Usefulness of brain FDG PET/CT imaging in pediatric patients with suspected autoimmune encephalitis from a prospective study.

Journal: European Journal Of Nuclear Medicine And Molecular Imaging
Published:
Abstract

Purpose: Early diagnosis and treatment are of paramount importance for pediatric patients with autoimmune encephalitis (AE). The aim is to evaluate the usefulness of FDG PET/CT in pediatric patients with suspected AE from a prospective study.

Methods: The prospective study was conducted over a period of 23.5 months from May 14, 2019, to April 30, 2021. All patients (< 18-year-old) were hospitalized at the department of pediatric neurology and met the criteria of clinical suspected AE. The children underwent the tests of blood samplings, CSF, EEG, MRI, and 18F-FDG PET/CT. The criteria for FDG PET/CT diagnosis of AE were large lobar hypometabolism with or without focal hypermetabolism found on PET/CT. The clinical final diagnosis of AE includes seropositive and seronegative AE based on the diagnostic criteria.

Results: One hundred four pediatric inpatients (57 boys, 47 girls) were included, of which 58 children were diagnosed with AE (seropositive, 16; seronegative, 42), 45 children were diagnosed with non-AE, and one boy remained indeterminate diagnosis. Large lobar hypometabolism was found in 61 children, of which 54 (88.5%) children were finally diagnosed with AE. The sensitivity, specificity, and accuracy of FDG PET/CT for diagnosis of AE were 93.1%, 84.4%, and 89.3%, respectively, with a positive predictive value of 88.5% and a negative predictive value of 90.5%. The most common involved with hypometabolism was the parietal lobe, followed by occipital and frontal lobes, finally the temporal lobe on PET/CT in children with AE.

Conclusion: Brain FDG PET/CT imaging has high specificity, sensitivity, and accuracy for diagnosis of AE in clinical suspected AE children. Trial registration: null Clinical trials: gov. NCT02969213. Registered 17 October 2016.

Authors
Yafu Yin, Jing Wu, Shuqi Wu, Suyun Chen, Weiwei Cheng, Ling Li, Hui Wang