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This article reviews the current evolution and future directions in PET/CT technology focusing on three areas: time of flight, image reconstruction, and data-driven gating. Image reconstruction is considered with advances in point spread function modelling, Bayesian penalised likelihood reconstruction, and artificial intelligence approaches. Data-driven gating is examined with reference to respiratory motion, cardiac motion, and head motion. For each of these technological advancements, theory will be briefly discussed, benefits of their use in routine practice will be detailed and potential future developments will be discussed. Representative clinical cases will be presented, demonstrating the huge opportunities given to the PET community by hardware and software advances in PET technology when it comes to lesion detection, disease characterization, accurate quantitation and quicker scans. Through this review, hospitals are encouraged to embrace, evaluate and appropriately implement the wide range of new PET technologies that are available now or in the near future, for the improvement of patient care., Competing Interests: Conflict of Interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Inc. All rights reserved.)

When evaluating 18 F-FDG PET images with the Deauville score (DS), the quantification of tumor and reference organs limits the problem of optical misinterpretation. Compared with conventional reconstruction algorithms, point-spread function (PSF) modeling increases SUVs significantly in tumors but only moderately in the liver, which could affect the DS. We investigated whether the choice of the reconstruction algorithm affects the DS and whether discordance affects the capability of 18 F-FDG PET to stratify lymphoma patients. Methods: Overall, 126 patients with diffuse large B-cell lymphoma were included (56 female and 70 male; median age, 65 y; range, 20-88 y). PET data were reconstructed with the unfiltered PSF method. Additionally, a 6-mm filter was applied to PSF images to meet the requirements of the EANM Research Ltd. (EARL) harmonization program from the European Association of Nuclear Medicine (EANM) (PSF EARL ). One hundred interim PET (i-PET) and 95 end-of-treatment PET (EoT-PET) studies were analyzed. SUV max in the liver and aorta was determined using automatic volumes of interest and compared with SUV max in the residual mass with the highest 18 F-FDG uptake. Results: For i-PET, using PSF and PSF EARL , we classified patients as responders and nonresponders in 60 and 40 cases versus 63 and 37 cases, respectively. Five cases of major discordance (5.0%) occurred (i.e., changes from responder to nonresponder). For Eot-PET, patients were classified using PSF and PSF EARL as responders and nonresponders in 69 and 26 cases versus 72 and 23 cases, respectively. Three cases of major discordance (3.2%) occurred. Concordance (Cohen unweighted κ) between the PSF and the PSF EARL DS was 0.82 (95% confidence interval, 0.73-0.91) for i-PET and 0.89 (95% confidence interval, 0.81-0.96) for EoT-PET. The median follow-up periods were 28.4 and 27.4 mo for i-PET and EoT-PET, respectively. Kaplan-Meier analysis showed statistically significant differences in progression-free survival and overall survival among responders and nonresponders no matter which reconstruction was used for i-PET and EoT-PET. Conclusion: Neither DS nor risk stratification of diffuse large B-cell lymphoma patients is affected by the choice of PET reconstruction. Specifically, the use of PSF is not an issue in routine clinical processes or in multicenter trials. These findings have to be confirmed in escalation and deescalation procedures based on early i-PET., (© 2018 by the Society of Nuclear Medicine and Molecular Imaging.)

Quantitative positron emission tomography/computed tomography (PET/CT) can be used as diagnostic or prognostic tools (i.e. single measurement) or for therapy monitoring (i.e. longitudinal studies) in multicentre studies. Use of quantitative parameters, such as standardized uptake values (SUVs), metabolic active tumor volumes (MATVs) or total lesion glycolysis (TLG), in a multicenter setting requires that these parameters be comparable among patients and sites, regardless of the PET/CT system used. This review describes the motivations and the methodologies for quantitative PET/CT performance harmonization with emphasis on the EANM Research Ltd. (EARL) Fluorodeoxyglucose (FDG) PET/CT accreditation program, one of the international harmonization programs aiming at using FDG PET as a quantitative imaging biomarker. In addition, future accreditation initiatives will be discussed. The validation of the EARL accreditation program to harmonize SUVs and MATVs is described in a wide range of tumor types, with focus on therapy assessment using either the European Organization for Research and Treatment of Cancer (EORTC) criteria or PET Evaluation Response Criteria in Solid Tumors (PERCIST), as well as liver-based scales such as the Deauville score. Finally, also presented in this paper are the results from a survey across 51 EARL-accredited centers reporting how the program was implemented and its impact on daily routine and in clinical trials, harmonization of new metrics such as MATV and heterogeneity features.

