Computer-Aided Diagnosis and Localization of Lateralized Temporal Lobe Epilepsy Using Interictal FDG-PET
Open Access
- 1 January 2013
- journal article
- research article
- Published by Frontiers Media SA in Frontiers in Neurology
- Vol. 4, 31
- https://doi.org/10.3389/fneur.2013.00031
Abstract
Interictal FDG-PET (iPET) is a core tool for localizing the epileptogenic focus, potentially before structural MRI, that does not require rare and transient epileptiform discharges or seizures on EEG. The visual interpretation of iPET is challenging and requires years of epilepsy-specific expertise. We have developed an automated computer-aided diagnostic (CAD) tool that has the potential to work both independent of and synergistically with expert analysis. Our tool operates on distributed metabolic changes across the whole brain measured by iPET to both diagnose and lateralize temporal lobe epilepsy (TLE). When diagnosing left TLE (LTLE) or right TLE (RTLE) vs. non-epileptic seizures (NES), our accuracy in reproducing the results of the gold standard long term video-EEG monitoring was 82% [95% confidence interval (CI) 69–90%] or 88% (95% CI 76–94%), respectively. The classifier that both diagnosed and lateralized the disease had overall accuracy of 76% (95% CI 66–84%), where 89% (95% CI 77–96%) of patients correctly identified with epilepsy were correctly lateralized. When identifying LTLE, our CAD tool utilized metabolic changes across the entire brain. By contrast, only temporal regions and the right frontal lobe cortex, were needed to identify RTLE accurately, a finding consistent with clinical observations and indicative of a potential pathophysiological difference between RTLE and LTLE. The goal of CADs is to complement – not replace – expert analysis. In our dataset, the accuracy of manual analysis (MA) of iPET (∼80%) was similar to CAD. The square correlation between our CAD tool and MA, however, was only 30%, indicating that our CAD tool does not recreate MA. The addition of clinical information to our CAD, however, did not substantively change performance. These results suggest that automated analysis might provide clinically valuable information to focus treatment more effectively.This publication has 106 references indexed in Scilit:
- Hemispheric Asymmetry in White Matter Connectivity of the Temporoparietal Junction with the Insula and Prefrontal CortexPLOS ONE, 2012
- Classification and Lateralization of Temporal Lobe Epilepsies with and without Hippocampal Atrophy Based on Whole-Brain Automatic MRI SegmentationPLOS ONE, 2012
- Predicting Regional Neurodegeneration from the Healthy Brain Functional ConnectomeNeuron, 2012
- Surgical decision making in temporal lobe epilepsy: A comparison of [18F]FDG-PET, MRI, and EEGEpilepsy & Behavior, 2011
- Hippocampal Sclerosis in Temporal Lobe Epilepsy: Findings at 7 TRadiology, 2011
- Asymmetrical hippocampal connectivity in mesial temporal lobe epilepsy: evidence from resting state fMRIBMC Neuroscience, 2010
- Electrical source imaging for presurgical focus localization in epilepsy patients with normal MRIEpilepsia, 2010
- Multimodal neuroimaging in presurgical evaluation of childhood epilepsyKorean Journal of Pediatrics, 2010
- 18F‐FCWAY and 18F‐FDG PET in MRI‐negative temporal lobe epilepsyEpilepsia, 2009
- FDG-PET/MRI coregistration improves detection of cortical dysplasia in patients with epilepsyNeurology, 2008