A New Method for Objective 3D surface evaluation of electrophysiologic correlates of Cerebral Glucose Metabolic Abnormalities in Children with Focal Epilepsy
Abstract number :
3.202
Submission category :
5. Neuro Imaging / 5B. Structural Imaging
Year :
2016
Submission ID :
199056
Source :
www.aesnet.org
Presentation date :
12/5/2016 12:00:00 AM
Published date :
Nov 21, 2016, 18:00 PM
Authors :
Jeong Won Jeong, Wayne State University, Children's Hospital of Michigan; Vinod Kumar. Pilli, Wayne State University, Children's Hospital of Michigan; Yasuo Nakai, Wayne State University, Children's Hospital of Michigan, Detroit Medical Center; Eishi Asan
Rationale: 2-deoxy-2[18F]fluoro-D-glucose positron emission tomography (FDG-PET) has been widely applied for presurgical localization of epileptic foci. However, ictal and interictal electrophysiologic correlates of FDG-PET abnormalities remain poorly understood. Our previous studies suggested that hypometabolic cortical areas can identify general regions of epileptic cortex, but seizures may also originate from normometabolic cortex [Juhasz et al. Ann Neur 2001, Alkonyi et al. Epilepsy Res 2010]. To further address the spatial relationship of glucose metabolic and intracranial EEG abnormalities, we have now developed a novel methodology to correlate objectively identified hypo- and hypermetabolic cortical regions with ictal and interictal electrocorticography (ECoG) changes on the 3-D brain surface. Methods: FDG PET scans of 64 children (pseudo-control group; mean age: 9.0 years; age range: 1-18 years) with non-lesional partial epilepsy and normal MRI and FDG PET (on visual analysis) were processed to create 5 pediatric PET templates for different age groups. SPM 8 (http://www.fil.ion.ucl.ac.uk/spm/) was used to compare the FDG PET scan of individual children with intractable focal epilepsy, who underwent two-stage epilepsy surgery with subdural electrodes, to FDG-PET scans of the appropriate age-matched control subgroup. The resulting t-statistic maps of two different contrasts: controls>patient (hypometabolism) and controls < patient (hypermetabolism) were co-registered to native 3D T1 volumetric MRI surface in order to directly compare these maps with ictal and interictal ECoG data including seizure onset and interictal spiking, respectively. Results: Figure 1 shows representative color-coded SPM t-statistic maps with corresponding ECoG data in four children with neocortical epileptic foci. Maximum hypometabolic cortex (highest t-score) was detected on the lateral (a), medial (b) and inferior (c) cortical surface of three different subjects, where the areas of the highest SPM t-statistic scores overlapped with a subset of electrodes showing interictal spiking (yellow electrodes) or seizure onset (red electrodes). In the fourth patient (d), an area of maximum hypermetabolism was detected in the inferior temporal cortex and corresponded to electrodes showing frequent interictal spiking (yellow electrodes). Conclusions: Using this methodology, measurement of SPM t-statistics objectively defining both hypo- and hypermetabolic cortical areas can directly be correlated with epileptogenic areas defined by ECoG. Further studies will optimize this approach and determine its accuracy to detect epileptogenic cortex in children with focal epilepsy above 1 year of age. Funding: This study was funded by a grant from National Institute of Neurological Disorders and Stroke (R01-NS089659 to J.J).
Neuroimaging