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Published on: January 20, 2023
Quantitative brain 18F-FDG PET/CT analysis in seronegative autoimmune encephalitis
Samantha N Roman1, Moe S Sadaghiani2, Luisa A Diaz-Arias1
1Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Brain 18F-FDG PET/CT scans reveal a common pattern of frontal lobe hypometabolism and medial temporal lobe hypermetabolism in seronegative autoimmune encephalitis (AE). This finding may serve as a potential biomarker for earlier AE diagnosis and treatment.
Area of Science:
- Neurology
- Nuclear Medicine
- Immunology
Background:
- Autoimmune encephalitis (AE) diagnosis can be challenging, especially in seronegative cases.
- Previous studies identified specific brain 18F-FDG PET/CT dysmetabolism patterns in anti-NMDAR and anti-LGI1 AE.
- Brain 18F-FDG PET/CT abnormalities in seronegative AE remain undescribed.
Purpose of the Study:
- To investigate brain 18F-FDG PET/CT findings in patients with seronegative autoimmune encephalitis.
- To identify common patterns of brain dysmetabolism in seronegative AE.
- To compare these patterns with those observed in anti-NMDAR and anti-LGI1 AE.
Main Methods:
- Cross-sectional analysis of brain 18F-FDG PET/CT data from patients with seronegative AE.
- Utilized NeuroQ™ software to calculate Z-scores for 47 brain regions.
- Compared findings with healthy controls and previously reported anti-NMDAR and anti-LGI1 AE cohorts.
Main Results:
- Eight probable and nine possible seronegative AE cases were analyzed.
- Both seronegative groups exhibited similar patterns of brain dysmetabolism.
- A consistent pattern of frontal lobe hypometabolism and medial temporal lobe hypermetabolism was observed, mirroring patterns in other AE types.
- Changes in PET/CT findings correlated with clinical status in four patients with serial scans.
Conclusions:
- A distinct 18F-FDG PET/CT pattern of frontal hypometabolism and medial temporal hypermetabolism may serve as a common biomarker for autoimmune encephalitis.
- This imaging pattern, combined with clinical data, could aid in earlier AE diagnosis and treatment initiation.
- Further research is warranted to validate this potential biomarker across diverse AE populations.
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