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Metaiodobenzylguanidine (MIBG) imaging has been the standard for neuroblastoma staging for many decades. Novel agents such as 18F-DOPA and 68Ga-DOTATATE are being used nowadays in academic centers. During the coronavirus disease 2019 (COVID-19) pandemic, procurement of 123I-MIBG has proved particularly challenging, necessitating the use of 68Ga-DOTATATE PET. 68Ga-DOTATATE is Food and Drug Administration-approved for imaging of somatostatin receptor-positive gastroenteropancreatic neuroendocrine tumors. Methods:68Ga-DOTATATE PET/CT imaging was performed for staging of 3 pediatric patients with neuroblastoma at our institution. A review of the literature was also completed. Results:68Ga-DOTATATE PET/CT scans were successfully performed on all patients. All patients showed 68Ga-DOTATATE-avid disease. PET scans showed an excellent spatial resolution and demonstrated high accuracy in concordance with current European Association of Nuclear Medicine guidelines. Conclusion: We have presented 68Ga-DOTATATE PET/CT imaging for staging of neuroblastoma and believe it can reliably be used as an alternative to 123I-MIBG. It has technical, clinical, and practical advantages making it an attractive option. Further multicenter studies are required before it can be recommended for standard clinical use. [ABSTRACT FROM AUTHOR]

Purpose: The conversion of synaptic glutamate to glutamine in astrocytes by glutamine synthetase (GS) is critical to maintaining healthy brain activity and may be disrupted in several brain disorders. As the GS catalysed conversion of glutamate to glutamine requires ammonia, we evaluated whether [13N]ammonia positron emission tomography (PET) could reliability quantify GS activity in humans. Methods: In this test–retest study, eight healthy volunteers each received two dynamic [13N]ammonia PET scans on the morning and afternoon of the same day. Each [13N]ammonia scan was preceded by a [15O]water PET scan to account for effects of cerebral blood flow (CBF). Results: Concentrations of radioactive metabolites in arterial blood were available for both sessions in five of the eight subjects. Our results demonstrated that kinetic modelling was unable to reliably distinguish estimates of the kinetic rate constant k3 (related to GS activity) from K1 (related to [13N]ammonia brain uptake), and indicated a non-negligible back-flux of [13N] to blood (k2). Model selection favoured a reversible one-tissue compartmental model, and [13N]ammonia K1 correlated reliably (r2 = 0.72–0.92) with [15O]water CBF. Conclusion: The [13N]ammonia PET method was unable to reliably estimate GS activity in the human brain but may provide an alternative index of CBF. [ABSTRACT FROM AUTHOR]

Background: Positron emission tomography (PET) is the non-invasive reference standard for myocardial blood flow (MBF) quantification. Hybrid PET-MR allows simultaneous PET and cardiac magnetic resonance (CMR) acquisition under identical experimental and physiological conditions. This study aimed to determine feasibility of simultaneous 13N-Ammonia PET and dynamic contrast-enhanced CMR MBF quantification in phantoms and healthy volunteers. Methods: Images were acquired using a 3T hybrid PET-MR scanner. Phantom study: MBF was simulated at different physiological perfusion rates and a protocol for simultaneous PET-MR perfusion imaging was developed. Volunteer study: five healthy volunteers underwent adenosine stress. 13N-Ammonia and gadolinium were administered simultaneously. PET list mode data was reconstructed using ordered subset expectation maximisation. CMR MBF was quantified using Fermi function-constrained deconvolution of arterial input function and myocardial signal. PET MBF was obtained using a one-tissue compartment model and image-derived input function. Results: Phantom study: PET and CMR MBF measurements demonstrated high repeatability with intraclass coefficients 0.98 and 0.99, respectively. There was high correlation between PET and CMR MBF (r = 0.98, p < 0.001) and good agreement (bias − 0.85 mL/g/min; 95% limits of agreement 0.29 to − 1.98). Volunteer study: Mean global stress MBF for CMR and PET were 2.58 ± 0.11 and 2.60 ± 0.47 mL/g/min respectively. On a per territory basis, there was moderate correlation (r = 0.63, p = 0.03) and agreement (bias − 0.34 mL/g/min; 95% limits of agreement 0.49 to − 1.18). Conclusion: Simultaneous MBF quantification using hybrid PET-MR imaging is feasible with high test repeatability and good to moderate agreement between PET and CMR. Future studies in coronary artery disease patients may allow cross-validation of techniques. