Authors :
First Author: Seung Soo Kim, MD, PhD – Soonchunhyang University College of Medicine
Presenting Author: Han Na Jang, MD –
Han Na Jang, MD – Pediatrics – Soonchunhyang University College of Medicine; Jin Yong Jeon, PhD – Professor, Architectural Engineering, Hanyang University; Dong Hyun Ahn, MD – Professor, Neuropsychiatry, Hanyang University College of Medicine; Jin-Hwa Moon, MD – Professor, Pediatrics, Hanyang University College of Medicine
Rationale:
There have been reports that many children with childhood absence epilepsy (CAE) are experiencing attention problems or other cognitive difficulties. Cognitive problems in CAE may be related with altered brain networks which are also affect the pathophysiology of epilepsy. However, brain network researches are still mainly conducted on patients with intractable epilepsy using invasive electroencephalography (EEG) and functional images for the epilepsy surgery, and there had been few researches on CAE patients. With these backgrounds, the authors attempted to analyze the difference in brain connectivity of CAE patients on sleep EEG, according to the resolution of 3 Hz spike-and-wave discharges (SWD) with anti-seizure medication (ASM), which is one of the major biomarkers for the drug responsiveness in CAE patients, by using graph theory analysis.
Methods:
Authors retrospectively reviewed the medical records of patients who were diagnosed CAE and prescribed ASM at one university hospital. The average montage waking and sleep EEGs recorded in the international 10-20 system were analyzed, and the subjects were divided into the pSWD group with positive 3 Hz SWD on waking EEG with ASM and the nSWD group with negative 3 Hz SWD with ASM. The Epochs on sleep stage 1 and 2 were used for connectivity analysis. The analysis was conducted according to the following steps. 1) Imaginary coherence (ImCoh) between each channel is calculated for each frequency band (delta [0.5-4.0 Hz], theta [4.0-8.0 Hz], alpha [8.0-12.0 Hz], sigma [12.0-16.0 Hz], beta [16.0-30.0 Hz], gamma [30.0-50.0 Hz]); 2) Using the ImCoh, graph theory analysis was performed and small worldness (omega), characteristic path length (CPL), and average clustering coefficient (ACC) were calculated; 3) The differences between the pSWD group and the nSWD group were compared and analyzed. For comparison between the two groups, independent t test and Fisher's exact test was used. Python 3.8.0 and its packages (MNE-python, networkx) were used for the analysis.
Results:
Finally fifteen patients were included in the analysis. There were five subjects (mean age 11.2 ± 1.8 year-old, five girls) in pSWD, and 10 subjects (mean age 8.8 ± 2.6 year-old, 8 girls) in nSWD. ACC between pSWD and nSWD showed significant differences in the sigma and the gamma frequency bands (
P=0.02 and 0.03, respectively). In the other frequency bands, there was no statistically significant difference in ACC between the two groups (Table 1). There was no statistically significant difference in omega and CPL in all frequency bands between the two groups.
Conclusions:
In this study, we found differences in ACC according to the resolution of 3 Hz SWD with ASM in the sigma and the gamma frequency band, which were suspected to be related with sleep dependent learning and emotional integration. This is suggestive of a relationship between cognitive function and treatment responsiveness in CAE patients.
Funding:
A grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health &Welfare, Republic of Korea (grant number : RS-2023-00267049).