多发性硬化磁共振成像研究进展的文献计量学分析。

IF 1.1 4区医学 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Current Medical Imaging Reviews Pub Date : 2026-04-28 DOI:10.2174/0115734056439145260413194039

Xiaoxing Li, Dingbang Peng, Xiao Liang, Yao Wang, Chen Yang, Lin Wu, Fuqing Zhou

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引用次数: 0

摘要

导读：尽管磁共振成像在多发性硬化症研究中的应用呈指数级增长，但全面的文献计量学分析仍然很少。本研究绘制了25年全球MS-MRI趋势（2000-2024），以确定变革变化。方法：使用VOSviewer、Bibliometrix和CiteSpace对Web of Science核心馆藏中的8038篇出版物进行分析。机器学习聚类量化了协作网络，而双图覆盖和突发检测量化了跨学科桥梁和范式转换。结果：出版物增长呈现三个阶段：稳定（2005-2011年，+6.2%/年）、加速（2011-2021年，峰值480篇）和稳定（2022-2024年），最近的下降与诊断标准简化和人工智能驱动的整合有关。美国主导了总产量（24.2%），而英国主导了国际合作（44.2%）。中国对精神神经免疫学的独特关注与西方临床翻译的重点形成鲜明对比。最强的跨学科联系涉及神经病学/运动/眼科和分子/生物学/遗传学领域（Z-score = 5.3）。人工智能推动了范式转变，深度学习显示出最高的关键词爆发强度（413.27）。中心作者（如Massimo Filippi， Frederik Barkhof）将磁共振成像生物标志物与治疗创新联系起来。讨论：MS-MRI研究正在从描述性观察发展到人工智能驱动的精准医学。未来的成功依赖于将超高场核磁共振成像和多组学相结合的闭环模式。结论：该分析表明：(1)磁共振成像-人工智能-生物标志物的整合解决了临床-放射学悖论，实现了患者的动态分层；(2)超高场磁共振成像和多组学为精准神经学治疗个性化提供了路线图；(3)全球合作的协同效应可能使晚期多发性硬化症的治疗民主化。

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Web of Science Bibliometrics Analysis of Magnetic Resonance Imaging Research Advances in Multiple Sclerosis.

Introduction: Comprehensive bibliometric analysis of magnetic resonance imaging applications in multiple sclerosis research remains scarce despite exponential growth. This study maps 25-year global MS-MRI trends (2000-2024) to identify transformative shifts.

Methods: We analyzed 8,038 publications from the Web of Science Core Collection using VOSviewer, Bibliometrix, and CiteSpace. Machine learning clustering quantified collaboration networks, while dual-map overlays and burst detection quantified interdisciplinary bridges and paradigm shifts.

Results: Publication growth showed three phases: steady (2005-2011, +6.2%/year), accelerated (2011-2021, peak 480 publications), and stabilization (2022-2024), with recent decline linked to diagnostic criteria simplification and artificial intelligence-driven consolidation. The USA dominated total output (24.2%), while the UK led international collaboration (44.2% multi-country publications). China's unique focus on psychoneuroimmunology contrasts with Western clinical-translational priorities. The strongest interdisciplinary link connected Neurology/Sports/Ophthalmology and Molecular/Biology/Genetics fields (Z-score = 5.3). Artificial intelligence drove paradigm shifts, with deep learning showing the highest keyword burst strength (413.27). Central authors (e.g., Massimo Filippi, Frederik Barkhof) bridged magnetic resonance imaging biomarkers and therapeutic innovation.

Discussion: MS-MRI research is evolving from descriptive observations to AI-driven precision medicine. Future success relies on a closed-loop paradigm integrating ultra-high-field MRI and multi-omics.

Conclusion: This analysis reveals: (1) Magnetic resonance imaging-artificial intelligence-biomarker integration resolves clinical-radiological paradoxes, enabling dynamic patient stratification; (2) ultra-high-field magnetic resonance imaging and multi-omics provide a roadmap for precision neurology in therapy personalization; (3) global collaboration synergies may democratize advanced multiple sclerosis care.

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来源期刊

Current Medical Imaging Reviews 医学-核医学

CiteScore

2.60

自引率

0.00%

发文量

246

审稿时长

1 months

期刊介绍： Current Medical Imaging Reviews publishes frontier review articles, original research articles, drug clinical trial studies and guest edited thematic issues on all the latest advances on medical imaging dedicated to clinical research. All relevant areas are covered by the journal, including advances in the diagnosis, instrumentation and therapeutic applications related to all modern medical imaging techniques. The journal is essential reading for all clinicians and researchers involved in medical imaging and diagnosis.