The goal of this study was to evaluate the performances of SPM analysis of FDG-PET in children using an age-matched pseudo-control group of epileptic patients with robustly negative imaging versus classical healthy young adult controls. Both SPM analyses achieve a similar rate of detection of hypometabolic clusters and perform as well as visual analysis, not only in MRI-positive patients but also in MRI-negative ones. Although the sensitivity of SPM is not increased using pediatric vs. adult controls (79% vs. 87%), specificity is increased (97% vs. 89%) due to the reduction of the number of hypometabolic artifacts detected. As a result the positive predictive value of the method rises from 65% to 86%. That provides a relevant clinical impact especially in the younger children.
Visual inspection of FDG-PET images is extensively used in clinical epilepsy practice and remains the reference method of analysis in children
[14, 27]. The hypometabolic areas detected have been proved to include the seizure onset zone, although they usually are more extended and do not delineate it
[6, 8]. The localizing value of visual PET analysis varies from 36% to 73% in extratemporal cases, depending whether MRI is negative or not
[9, 20], and reaches 90% exclusively in temporal lobe cases
. This detection value can be improved, particularly in extratemporal epilepsy with negative MRI, using PET/MRI coregistration
[12, 13]. That has been confirmed by intracranial EEG and post-operative data. The present 56% detection rate of relevant hypometabolic areas is therefore in accordance with the literature, if one considers that we did not use coregistration and that the series mostly comprises MRI-negative patients and children with extratemporal epilepsy. In addition, the ability to detect a hypometabolic area visually is subjective and depends on the expertise and experience of the observer. Most reported series tend to limit this bias by achieving a consensus between closely performing readers, as we presently did with a first concordance of 0.81.
By contrast, SPM analysis is observer independent
[1, 2]. Taking the whole brain into account, it allows assessing the spatial extent and location of the abnormal site on the brain map with no a priori hypothesis. Initially dedicated to the comparison of data sets among groups of subjects, SPM method also proved to be reliable for quantitative analysis of individual FDG-PET scans in various neurological disorders, including epilepsy
. SPM analysis has been widely applied to the study of adults with epilepsy, with thresholds varying from p < 0.001 (uncorrected) to p < 0.05 (corrected) and >20 voxels to >250 voxels
[5, 7]. Since SPM showed comparable sensitivity to visual assessment, it is considered as an aid in diagnosing seizure onset zones in temporal as well as in extratemporal lobe epilepsy and in lesional as well as in non-lesional cases
[5, 7, 12, 15, 16, 38].
In children, experience with SPM in epilepsy is more limited. Only one study formally assessed the role of statistical threshold on sensitivity and specificity
: they found p < 0.001 as the best compromise, as we presently do. Based on young adults as controls, the results are not univocal. De Tiege et al. did succeed detecting areas of remote inhibition in children aged 5 to 11 years with a particular epileptic encephalopathy and to see them vanish when epilepsy and cognitive deficits recover
[24, 39, 40]. Some authors showed a high SPM performance (86%) for correct localization of the seizure onset zone in adolescents (12 to 15 years)
, but others achieved a rate of only 13% in children from the age of 3
. In another series, the same procedure gave an SPM sensitivity of 74% in children over 6 years old
, whereas it failed in children under 6 years of age due to a significant proportion of artifacts
. We also found a high number of such false positive hypometabolic clusters when using an adult template, at a threshold stringent for such an individual SPM analysis
. One main issue is the different sizes of the head of adults and young children
. We confirm here that this artifact rate is higher in the younger ages and can be reduced by using a pediatric template
. Another potential advantage of a pseudo-normal epilepsy group could be that the potential effect of the antiepileptic drugs is largely cancelled out since both the patients and the control groups were on antiepileptic medication
. To generate even better templates, one could speculate on data from other pathologies that justify whole-body PET scanning but may respect the brain, like pediatric lymphoma, for example
In order to deal with the pediatric controls the closest to “normals”, we confirmed PET negativity using the Signorini’s method
: each data set of the pseudo-control group was compared to the rest of the group using SPM. The complete procedure excluded three additional children. Our main result is a gain of specificity and this pediatric procedure reaches the highest rates ever reported in epilepsy for SPM. Conversely, the predictive positive value is improved, thus decreasing the number of artifacts and optimizing the clinical relevance of SPM analysis compared to the classical adult procedure. We assume that these advantages of pediatric SPM can compensate the slightly decreased sensitivity compared to adult SPM (79% vs. 87%). Note that these rates of sensitivity and specificity apply to SPM analysis and not to FDG-PET in general, since we excluded from their calculation the major part of negative cases. Nevertheless, this method was robustly able to identify some clinically relevant hypometabolic areas missed by visual analysis in 6% of cases.
Although our template presents with the usual balance of specificity versus sensitivity, we recently showed the whole procedure to be beneficial also in multifocal childhood epilepsy when visual PET analysis fails to detect bilateral abnormalities, as in school-age children with a fever-induced epileptic encephalopathy