Prediction of Radiofrequency Thermocoagulation Outcomes Based on High Frequency Oscillation Network
Abstract number :
3.034
Submission category :
1. Basic Mechanisms / 1C. Electrophysiology/High frequency oscillations
Year :
2024
Submission ID :
872
Source :
www.aesnet.org
Presentation date :
12/9/2024 12:00:00 AM
Published date :
Authors :
Xiaofeng Yang, MD – Guangzhou Medical University
Jiaoyang Wang, PhD, MD – Guangzhou Lab
Guoyun Feng, PhD,MD – Guangzhou Lab
Presenting Author: Xiaofeng Yang, MD – Guangzhou Medical University
Rationale: This study aims to conduct retrospective and prospective studies on radiofrequency thermocoagulation (RFTC) to ablate key nodes in the epileptic high-frequency oscillation (HFO) network, aiming to explore the feasibility of controlling epilepsy by modulating HFO network.
Methods: In the retrospective study, we enrolled 40 patients undergoing RFTC across three comprehensive epilepsy centers. We randomly selected 5-minute intracranial interictal electroencephalogram segments of during slow-wave sleep for each patient. The HFO network was plotted using a time-delayed network analysis method, and the key nodes of the HFO network were divided into three levels (1, 2, 3) bases on the HFO propagation intensity. We compared the ablation ratios of key nodes and analyzed changes in HFO characteristics and network connection strengths before and after RFTC in relation to patient prognosis. Additionally, the coupling between theta band and HFOs was compared to explore the possible mechanism of HFO network formation. Finally, we conducted a prospective clinical trial involving three patients to further validate clinical applications.
Results: Ripple networks encompass larger brain areas compared to fast ripples (FR) networks. Key nodes at different levels showed distinct theta-HFO coupling features. Post-RFTC, patients with good prognoses experienced significant decreases in HFO rate and network connection strength, whereas those with poor prognoses showed negligible changes. Complete ablation of grade 1 and 2 key nodes in the ripple network strongly correlated with good outcome. Additionally, the complete disappearance of ripples within the RFTC area predicted postoperative seizure-free, whereas the emergence or increase of FRs in the peri-RFTC area indicated poorer outcomes.
Conclusions: Given the correspondence between epileptic HFO network dynamics and the epileptogenic network, complete destruction of the highly interconnected HFO network is crucial for a good outcome. Cross-frequency coupling likely mediates the spread of HFOs and may serve as one of the mechanisms of HFO network formation. These findings underscore the potential of RFTC in modulating HFO networks to potentially mitigate epilepsy, providing valuable insights into therapeutic strategies and underlying mechanisms.
Funding: National Natural Science Foundation of China (XFY 82271492,
8197120) and China Association Against Epilepsy Research Fund (CU-2023-09).
Basic Mechanisms