Decrease in the cortex/striatum metabolic ratio on [18F]-FDG PET: a biomarker of autoimmune encephalitis.

PURPOSE: The aim of this [18F]-FDG PET study was to determine the diagnostic value of the cortex/striatum metabolic ratio in a large cohort of patients suffering from autoimmune encephalitis (AE) and to search for correlations with the course of the disease. METHODS: We retrospectively collected clinical and paraclinical data of patients with AE, including brain 18F-FDG PET/CT. Whole-brain statistical analysis was performed using SPM8 software after activity parametrization to the striatum in comparison to healthy subjects. The discriminative performance of this metabolic ratio was evaluated in patients with AE using receiver operating characteristic curves against 44 healthy subjects and a control group of 688 patients with MCI. Relationship between cortex/striatum metabolic ratios and clinical/paraclinical data was assessed using univariate and multivariate analysis in patients with AE. RESULTS: Fifty-six patients with AE were included. In comparison to healthy subjects, voxel-based statistical analysis identified one large cluster (p-cluster < 0.05, FWE corrected) of widespread decreased cortex/striatum ratio in patients with AE. The mean metabolic ratio was significantly lower for AE patients (1.16 ± 0.13) than that for healthy subjects (1.39 ± 0.08; p < 0.001) and than that for MCI patients (1.32 ± 0.11; p < 0.001). A ratio threshold of 1.23 allowed to detect AE patients with a sensitivity of 71% and a specificity of 82% against MCI patients, and 98% against healthy subjects. A lower cortex/striatum metabolic ratio had a trend towards shorter delay before 18F-FDG PET/CT (p = 0.07) in multivariate analysis. CONCLUSION: The decrease in the cortex/striatal metabolic ratio has a good early diagnostic performance for the differentiation of AE patients from controls.

Single snapshot imaging of optical properties.

A novel acquisition and processing method that enables single snapshot wide field imaging of optical properties in the Spatial Frequency Domain (SFD) is described. This method makes use of a Fourier transform performed on a single image and processing in the frequency space to extract two spatial frequency images at once. The performance of the method is compared to the standard six image SFD acquisition method, assessed on tissue mimicking phantoms and in vivo. Overall both methods perform similarly in extracting optical properties.