Background: PET imaging after yttrium-90 (Y-90) radioembolization is challenging because of the low positron fraction of Y-90 (32 × 10⁻⁶). The resulting low number of events can be compensated by the high sensitivity of long axial field-of-view (LAFOV) PET/CT scanners. Nevertheless, the reduced event statistics require optimization of the imaging protocol to achieve high image quality (IQ) and quantification accuracy sufficient for post-treatment dosimetry. Methods: Two phantoms (NEMA IEC and AbdoMan phantoms, mimicking human liver) filled with Y-90 and a 4:1 sphere (tumor)-to-background ratio were scanned for 24 h with the Biograph Vision Quadra (Siemens Healthineers). Eight patients were scanned after Y-90 radioembolization (1.3–4.7 GBq) using the optimized protocol (obtained by phantom studies). The IQ, contrast recovery coefficients (CRCs) and noise were evaluated for their limited and full acceptance angles, different rebinned scan durations, numbers of iterations and post-reconstruction filters. The s-value-based absorbed doses were calculated to assess their suitability for dosimetry. Results: The phantom studies demonstrate that two iterations, five subsets and a 4 mm Gaussian filter provide a reasonable compromise between a high CRC and low noise. For a 20 min scan duration, an adequate CRC of 56% (vs. 24 h: 62%, 20 mm sphere) was obtained, and the noise was reduced by a factor of 1.4, from 40% to 29%, using the full acceptance angle. The patient scan results were consistent with those from the phantom studies, and the impacts on the absorbed doses were negligible for all of the studied parameter sets, as the maximum percentage difference was −3.89%. Conclusions: With 2i5s, a 4 mm filter and a scan duration of 20 min, IQ and quantification accuracy that are suitable for post-treatment dosimetry of Y-90 radioembolization can be achieved.

Background: Static [¹⁸F]FDG-PET/CT is the imaging method of choice for the evaluation of indeterminate lung lesions and NSCLC staging; however, histological confirmation of PET-positive lesions is needed in most cases due to its limited specificity. Therefore, we aimed to evaluate the diagnostic performance of additional dynamic whole-body PET. Methods: A total of 34 consecutive patients with indeterminate pulmonary lesions were enrolled in this prospective trial. All patients underwent static (60 min p.i.) and dynamic (0–60 min p.i.) whole-body [¹⁸F]FDG-PET/CT (300 MBq) using the multi-bed-multi-timepoint technique (Siemens mCT FlowMotion). Histology and follow-up served as ground truth. Kinetic modeling factors were calculated using a two-compartment linear Patlak model (FDG influx rate constant = Ki, metabolic rate = MR-FDG, distribution volume = DV-FDG) and compared to SUV using ROC analysis. Results: MR-FDG_mean provided the best discriminatory power between benign and malignant lung lesions with an AUC of 0.887. The AUC of DV-FDG_mean (0.818) and SUV_mean (0.827) was non-significantly lower. For LNM, the AUCs for MR-FDG_mean (0.987) and SUV_mean (0.993) were comparable. Moreover, the DV-FDG_mean in liver metastases was three times higher than in bone or lung metastases. Conclusions: Metabolic rate quantification was shown to be a reliable method to detect malignant lung tumors, LNM, and distant metastases at least as accurately as the established SUV or dual-time-point PET scans.