Purpose The aim of this study was to describe brain metabolic changing patterns demonstrated by serial brain FDG PET/CT scans and their relationship with the clinical course in patients with anti-N-methyl-d-aspartate receptor encephalitis (ANMDARE). Patients and Methods Eighteen serial PET scans of 8 patients with ANMDARE were reviewed. All the 18 PET scans were divided into 4 groups according to studies timing in different clinical course: group A, the acute and subacute phase; group B, early recovery phase; group C, recovery phase; and group D, relapsing phase. Antibody levels of ANMDARE of all these patients were tested at the same time. The PET images of each group were analyzed visually and also compared with 10 age- and sex-matched normal controls using voxel-wise statistical parametric mapping analysis (SPM5). Results Variable brain metabolic patterns and its association with the clinical course and the levels of NMDA antibody were demonstrated by FDG PET images. First, severe hypometabolism in bilateral occipital lobes and relatively mild hypermetabolism in the partial frontal and basal ganglia in acute and subacute phase, the level of antibody was high. Second, in early recovery phase when the symptoms was partially improved, extensive cortical hypometabolism was observed, and the level of antibody was low. Third, the patients in the recovery phase have no obvious neurological and psychiatric symptoms; PET images were nearly normal, and the antibodies tests were all negative, correspondingly. Fourth, 3 scans of relapsing phase presented heterogeneous brain metabolic abnormalities. Conclusions There existed a specific serial brain metabolic changing pattern that correlated with the clinical course and antibody level in ANMDARE.

Normal aging is accompanied by structural degeneration and glucose hypometabolism in the human brain. However, the relationship between structural network disconnections and hypometabolism in normal aging remains largely unknown. In the present study, by combining MRI and PET techniques, we investigated the metabolic mechanism of the structural brain connectome and its relationship with normal aging in a cross-sectional, community-based cohort of 42 cognitively normal elderly individuals aged 57-84 years. The structural connectome was constructed based on diffusion MRI tractography, and the network efficiency metrics were quantified using graph theory analyses. FDG-PET scanning was performed to evaluate the glucose metabolic level in the cortical regions of the individuals. The results of this study demonstrated that both network efficiency and cortical metabolism decrease with age (both p < 0.05). In the subregions of the bilateral thalamus, significant correlations between nodal efficiency and cortical metabolism could be observed across subjects. Individual-level analyses indicated that brain regions with higher nodal efficiency tend to exhibit higher metabolic levels, implying a tight coupling between nodal efficiency and glucose metabolism (r = 0.56, p = 1.15 × 10-21). Moreover, efficiency-metabolism coupling coefficient significantly increased with age (r = 0.44, p = 0.0046). Finally, the main findings were also reproducible in the ADNI dataset. Together, our results demonstrate a close coupling between structural brain connectivity and cortical metabolism in normal elderly individuals and provide new insight that improve the present understanding of the metabolic mechanisms of structural brain disconnections in normal aging.

Objective: Our study aimed to investigate the utility of ¹⁸F-FDG PET imaging in diagnosing and monitoring patients with anti–leucine-rich glioma-inactivated 1 antibody autoimmune encephalitis (anti-LGI1 AE). We also sought to understand the mechanisms of faciobrachial dystonic seizures (FBDSs). Patients and Methods: We analyzed ¹⁸F-FDG PET scans from 50 patients with anti-LGI1 AE, using visual and semiquantitative methods, and compared these with 24 healthy controls. All patients tested positive for anti-LGI1 antibodies in serum or cerebrospinal fluid before PET imaging. The patients were divided into FBDS and non-FBDS groups to compare metabolic differences using voxel-based semiquantitative analysis. Finally, we separately analyzed PET images of patients with symptom recurrence. Results: The sensitivity of ¹⁸F-FDG PET was superior to MRI (97.9% vs 63.8%, respectively; P < 0.001). Semiquantitative analysis revealed hypermetabolism in the basal ganglia, medial temporal lobe, and brainstem, and hypometabolism in most neocortical regions compared with healthy controls. The FBDS group exhibited hypometabolism in the frontal and temporal lobes compared with the non-FBDS group. Among 7 recurrent patients, 3 were confirmed as recurrence and 3 as sequelae by PET. One patient relapsed shortly after discontinuing corticosteroids when PET indicated active lesions. Conclusions: ¹⁸F-FDG PET scans were more sensitive than MRI in detecting anti-LGI1 AE, which displayed a pattern of hypermetabolism in the basal ganglia and medial temporal lobe, as well as neocortex hypometabolism. Hypometabolism in the frontal and temporal lobes was associated with FBDS. Furthermore, ¹⁸F-FDG PET scans can differentiate recurrence from sequelae and guide the timing of immunotherapy cessation.

Background: Understanding the characteristics of intrinsic connectivity networks (ICNs) in terms of both glucose metabolism and functional connectivity (FC) is important for revealing cognitive aging and neurodegeneration, but the relationships between these two aspects during aging has not been well established in older adults. Objective: This study is to assess the relationship between age-related glucose metabolism and FC in key ICNs, and their direct or indirect effects on cognitive deficits in older adults. Methods: We estimated the individual-level standard uptake value ratio (SUVr) and FC of eleven ICNs in 59 cognitively unimpaired older adults, then analyzed the associations of SUVr and FC of each ICN and their relationships with cognitive performance. Results: The results showed both the SUVr and FC in the posterior default mode network (pDMN) had a significant decline with age, and the association between them was also significant. Moreover, both decline of metabolism and FC in the pDMN were significantly correlated with executive function decline. Finally, mediation analysis revealed the glucose metabolism mediated the FC decline with age and FC mediated the executive function deficits. Conclusions: Our findings indicated that covariance between glucose metabolism and FC in the pDMN is one of the main routes that contributes to age-related executive function decline.