Yang WL, Zhou R, Zhang XJ, Jiang WC. Bibliometric analysis of original studies on stereoelectroencephalography from 1990 to 2023. World J Meta-Anal 2025; 13(1): 102634 [DOI: 10.13105/wjma.v13.i1.102634]
Corresponding Author of This Article
Wen-Cai Jiang, Department of Anesthesiology, Deyang People’s Hospital, No. 173 Taishan Road Section 1, Deyang 618000, Sichuan Province, China. jiang940724@163.com
Research Domain of This Article
Neuroimaging
Article-Type of This Article
Scientometrics
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Wei-Lin Yang, Xian-Jie Zhang, Wen-Cai Jiang, Department of Anesthesiology, Deyang People’s Hospital, Deyang 618000, Sichuan Province, China
Rui Zhou, Department of Anesthesiology and Perioperative Medicine, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China
Author contributions: Yang WL, Jiang WC and Zhou R conceived and designed the study; Yang WL and Zhou R participated in data processing and analysis; Yang WL, Jiang WC, Zhou R, Zhang XJ drafted the manuscript; Yang WL and Jiang WC contributed to data analysis and interpretation; Zhang XJ supervised the review of the study. All authors seriously revised and approved the final manuscript.
Conflict-of-interest statement: The authors declare that they have no conflicts of interest.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Received: October 24, 2024 Revised: January 4, 2025 Accepted: February 18, 2025 Published online: March 18, 2025 Processing time: 141 Days and 15.2 Hours
Abstract
BACKGROUND
Stereoelectroencephalography (SEEG) is a minimally invasive preoperative evaluation of drug-resistant focal epilepsies. Increasing preclinical data show that SEEG has tremendous diagnostic and therapeutic value for epilepsy. There are currently many studies on SEEG.
AIM
To summarize the development and application of SEEG.
METHODS
We conducted a bibliometric analysis of research on SEEG from 2019 to 2023. We obtained publications on SEEG from the Web of Science Core Collection (WoSCC) database. Excel, VOSviewer, and CiteSpace were responsible for the analyses. A variety of bibliographic elements were collected, including annual publications, authors, countries/regions, journals, keywords, etc.
RESULTS
A total of 691 publications were included in this study. Professor Fabrice Bartolomei of Timone Hospital in France was the most productive and influential author in the field of SEEG, whereas the authors from the United States were the leaders in general. In addition, we found that deep learning and source localization in SEEG have been popular in recent years.
CONCLUSION
This study provides a comprehensive analysis of SEEG research and highlights the growing interest in SEEG and its deep learning and source localization.
Core Tip: Stereoelectroencephalography (SEEG) is a popular issue recently. The United States, China, and France are in the leading place. Epilepsia, Clinical Neurophysiology, Journal of Neurosurgery, and Frontiers in Neurology are the most popular journals in this field. Epilepsy is still the primary clinical application of SEEG, while deep learning and source localization have strongly increased.
