Balfroid T, Warren AE, Dalic LJ, Aeby A, Berlangieri SU, Archer JS. Frontoparietal 18F-FDG-PET hypo-metabolism in Lennox-Gastaut syndrome: further evidence highlighting the key network.
Epilepsy Res 2023;
192:107131. [PMID:
37054522 DOI:
10.1016/j.eplepsyres.2023.107131]
[Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 03/20/2023] [Accepted: 03/27/2023] [Indexed: 03/31/2023]
Abstract
INTRODUCTION
Lennox Gastaut syndrome (LGS) can be conceptualised as a "secondary network epilepsy", in which the shared electroclinical manifestations reflect epileptic recruitment of a common brain network, despite a range of underlying aetiologies. We aimed to identify the key networks recruited by the epileptic process of LGS using interictal 2-deoxy-2-(18F)fluoro-D-glucose positron emission tomography (18F-FDG-PET).
METHODS
Group analysis of cerebral 18F-FDG-PET, comparing 21 patients with LGS (mean age = 15 years) and 18 pseudo-controls (mean age = 19 years), studied at Austin Health Melbourne, between 2004 and 2015. To minimise the influence of individual patient lesions in the LGS group, we only studied brain hemispheres without structural MRI abnormalities. The pseudo-control group consisted of age- and sex-matched patients with unilateral temporal lobe epilepsy, using only the hemispheres contralateral to the side of epilepsy. Voxel-wise permutation testing compared 18F-FDG-PET uptake between groups. Associations were explored between areas of altered metabolism and clinical variables (age of seizure onset, proportion of life with epilepsy, and verbal/nonverbal ability). Penetrance maps were calculated to explore spatial consistency of altered metabolic patterns across individual patients with LGS.
RESULTS
Although not always readily apparent on visual inspection of individual patient scans, group analysis revealed hypometabolism in a network of regions including prefrontal and premotor cortex, anterior and posterior cingulate, inferior parietal lobule, and precuneus (p < 0.05, corrected for family-wise error). These brain regions tended to show a greater reduction in metabolism in non-verbal compared to verbal LGS patients, although this difference was not statistically significant. No areas of hypermetabolism were detected on group analysis, although ∼25 % of individual patients showed increased metabolism (relative to pseudo-controls) in the brainstem, putamen, thalamus, cerebellum, and pericentral cortex.
DISCUSSION
Interictal hypometabolism in frontoparietal cortex in LGS is compatible with our previous EEG-fMRI and SPECT studies showing that interictal bursts of generalised paroxysmal fast activity and tonic seizures recruit similar cortical regions. This study provides further evidence that these regions are central to the electroclinical expression of LGS.
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