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<p>While magnetic resonance imaging (MRI) has become indispensable in the clinical management of primary trigeminal neuralgia (PTN), a systematic analysis delineating the intellectual structure and evolving trends in this domain remains lacking. This study aims to map the research landscape through bibliometric analysis to identify developmental trajectory, key hotspots, and global research trends in MRI applications for PTN. We performed a bibliometric analysis of 290 scientific publications from the Web of Science Core Collection (2004-2024). Using VOSviewer and CiteSpace, we examined publication trends, geographic distribution, institutional contributions, collaborative networks, and thematic evolution. Publication output increased significantly since 2019. Although high-income countries (HICs) contributed the majority of publications (56.55%), upper-middle-income countries (UMICs)(particularly China) exhibited the most rapid growth and achieved the highest normalized citation impact (normalized total citations = 1.07). At the individual level, Professor Hodaie M held the highest academic influence (H-index = 6), while the Journal of Neurosurgery ranked first among journals in field-specific impact (H-index = 13). Keyword cluster analysis identified three major research themes: anatomical-surgical correlation, interventional management, and central pain mechanisms. The intellectual focus of the field has evolved from initial structural-anatomical investigations toward image-guided therapeutic applications and advanced studies of whole-brain microstructure, functional changes. MRI research in PTN is transitioning toward multimodal, quantitative, and translational approaches. Future research should prioritize multi-center collaborations, high-field MRI applications, and artificial intelligence-powered analysis to develop imaging biomarkers and personalized therapeutic strategies.</p>

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Mapping global research landscape and trends in magnetic resonance imaging applications for primary trigeminal neuralgia: a bibliometric analysis

  • 期刊论文

  • 发表日期：

    2025年10月16日

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  • Jingqi Jiang,
  • Jun Wang,
  • Liang Zhou,
  • Pengfei Zhang,
  • Shu Cui,
  • Longhui Lai,
  • Yingru Wang,
  • Zheng Cheng,
  • Laiyang Ma,
  • Suoshi Jing,
  • Jing Zhang

摘要

While magnetic resonance imaging (MRI) has become indispensable in the clinical management of primary trigeminal neuralgia (PTN), a systematic analysis delineating the intellectual structure and evolving trends in this domain remains lacking. This study aims to map the research landscape through bibliometric analysis to identify developmental trajectory, key hotspots, and global research trends in MRI applications for PTN. We performed a bibliometric analysis of 290 scientific publications from the Web of Science Core Collection (2004-2024). Using VOSviewer and CiteSpace, we examined publication trends, geographic distribution, institutional contributions, collaborative networks, and thematic evolution. Publication output increased significantly since 2019. Although high-income countries (HICs) contributed the majority of publications (56.55%), upper-middle-income countries (UMICs)(particularly China) exhibited the most rapid growth and achieved the highest normalized citation impact (normalized total citations = 1.07). At the individual level, Professor Hodaie M held the highest academic influence (H-index = 6), while the Journal of Neurosurgery ranked first among journals in field-specific impact (H-index = 13). Keyword cluster analysis identified three major research themes: anatomical-surgical correlation, interventional management, and central pain mechanisms. The intellectual focus of the field has evolved from initial structural-anatomical investigations toward image-guided therapeutic applications and advanced studies of whole-brain microstructure, functional changes. MRI research in PTN is transitioning toward multimodal, quantitative, and translational approaches. Future research should prioritize multi-center collaborations, high-field MRI applications, and artificial intelligence-powered analysis to develop imaging biomarkers and personalized therapeutic strategies.