Pre- and posttreatment PET comparative scans should ideally be obtained with identical acquisition and processing, but this is often impractical. The degree to which differing protocols affect PERCIST classification is unclear. This study evaluates the consistency of PERCIST classification across different reconstruction algorithms and whether a proprietary software tool can harmonize SUV estimation sufficiently to provide consistent response classification., Methods: Eighty-six patients with non-small cell lung cancer, colorectal liver metastases, or metastatic melanoma who were scanned for therapy monitoring purposes were prospectively recruited in this multicenter trial. Pre- and posttreatment PET scans were acquired in protocols compliant with the Society of Nuclear Medicine and Molecular Imaging and the European Association of Nuclear Medicine (EANM) acquisition guidelines and were reconstructed with a point spread function (PSF) or PSF + time-of-flight (TOF) for optimal tumor detection and also with standardized ordered-subset expectation maximization (OSEM) known to fulfill EANM harmonizing standards. After reconstruction, a proprietary software solution was applied to the PSF ± TOF data (PSF ± TOF.EQ) to harmonize SUVs with the OSEM values. The impact of differing reconstructions on PERCIST classification was evaluated., Results: For the OSEM PET1 /OSEM PET2 (OSEM reconstruction for pre- and posttherapeutic PET, respectively) scenario, which was taken as the reference standard, the change in SUL was -41% ± 25 and +56% ± 62 in the groups of tumors showing a decrease and an increase in 18 F-FDG uptake, respectively. The use of PSF reconstruction affected classification of tumor response. For example, taking the PSF ± TOF PET1 /OSEM PET2 scenario increased the apparent reduction in SUL in responding tumors (-48% ± 22) but reduced the apparent increase in SUL in progressing tumors (+37% ± 43), as compared with the OSEM PET1 /OSEM PET2 scenario. As a result, variation in reconstruction methodology (PSF ± TOF PET1 /OSEM PET2 or OSEM PET1 /PSF ± TOF PET2 ) led to 13 of 86 (15%) and 17 of 86 (20%) PERCIST classification discordances, respectively. Agreement was better for these scenarios with application of the propriety filter, with κ values of 1 and 0.95 compared with 0.79 and 0.72, respectively., Conclusion: Reconstruction algorithm-dependent variability in PERCIST classification is a significant issue but can be overcome by harmonizing SULs using a proprietary software tool., (© 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.)

Purpose: We compared conventional filtered back-projection (FBP), two-dimensional-ordered subsets expectation maximization (OSEM) and maximum a posteriori (MAP) NEMA NU 4-optimized reconstructions for therapy assessment., Procedures: Varying reconstruction settings were used to determine the parameters for optimal image quality with two NEMA NU 4 phantom acquisitions. Subsequently, data from two experiments in which nude rats bearing subcutaneous tumors had received a dual PI3K/mTOR inhibitor were reconstructed with the NEMA NU 4-optimized parameters. Mann-Whitney tests were used to compare mean standardized uptake value (SUV(mean)) variations among groups., Results: All NEMA NU 4-optimized reconstructions showed the same 2-deoxy-2-[(18)F]fluoro-D-glucose ([(18)F]FDG) kinetic patterns and detected a significant difference in SUV(mean) relative to day 0 between controls and treated groups for all time points with comparable p values., Conclusion: In the framework of therapy assessment in rats bearing subcutaneous tumors, all algorithms available on the Inveon system performed equally.