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: Misregistration artifacts between the PET and attenuation correction CT (CTAC) exams can degrade image quality and cause diagnostic errors. Deep learning (DL)-warped elastic registration methods have been proposed to improve misregistration errors., Materials and Methods: 30 patients undergoing routine oncologic examination (20 18 F-FDG PET/CT and 10 64 Cu-DOTATATE PET/CT) were retrospectively identified and compared using unmodified CTAC, and a DL-augmented spatial transformation CT attenuation map. Primary endpoints included differences in subjective image quality and standardized uptake values (SUV). Exams were randomized to reduce reader bias, and three radiologists rated image quality across six anatomic sites using a modified Likert scale. Measures of local bias and lesion SUV were also quantitatively evaluated., Results: The DL attenuation correction methods were associated with higher image quality and reduced misregistration artifacts (Mean 18 F-FDG quality rating=3.5-3.8 for DL vs 3.2-3.5 for standard reconstruction (STD); Mean 64 Cu-DOTATATE quality rating= 3.2-3.4 for DL vs 2.1-3.3; P < 0.05 for STD, for all except 64 Cu-DOTATATE inferior spleen). Percent change in superior liver SUV mean for 18 F-FDG and 64 Cu-DOTATATE were 5.3 ± 4.9 and 8.2 ± 4.1%, respectively. Measures of signal-to-noise ratio were significantly improved for the DL over STD (Hepatopulmonary index (HPI) [ 18 F-FDG] = 4.5 ± 1.2 vs 4.0 ± 1.1, P < 0.001; HPI [ 64 Cu-DOTATATE] = 16.4 ± 16.9 vs 12.5 ± 5.5, P = 0.039)., Conclusion: Deep learning elastic registration for CT attenuation correction maps on routine oncology PET/CT decreases misregistration artifacts, with a greater impact on PET scans with longer acquisition times., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Joshua Schaefferkoetter reports a relationship with Siemens Medical Solutions USA Inc that includes: employment. James Hamill reports a relationship with Siemens Medical Solutions USA Inc that includes: employment. Jim O Doherty reports a relationship with Siemens Medical Solutions USA Inc that includes: employment. If there are other authors, they 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 © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Rationale and Objectives: Coronary CT angiography (CCTA) is mandatory before transcatheter aortic valve replacement (TAVR). Our objective was to evaluate the efficacy of artificial intelligence (AI)-powered software in automatically analyzing cardiac parameters from pre-procedural CCTA to predict major adverse cardiovascular events (MACE) in TAVR patients., Materials and Methods: Patients undergoing pre-TAVR CCTA were retrospectively included. AI software automatically extracted 34 morphologic and volumetric cardiac parameters characterizing the ventricles, atria, myocardium, and epicardial adipose tissue. Clinical information and outcomes were recorded from institutional database. Cox regression analysis identified predictors of MACE, including non-fatal myocardial infarction, heart failure hospitalization, unstable angina, and cardiac death. Model performance was evaluated with Harrell's C-index, and nested models were compared using the likelihood ratio test. Manual analysis of 170 patients assessed agreement with automated measurements., Results: Among the 648 enrolled patients (77 ± 9.3 years, 58.9% men), 116 (17.9%) experienced MACE within a median follow-up of 24 months (interquartile range 10-40). After adjusting for clinical parameters, only left ventricle long axis shortening (LV-LAS) was an independent predictor of MACE (hazard ratio [HR], 1.05 [95% confidence interval, 1.05-1.11]; p = 0.04), with significantly improved C-index (0.620 vs. 0.633; p < 0.001). When adjusted for the Society of Thoracic Surgeons Predicted Risk of Mortality score, LV-LAS was also predictive of MACE (HR, 1.08 [95%CI, 1.03-1.13]; p = 0.002), while improving model performance (C-index: 0.557 vs. 0.598; p < 0.001). All parameters showed good or excellent agreement with manual measurements., Conclusion: Automated AI-based comprehensive cardiac assessment enables pre-TAVR MACE prediction, with LV-LAS outperforming all other parameters., Competing Interests: Declaration of Competing Interest The authors of this manuscript declare relationships with the following companies: A.V-S.: receives institutional research support and/or personal subscriptions from Siemens and Elucid Bioimaging; U.J.S.: receives institutional research support and/or personal fees by Bayer, Bracco, Elucid BioImaging, Guerbet, HeartFlow, Inc., Keya Medical, and Siemens; A.J.: is an employee of Siemens Medical Solutions USA Inc; P.S.: is an employee of Siemens Medical Solutions USA Inc; S.R.: is an employee of Siemens Medical Solutions USA Inc; J.O.: is an employee of Siemens Medical Solutions USA Inc; T.E.: receives travel support and speaker fee from Siemens Medical Solutions USA Inc, institutional research support by Siemens Healthineers and is a consultant for Circle Cardiovascular Imaging; For the remaining authors, none were declared., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)