Individual metabolic brain network abnormalities associated with drug-resistant mTLE vary in surgical outcomes

Front Neurol. 2024 Dec 18:15:1444787. doi: 10.3389/fneur.2024.1444787. eCollection 2024.

Abstract

Objective: This investigation aimed to elucidate alterations in metabolic brain network connectivity in drug-resistant mesial temporal lobe epilepsy (DR-MTLE) patients, relating these changes to varying surgical outcomes.

Methods: A retrospective cohort of 87 DR-MTLE patients who underwent selective amygdalohippocampectomy was analyzed. Patients were categorized based on Engel surgical outcome classification into seizure-free (SF) or non-seizure-free (NSF) groups. Additionally, 38 healthy individuals constituted a control group (HC). Employing effect size (ES) methodology, we constructed individualized metabolic brain networks and compared metabolic connectivity matrices across these groups using the DPABINet toolbox.

Results: Compared to HCs, both SF and NSF groups exhibited diminished metabolic connectivity, with the NSF group showing pronounced reductions across the whole brain. Notably, the NSF group demonstrated weaker metabolic links between key networks, including the default mode network (DMN), frontoparietal network (FPN), and visual network (VN), in comparison to the SF group.

Conclusion: Individual metabolic brain networks, constructed via ES methodology, revealed significant disruptions in DR-MTLE patients, predominantly in the NSF group. These alterations, particularly between limbic structures and cognitive networks like the DMN, suggested impaired and inefficient information processing across the brain's networks. This study identified abnormal brain networks associated with DR-MTLE and, importantly, contributed novel insights into the mechanisms underlying poor postoperative seizure control, and offered potential implications for refining preoperative assessments.

Keywords: connectivity analysis; drug-resistant mesial temporal lobe epilepsy; effect size; positron emission tomography-computed tomography; surgical outcomes.

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by grants from the Natural Science Foundation of Fujian Province (Grant No. 2019J01524) and Fujian Province guided project, China (Grant No. 2023Y0066).