Unknown

Dataset Information

0

Metabolic covariance networks combining graph theory measuring aberrant topological patterns in mesial temporal lobe epilepsy.


ABSTRACT:

Objective

We aimed to study the networks' mechanism of metabolic covariance networks in mesial temporal lobe epilepsy (mTLE), through examining the brain value of fluorine-18-fluorodeoxyglucose positron emission tomography (18 F-FDG-PET).

Methods

18 F-FDG-PET images from 16 patients with mTLE were analyzed using local and global metabolic covariance network (MCN) approaches, including whole metabolic pattern analysis (WMPA), hippocampus-based (h-) MCN, whole brain (w-) MCN, and edge-based connectivity analysis (EBCA).

Results

WMPA showed a typical ipsilateral hypometabolism and contralateral hypermetabolism pattern to epileptic zones in mTLE. h-MCN revealed decreased hippocampus-based synchronization in contralateral regions. w-MCN exhibited a disrupted metabolic network with globally increased small-world properties and regionally decreased nodal metrics in the ipsilateral hemisphere. Hippocampus (h)-EBCA and whole brain EBCA (w-EBCA) both detected a reduced-connectivity dominated metabolic covariant network. Moreover, the reduced interhemisphere connectivity seemingly played a major role in the aberrant epileptic topological pattern.

Conclusion

From a metabolic point of view, we demonstrated the damaging effects with reduced contralateral intranetwork metrics properties and the compensatory effects in contralateral intranetworks with increased network properties. However, the import role of significant reduced interhemisphere connection has rarely been reported in other mTLE studies. Taken together, 18 F-FDG-PET MCN analysis provides new evidence that the mTLE is a system neurological disorder with disrupted networks.

SUBMITTER: Wang KL 

PROVIDER: S-EPMC6488969 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

2010-06-11 | E-GEOD-6773 | biostudies-arrayexpress
2007-01-23 | GSE6773 | GEO
| S-EPMC6870458 | biostudies-literature
| S-EPMC5013648 | biostudies-literature
| S-EPMC6866709 | biostudies-literature
2012-12-01 | E-GEOD-25453 | biostudies-arrayexpress
2007-01-23 | E-GEOD-6771 | biostudies-arrayexpress
| S-EPMC5877322 | biostudies-literature
| S-EPMC4867275 | biostudies-literature
| S-EPMC3420694 | biostudies-literature