18F-Flurodeoxyglucose positron emission tomography with computed tomography (FDG PET/CT) findings in children with encephalitis and comparison to conventional imaging.

PURPOSE: FDG PET/CT is emerging as a new tool for the evaluation of acute encephalitis (AE). However, to date, there are no exclusively pediatric studies on the use of FDG PET for suspected AE. The objective of this study was to compare qualitative and quantitative brain PET to conventional brain imaging in a cohort of children, and to identify patterns of metabolic abnormalities characteristic of AE. METHODS: This retrospective study included 34 children imaged with PET/CT, CT and magnetic resonance imaging (MRI). The positivity rate of all three imaging modalities was measured. Besides visual assessment, quantification of relative regional brain metabolism (RRBM) was performed and compared to a database of normal pediatric brains. RESULTS: Fourteen subjects had a clinical diagnosis of autoimmune encephalitis (AIE) or encephalitis of unknown origin (EX), six of anti-N-methyl-D-aspartate receptor (anti-NMDAr) encephalitis, three of Hashimoto's encephalopathy, three of neurolupus and eight had other subtypes of encephalitis. Quantitative PET was abnormal in 100% of cases, visually assessed PET in 94.1% of subjects, MRI in 41.2% and CT in 6.9%. RRBM quantification demonstrated multiple hyper and hypo metabolic cortical regions in 82.3% of subjects, exclusively hypermetabolic abnormalities in 3%, and exclusively hypometabolic abnormalities in 14.7%. The basal ganglia were hypermetabolic in 26.5% of cases on visual assessment and in 58.8% of subjects using quantification. CONCLUSION: In our pediatric population FDG PET was more sensitive than conventional imaging for the detection of AE, and basal ganglia hypermetabolism was frequently encountered.

Modeling the Effects of Age and Sex on Normal Pediatric Brain Metabolism Using 18F-FDG PET/CT.

Reference databases of pediatric brain metabolism are uncommon, because local brain metabolism evolves significantly with age throughout childhood, limiting their clinical applicability. The aim of this study was to develop mathematic models of regional relative brain metabolism using pediatric 18F-FDG PET with CT data of normal pediatric brains, accounting for sex and age. Methods: PET/CT brain acquisitions were obtained from 88 neurologically normal subjects, aged 6 mo to 18 y. Subjects were assigned to either a development group (n = 59) or a validation group (n = 29). For each subject, commercially available software was used to quantify the relative metabolism of 47 separate brain regions using whole-brain-normalized (WBN) and pons-normalized (PN) activity. The effects of age on regional relative brain metabolism were modeled using multiple linear and nonlinear mathematic equations, and the significance of sex was assessed using the Student t test. Optimal models were selected using the Akaike information criterion. Mean predicted values and 95% prediction intervals were derived for all regions. Model predictions were compared with the validation dataset, and mean predicted error was calculated for all regions using both WBN and PN models. Results: As a function of age, optimal models of regional relative brain metabolism were linear for 9 regions, quadratic for 13, cubic for 6, logarithmic for 12, power law for 7, and modified power law for 2 using WBN data and were linear for 9, quadratic for 25, cubic for 2, logarithmic for 6, and power law for 4 using PN data. Sex differences were found to be statistically significant only in the posterior cingulate cortex for the WBN data. Comparing our models with the validation group resulted in 94.3% of regions falling within the 95% prediction interval for WBN and 94.1% for PN. For all brain regions in the validation group, the error in prediction was 3% ± 0.96% using WBN data and 4.72% ± 1.25% when compared with the PN data (P < 0.0001). Conclusion: Pediatric brain metabolism is a complex function of age and sex. We have developed mathematic models of brain activity that allow for accurate prediction of regional pediatric brain metabolism.

Complete normalization of severe brain 18F-FDG hypometabolism following electroconvulsive therapy in a major depressive episode.

We describe a patient with a complex neuropsychiatric disorder who presented a severe and diffuse cerebral glucose hypometabolism on (18)F-FDG PET initially which, in the clinical setting, was suspicious of an advanced neurodegenerative disease. Further evaluation suggested a major depressive episode with agitation and poor response to medication. Electroconvulsive therapy (ECT) brought excellent results. A follow-up cerebral (18)F-FDG PET was completely normal, thus illustrating the potential for complete recovery and normalization of brain metabolism in major depressive episode following ECT. It also shows the risk of false interpretation of brain PET in patients with depression.