Predictive modeling based on functional connectivity of interictal scalp EEG for infantile epileptic spasms syndrome

Sotaro Kanai; Masayoshi Oguri; Tohru Okanishi; Yosuke Miyamoto; Masanori Maeda; Kotaro Yazaki; Ryuki Matsuura; Takenori Tozawa; Satoru Sakuma; Tomohiro Chiyonobu; Shin-Ichiro Hamano; Yoshihiro Maegaki

doi:10.1016/j.clinph.2024.08.016

Predictive modeling based on functional connectivity of interictal scalp EEG for infantile epileptic spasms syndrome

Clin Neurophysiol. 2024 Aug 30:167:37-48. doi: 10.1016/j.clinph.2024.08.016. Online ahead of print.

Authors

Affiliations

¹ Division of Child Neurology, Institute of Neurological Sciences, Faculty of Medicine, Tottori University, 86 Nishi-cho, Yonago 683-8503, Japan. Electronic address: s.kanai82@gmail.com.
² Department of Medical Technology, Kagawa Prefectural University of Health Sciences, 281-1 Mure-cho, Takamatsu 761-0123, Japan.
³ Division of Child Neurology, Institute of Neurological Sciences, Faculty of Medicine, Tottori University, 86 Nishi-cho, Yonago 683-8503, Japan.
⁴ Department of Pediatrics, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi Hirokoji, Kamigyo-ku, Kyoto 602-8566, Japan.
⁵ Department of Pediatrics, Wakayama Medical University, 811-1 Kimiidera, Wakayama 641-8509, Japan.
⁶ Department of Pediatrics, Osaka Metropolitan University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585, Japan.
⁷ Division of Neurology, Saitama Children's Medical Center, 1-2 Shintoshin, Chuo-ku, Saitama 330-8777, Japan.

PMID: 39265289
DOI: 10.1016/j.clinph.2024.08.016

Abstract

Objective: This study aims to delineate the electrophysiological variances between patients with infantile epileptic spasms syndrome (IESS) and healthy controls and to devise a predictive model for long-term seizure outcomes.

Methods: The cohort consisted of 30 individuals in the seizure-free group, 23 in the seizure-residual group, and 20 in the control group. We conducted a comprehensive analysis of pretreatment electroencephalography, including the relative power spectrum (rPS), weighted phase-lag index (wPLI), and network metrics. Follow-up EEGs at 2 years of age were also analyzed to elucidate physiological changes among groups.

Results: Infants in the seizure-residual group exhibited increased rPS in theta and alpha bands at IESS onset compared to the other groups (all p < 0.0001). The control group showed higher rPS in fast frequency bands, indicating potentially enhanced cognitive function. The seizure-free group presented increased wPLI across all frequency bands (all p < 0.0001). Our predictive model utilizing wPLI anticipated long-term outcomes at IESS onset (area under the curve 0.75).

Conclusion: Our findings demonstrated an initial "hypersynchronous state" in the seizure-free group, which was ameliorated following successful treatment.

Significance: This study provides a predictive model utilizing functional connectivity and insights into the diverse electrophysiology observed among outcome groups of IESS.

Keywords: Brain network; EEG quantitative analysis; Epileptic spasms; Functional connectivity; Power analysis; West syndrome.