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Sun L, Feng C, Zhang E, Chen H, Jin W, Zhu J, Yu L. High-performance prediction of epilepsy surgical outcomes based on the genetic neural networks and hybrid iEEG marker. Sci Rep 2024; 14:6198. [PMID: 38486013 PMCID: PMC10940588 DOI: 10.1038/s41598-024-56827-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 03/12/2024] [Indexed: 03/18/2024] Open
Abstract
Accurately identification of the seizure onset zone (SOZ) is pivotal for successful surgery in patients with medically refractory epilepsy. The purpose of this study is to improve the performance of model predicting the epilepsy surgery outcomes using genetic neural network (GNN) model based on a hybrid intracranial electroencephalography (iEEG) marker. We extracted 21 SOZ related markers based on iEEG data from 79 epilepsy patients. The least absolute shrinkage and selection operator (LASSO) regression was employed to integrated seven markers, selected after testing in pairs with all 21 biomarkers and 7 machine learning models, into a hybrid marker. Based on the hybrid marker, we devised a GNN model and compared its predictive performance for surgical outcomes with six other mainstream machine-learning models. Compared to the mainstream models, underpinning the GNN with the hybrid iEEG marker resulted in a better prediction of surgical outcomes, showing a significant increase of the prediction accuracy from approximately 87% to 94.3% (P = 0.0412). This study suggests that the hybrid iEEG marker can improve the performance of model predicting the epilepsy surgical outcomes, and validates the effectiveness of the GNN in characterizing and analyzing complex relationships between clinical data variables.
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Affiliation(s)
- Lipeng Sun
- Second Clinical Medical School, Zhejiang Chinese Medical University, Hangzhou, China
| | - Chen Feng
- Department of Neurosurgery, School of Medicine, Second Affiliated Hospital, Zhejiang University, Hangzhou, China
- School of Medicine, Epilepsy Center, Second Affiliated Hospital, Zhejiang University, Hangzhou, China
- Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China
| | - En Zhang
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- State Key Laboratory of Cognitive Neuroscience and Learning, Faculty of Psychology, Beijing Normal University, Beijing, China
| | - Huan Chen
- Department of Physical and Environmental Sciences, University of Toronto, Toronto, Canada
| | - Weifeng Jin
- School of Pharmacy, Zhejiang Chinese Medical University, Hangzhou, China
| | - Junming Zhu
- Department of Neurosurgery, School of Medicine, Second Affiliated Hospital, Zhejiang University, Hangzhou, China.
- School of Medicine, Epilepsy Center, Second Affiliated Hospital, Zhejiang University, Hangzhou, China.
| | - Li Yu
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, China.
- Key Laboratory of Drug Safety Evaluation and Research of Zhejiang Province, Hangzhou Medical College, Hangzhou, China.
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