subsets could improve dosimetry for smaller spheres. Conclusion The best choice of the combination of iterations and subsets depends on the size of the spheres. However, one should be careful on this choice, depending on the imaging conditions and setup. This study can be useful in this choice for future studies for more accurate 90Y post-dosimetry using a digital photon counting PET/CT.

Purpose of the Report: Using morphological and functional imaging to discriminate recurrence from postradiation-related modifications in patients with glioblastomas remains challenging. This pilot study aimed to assess the feasibility of using 68 Ga-prostate-specific membrane antigen (PSMA) 11 PET/CT compared with 18 F-FDOPA PET/CT to detect early recurrence. Methods: Nine patients followed up for glioblastomas who received MRI during 12 months of follow-up were referred for both 68 Ga-PSMA-11 and 18

Background: PET imaging of 90Y-microspheres distribution following radioembolisation is a challenging task due to the count-starved statistics from the low branching ratio producing e+/e- pairs during 90Y decay. The recent PET systems using silicon photo-multipliers technology has shown better 90Y image quality compared to photo-multiplier tubes. The aim of the present study was to quantitatively evaluate the impact of 90Y imaging conditions and reconstruction parameters on the dosimetry calculations using a digital photon counting PET.Methods: Quantitative PET and dosimetry accuracy were evaluated using two uniform cylindrical phantoms specific for PET calibration validation. A body phantom with an 9:1 hot sphere-to-background ratio was scanned at different activity concentrations of 90Y. Reconstructions were performed using OSEM algorithm with varying parameters. Time-of-flight and point-spread function modellings were included in all reconstructions. Absorbed dose calculations were carried out using Voxel S-Values convolution and were compared to reference Monte Carlo simulations. Dose-volume histograms and root-mean-square deviations were used to evaluate reconstruction parameter sets. Thanks to listmode data, datasets for phantoms and patients were rebinned into varying lengths of time to assess the influence of acquisition duration on the calculation of absorbed dose. Results: A 2 mm full width at half maximum post-reconstruction Gaussian filter size can be used for image reconstruction, keeping the same accuracy as when no filter is applied for dosimetry purposes and reducing noise. Larger filter sizes should not be used. An acquisition duration of more than 10 min/bed reduces image noise but has no significant impact in the quantification of phantom and patient data for the digital photon counting PET. 3 iterations with 10 subsets was found suitable for large spheres whereas 1 iteration with 30 subsets could improve dosimetry for smaller spheres. Conclusion: The choice of iterations and subsets combination depends on the size of the spheres. However, one should be careful on this choice, depending on the imaging conditions and setup. This study can be useful in this choice for future studies for more accurate 90Y post-dosimetry using a digital photon counting PET.