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ORIGINAL RESEARCH article

Front. Aging Neurosci.
Sec. Parkinson’s Disease and Aging-related Movement Disorders
Volume 16 - 2024 | doi: 10.3389/fnagi.2024.1455562

Bibliometric analysis of global research trends in magnetic resonance imaging studies of substantia nigra in Parkinson's disease (2001-2024)

Provisionally accepted
Mei Jiang Mei Jiang 1Xu Deng Xu Deng 1Zixiong Qiu Zixiong Qiu 1Jie Li Jie Li 1Zifan Song Zifan Song 2Xiaoshuai Chen Xiaoshuai Chen 1Ruiqi Chen Ruiqi Chen 1Xianzhi Huang Xianzhi Huang 1Xiao-Jun Cui Xiao-Jun Cui 1*Yuan Fu Yuan Fu 1*
  • 1 Guangdong Medical University, Zhanjiang, China
  • 2 School of Sports Health, Guangdong Sports Vocational and Technical College, Guangzhou, China

The final, formatted version of the article will be published soon.

    Background: Parkinson's disease (PD) is a globally prevalent neurodegenerative disorder, primarily characterized by muscle rigidity, resting tremor, and bradykinesia. The incidence of PD is rapidly escalating worldwide. Numerous studies have been conducted on the application of magnetic resonance imaging (MRI) in investigating the substantia nigra (SN) in PD patients. However, to date, no bibliometric analysis has been performed on this specific research area. Therefore, this study aimed to provide a comprehensive analysis of the current status in MRI research on the SN in PD patients.: MRI study records related to the SN in PD patients from 2001 to 2024 were searched by using the Web of Science Core Collection (WOSCC) database and then the CiteSpace and VOSviewer were used to conduct bibliometric analysis. Results: Our analysis found that the number of published articles related studies on MRI of the SN in PD showed an overall upward trend over the past decade, in which Lehericy, Stephane, Du, Guangwei, and Huang, Xuemei are the top three authors with the most articles. Additionally, USA, China and Germany are the main contributors to MRI studies of SN in PD.

    Keywords: Parkinson's disease, Substantia Nigra, Magnetic Resonance Imaging, bibliometric analysis, Citespace, VOSviewer

    Received: 27 Jun 2024; Accepted: 22 Aug 2024.

    Copyright: © 2024 Jiang, Deng, Qiu, Li, Song, Chen, Chen, Huang, Cui and Fu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Xiao-Jun Cui, Guangdong Medical University, Zhanjiang, China
    Yuan Fu, Guangdong Medical University, Zhanjiang, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.