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Spatio-temporal heterogeneity in hippocampal metabolism in control and epilepsy conditions.

ABSTRACT: The hippocampus's dorsal and ventral parts are involved in different operative circuits, the functions of which vary in time during the night and day cycle. These functions are altered in epilepsy. Since energy production is tailored to function, we hypothesized that energy production would be space- and time-dependent in the hippocampus and that such an organizing principle would be modified in epilepsy. Using metabolic imaging and metabolite sensing ex vivo, we show that the ventral hippocampus favors aerobic glycolysis over oxidative phosphorylation as compared to the dorsal part in the morning in control mice. In the afternoon, aerobic glycolysis is decreased and oxidative phosphorylation increased. In the dorsal hippocampus, the metabolic activity varies less between these two times but is weaker than in the ventral. Thus, the energy metabolism is different along the dorsoventral axis and changes as a function of time in control mice. In an experimental model of epilepsy, we find a large alteration of such spatiotemporal organization. In addition to a general hypometabolic state, the dorsoventral difference disappears in the morning, when seizure probability is low. In the afternoon, when seizure probability is high, the aerobic glycolysis is enhanced in both parts, the increase being stronger in the ventral area. We suggest that energy metabolism is tailored to the functions performed by brain networks, which vary over time. In pathological conditions, the alterations of these general rules may contribute to network dysfunctions.

SUBMITTER: Brancati GE

PROVIDER: S-EPMC7980466 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectiveTo provide a multi-atlas framework for automated hippocampus segmentation in temporal lobe epilepsy (TLE) and clinically validate the results with respect to surgical lateralization and post-surgical outcome.MethodsWe retrospectively identified 47 TLE patients who underwent surgical resection and 12 healthy controls. T1-weighted 3 T MRI scans were acquired for all subjects, and patients were identified by a neuroradiologist with regards to lateralization and degree of hippocampal sclerosis (HS). Automated segmentation was implemented through the Joint Label Fusion/Corrective Learning (JLF/CL) method. Gold standard lateralization was determined from the surgically resected side in Engel I (seizure-free) patients at the two-year timepoint. ROC curves were used to identify appropriate thresholds for hippocampal asymmetry ratios, which were then used to analyze JLF/CL lateralization.ResultsThe optimal template atlas based on subject images with varying appearances, from normal-appearing to severe HS, was demonstrated to be composed entirely of normal-appearing subjects, with good agreement between automated and manual segmentations. In applying this atlas to 26 surgically resected seizure-free patients at a two-year timepoint, JLF/CL lateralized seizure onset 92% of the time. In comparison, neuroradiology reads lateralized 65% of patients, but correctly lateralized seizure onset in these patients 100% of the time. When compared to lateralized neuroradiology reads, JLF/CL was in agreement and correctly lateralized all 17 patients. When compared to nonlateralized radiology reads, JLF/CL correctly lateralized 78% of the nine patients.SignificanceWhile a neuroradiologist's interpretation of MR imaging is a key, albeit imperfect, diagnostic tool for seizure localization in medically-refractory TLE patients, automated hippocampal segmentation may provide more efficient and accurate epileptic foci localization. These promising findings demonstrate the clinical utility of automated segmentation in the TLE MR imaging pipeline prior to surgical resection, and suggest that further investigation into JLF/CL-assisted MRI reading could improve clinical outcomes. Our JLF/CL software is publicly available at https://www.nitrc.org/projects/ashs/.

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Spatio-temporal heterogeneity in hippocampal metabolism in control and epilepsy conditions.

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