Purpose: We prospectively evaluated whether a strategy using point spread function (PSF) reconstruction for both diagnostic and quantitative analysis in non-small cell lung cancer (NSCLC) patients meets the European Association of Nuclear Medicine (EANM) guidelines for harmonization of quantitative values., Methods: The NEMA NU-2 phantom was used to determine the optimal filter to apply to PSF-reconstructed images in order to obtain recovery coefficients (RCs) fulfilling the EANM guidelines for tumour positron emission tomography (PET) imaging (PSF(EANM)). PET data of 52 consecutive NSCLC patients were reconstructed with unfiltered PSF reconstruction (PSF(allpass)), PSF(EANM) and with a conventional ordered subset expectation maximization (OSEM) algorithm known to meet EANM guidelines. To mimic a situation in which a patient would undergo pre- and post-therapy PET scans on different generation PET systems, standardized uptake values (SUVs) for OSEM reconstruction were compared to SUVs for PSF(EANM) and PSF(allpass) reconstruction., Results: Overall, in 195 lesions, Bland-Altman analysis demonstrated that the mean ratio between PSF(EANM) and OSEM data was 1.03 [95% confidence interval (CI) 0.94-1.12] and 1.02 (95% CI 0.90-1.14) for SUV(max) and SUV(mean), respectively. No difference was noticed when analysing lesions based on their size and location or on patient body habitus and image noise. Ten patients (84 lesions) underwent two PET scans for response monitoring. Using the European Organization for Research and Treatment of Cancer (EORTC) criteria, there was an almost perfect agreement between OSEM(PET1)/OSEM(PET2) (current standard) and OSEM(PET1)/PSF(EANM-PET2) or PSF(EANM-PET1)/OSEM(PET2) with kappa values of 0.95 (95% CI 0.91-1.00) and 0.99 (95% CI 0.96-1.00), respectively. The use of PSF(allpass) either for pre- or post-treatment (i.e. OSEM(PET1)/PSF(allpass-PET2) or PSF(allpass-PET1)/OSEM(PET2)) showed considerably less agreement with kappa values of 0.75 (95% CI 0.67-0.83) and 0.86 (95% CI 0.78-0.94), respectively., Conclusion: Protocol-optimized images and compliance with EANM guidelines allowed for a reliable pre- and post-therapy evaluation when using different generation PET systems. These data obtained in NSCLC patients could be extrapolated to other solid tumours.

Aim: The aim of the present study was to evaluate the impact of point spread function (PSF) reconstruction on quantitative values and diagnostic accuracy of FDG PET/CT for nodal staging in non-small cell lung cancer., Patients and Methods: Fifty-eight consecutive PET/CT examinations were reconstructed with both ordered subset expectation maximization (OSEM) and PSF algorithms. Two readers independently performed a randomized blinded review of PET/CT examinations and gave a nodal status (N0, N1, N2, or N3) to each PET data set. When discordant, a consensus was reached with a third reader. Sensitivity, specificity, positive and negative predictive values (NPV), and positive and negative likelihood ratios (LRs) were assessed and compared using a McNemar test. All PET data sets were then independently analyzed to extract quantitative PET values in 208 nodes and compare them using Bland-Altman analysis., Results: Bland-Altman analysis showed that, on average, PSF reconstruction increased SUVmax, SUVmean, and node/background ratios by 48%, 28%, and 27%, respectively. This increase was more marked for nodes less than 1 cm than for nodes 1 cm or greater (P < 0.0001 for SUVmax, SUVmean, and node/background ratios). Point spread function PET had higher sensitivity (97%) and NPV (92%) than OSEM PET (78% and 57%, respectively; P = 0.01 and P = 0.04, respectively). Negative LR was 0.04 for PSF PET and 0.31 for OSEM PET., Conclusions: By improving activity recovery, especially for nonenlarged nodes, PSF significantly improves the sensitivity, NPV, and negative LR of FDG-PET for nodal staging in non-small cell lung cancer. These data suggest that preoperative invasive nodal staging may be omitted in the case of a negative PSF FDG-PET/CT.