Optimizing statistical parametric mapping analysis of 18F-FDG PET in children

Abstract

BackgroundStatistical parametric mapping (SPM) procedure is an objective tool to analyze 18F-fluoro-2-deoxy-d-glucose-positron-emission tomography (FDG-PET) images and a useful complement to visual analysis. However, SPM requires a comparison to control data set that cannot be obtained in healthy children for ethical reasons. Using adults as controls showed some limitations. The purpose of the present study was to generate and validate a group of pseudo-normal children as a control group for FDG-PET studies in pediatrics.MethodsFDG-PET images of 47 children (mean ± SD age 10.2 ± 3.1 years) with refractory symptomatic (MRI-positive, n = 20) and cryptogenic (MRI-negative, n = 27) focal epilepsy planned for surgery were analyzed using visual and SPM analysis. Performances of SPM analysis were compared using two different control groups: (1) an adult control group consisting of healthy young adults (n = 25, 30.5 ± 5.8 years, adult PET template) and (2) a pediatric pseudo-control group consisting of patients (n = 24, 10.6 ± 3.1 years, children PET template) with refractory focal epilepsy but with negative MRI and with PET considered normal not only on visual analysis but also on SPM.ResultsAmong the 47 children, visual analysis succeeded detecting at least one hypometabolic area in 87% of the cases (interobserver kappa = 0.81). Regarding SPM analysis, the best compromise between sensitivity and specificity was obtained with a threshold of p less than 0.001 as an extent of more than 40 voxels. There was a significant concordance to detect hypometabolic areas between both SPM analyses [kappa (K) = 0.59; p < 0.005] and between both SPM and visual analyses (K = 0.45; p < 0.005), in symptomatic (K = 0.74; p < 0.005) as in cryptogenic patients (K = 0.26; p < 0.01). The pediatric pseudo-control group dramatically improved specificity (97% vs. 89%; p < 0.0001) by increasing the positive predictive value (86% vs. 65%). Sensitivity remained acceptable although it was not better (79% vs. 87%, p = 0.039). The main impact was to reduce by 41% the number of hypometabolic cortical artifacts detected by SPM, especially in the younger epileptic patients, which is a key point in clinical practice.ConclusionsThis age-matched pseudo-control group is a way to optimize SPM analysis of FDG-PET in children with epilepsy. It might also be considered for other brain pathologies in pediatrics in the future.

Objective 3D surface evaluation of intracranial electrophysiologic correlates of cerebral glucose metabolic abnormalities in children with focal epilepsy

“…We have shown that lobar accuracy of detection of the SOZ is similar to previously reported lobar accuracies in older pediatric and young adult groups [Lee et al, 2005; Kumar et al, 2010; Archambaud et al, 2013; vant’ Klooster et al, 2014]. In addition, by directly measuring the nearest Euclidean distance between ECoG-defined SOZ and SPM metabolic clusters on the actual 3D brain surface of individual patients, we found that 1) large portions of the hypometabolic abnormalities are located outside the SOZ, often at 30mm distance or beyond; 2) the hypometabolic abnormality provided slightly higher sensitivity to overlap focal SOZ than widespread SOZ; 3) hypermetabolic clusters were detected in 2/3 of the cases and were often associated with interictal epileptiform activity during FDG uptake; however, these hypermetabolic abnormalities were also observed mostly outside the ECoG-defined SOZ or ‘interictal spike zone’.…”

“…Although several previous studies utilized voxel-wise SPM analysis to objectively detect metabolic abnormalities in children with intractable epilepsy, none of those studies have reported how closely and accurately the SPM-defined cluster can detect ECoG-defined SOZ. Specifically, to define PET accuracy, the partial or total overlap of the hypometabolic region with the SOZ had been determined on either lobar basis or gyral level in previous studies [Kumar et al, 2010; Archambaud et al, 2013; vant’ Klooster et al, 2014]. This approximation of spatial correspondence inevitably resulted in variable performance of SPM analysis across the literature (e.g., sensitivity/specificity= 0.86/0.77 [Kumar et al, 2010], 0.79/0.97 [Archambaud et al, 2013], 0.35/0.90 [vant’ Klooster et al, 2014]).…”

Combined 18F-FDG-PET and diffusion tensor imaging in mesial temporal lobe epilepsy with hippocampal sclerosis

“…Cluster significant thresholds (extend threshold) were set at 50 contiguous voxels (Archambaud et al, 2013). Based on the results of previous studies (Dumas de la Roque et al, 2005, Gross, 2011), we selected only FA decrease and MD increase for further analysis.…”

Glucose Metabolic Profile by Visual Assessment Combined with Statistical Parametric Mapping Analysis in Pediatric Patients with Epilepsy

“…However, the visual assessment of 18 F-FDG PET images in the clinical application is subjective and relies on the experience and knowledge of the readers (23). Therefore, it is inevitable that the interpretation of a single image by visual assessment is variable among different observers, and subtle metabolic abnormalities of epilepsy might not be identified easily.…”