Objective: To consolidate current understanding of detection sensitivity of brain 18 F-FDG PET scans in the diagnosis of autoimmune encephalitis and to de ne speci c metabolic imaging patterns for the most frequently occurring autoantibodies. Methods: A systematic and exhaustive search of data available in the literature was performed by querying the PubMed/MEDLINE and Cochrane databases for the search terms: "FDG PET" and ""encephalitis" or "brain in ammation"". Studies had to satisfy the following criteria: i. include at least one patient suspected or diagnosed with autoimmune encephalitis according to the current recommendations, ii. be an original case-report iii. speci cally present 18 F-FDG PET and/or morphologic imaging ndings. The diagnostic 18 F-FDG PET detection sensitivity in autoimmune encephalitis was determined for all cases reported in the literature and a meta-analysis, according to the PRISMA method, was performed on a subset of these, which included PET scans for at least 10 patients, and whose quality was assessed with the QUADAS-2 tool. Results: The search strategy identi ed 1113 articles. The detection sensitivity of 18 F-FDG PET was 90%, based on 176 publications and 720 patients and 80% [75%-84%] by meta-analysis based on 21 publications and 444 patients. We also report speci c brain 18 F-FDG PET imaging patterns for the main encephalitis autoantibody subtypes. Conclusion and Relevance: Brain 18 F-FDG PET has a high detection sensitivity and should be included in future diagnostic autoimmune encephalitis recommendations. Speci c metabolic 18 F-FDG PET patterns corresponding to the main autoimmune encephalitis autoantibody subtypes further enhance the value of this diagnostic.

Purpose:The assessment of gliomas by 18 F-FDOPA PET imaging in adjunct to MRI showed high performance by combining static and dynamic features to non-invasively predict the isocitrate dehydrogenase (IDH) mutations and the 1p/19q co-deletion, which the World Health Organization classified as significant parameters in 2016. The current study evaluates whether other 18 F-FDOPA PET radiomics features further improve performance and the contributions of each of these features to performance.Methods: Our study included seventy-two, retrospectively selected, newly diagnosed, glioma patients with 18 F-FDOPA PET dynamic acquisitions. A set of 114 features, including conventional static features and dynamic features as well as other radiomics features were extracted and machine-learning models trained to predict IDH mutations and the 1p/19q co-deletion. Models were based on a machine-learning algorithm built from stable, relevant, and uncorrelated features selected by hierarchical clustering followed by a bootstrapped feature selection process. Models were assessed by comparing area under the curve (AUC) using a nested cross-validation approach.Feature importance was assessed using SHapley Additive exPlanations (SHAP) values. Results:The best models were able to predict IDH mutations (logistic regression with L2 regularization) and the 1p/19q co-deletion (support vector machine with radial basis function kernel) with an AUC of 0.831[0.790;0.873] and 0.724[0.669;0.782] respectively. For the prediction of IDH mutations, dynamic features were the most important features in the model (TTP: 35.5%).In contrast, other radiomics features were the most useful for predicting the 1p/19q co-deletion (up to 14.5% of importance for the small zone low grey level emphasis).4 Conclusions: 18 F-FDOPA PET is an effective tool for the non-invasive prediction of glioma molecular parameters using a full set of amino-acid PET radiomics features. The contribution of each feature set shows the importance of systematically integrating dynamic acquisition for the prediction of the IDH mutations as well as developing the use of radiomics features in routine practice for the prediction the 1p/19q co-deletion.

Impulse control disorders (ICDs) have received increased attention in Parkinson's disease (PD) because of potentially dramatic consequences. Their physiopathology, however, remains incompletely understood. An overstimulation of the mesocorticolimbic system has been reported, while a larger network has recently been suggested. The aim of this study is to specifically describe the metabolic PET substrate and related connectivity changes in PD patients with ICDs. Eighteen PD patients with ICDs and 18 PD patients without ICDs were evaluated using cerebral 18F-fluorodeoxyglucose positron emission tomography. SPM-T maps comparisons were performed between groups and metabolic connectivity was evaluated by interregional correlation analysis (IRCA; p < .005, uncorrected; k > 130) and by graph theory (p < .05). PD patients with ICDs had relative increased metabolism in the right middle and inferior temporal gyri compared to those without ICDs. The connectivity of this area was increased mostly with the mesocorticolimbic system, positively with the orbitofrontal region, and negatively with both the right parahippocampus and the left caudate (IRCA). Moreover, the betweenness centrality of this area with the mesocorticolimbic system was lost in patients with ICDs (graph analysis). ICDs are associated in PD with the dysfunction of a network exceeding the mesocorticolimbic system, and especially the caudate, the parahippocampus, and the orbitofrontal cortex, remotely including the right middle and inferior temporal gyri. This latest area loses its central place with the mesocorticolimbic system through a connectivity dysregulation.

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Objective The aim of this study was to compare brain perfusion SPECT obtained from a 360° CZT and a conventional Anger camera. Methods The 360° CZT camera utilizing a brain configuration, with 12 detectors surrounding the head, was compared to a 2-head Anger camera for count sensitivity and image quality on 30-min SPECT recordings from a brain phantom and from 99mTc-HMPAO brain perfusion in 2 groups of 21 patients investigated with the CZT and Anger cameras, respectively. Image reconstruction was adjusted according to image contrast for each camera. Results The CZT camera provided more than 2-fold increase in count sensitivity, as compared with the Anger camera, as well as (1) lower sharpness indexes, giving evidence of higher spatial resolution, for both peripheral/central brain structures, with respective median values of 5.2%/3.7% versus 2.4%/1.9% for CZT and Anger camera respectively in patients (p < 0.01), and 8.0%/6.9% versus 6.2%/3.7% on phantom; and (2) higher gray/white matter contrast on peripheral/central structures, with respective ratio median values of 1.56/1.35 versus 1.11/1.20 for CZT and Anger camera respectively in patients (p < 0.05), and 2.57/2.17 versus 1.40/1.12 on phantom; and (3) no change in noise level. Image quality, scored visually by experienced physicians, was also significantly higher on CZT than on the Anger camera (+ 80%, p < 0.01), and all these results were unchanged on the CZT images obtained with only a 15 min recording time. Conclusion The 360° CZT camera provides brain perfusion images of much higher quality than a conventional Anger camera, even with high-speed recordings, thus demonstrating the potential for repositioning brain perfusion SPECT to the forefront of brain imaging.