ISSN 1004-4140
    CN 11-3017/P

    CT虚拟单能量成像临床研究热点和趋势:中国知网数据的可视化分析

    The Hotspots and Trends of Computed Tomography Virtual Monoenergetic Imaging Clinical Research: A Visual Data Analysis of China National Knowledge Infrastructure

    • 摘要: 目的:通过对我国近五年发表的CT虚拟单能量成像(VMI)临床研究文献进行可视化分析,探讨我国VMI临床研究的热点和趋势。方法:检索中国知网数据库2020年1月1日至2025年2月28日收录的VMI临床研究文献,采用中国知网的分析功能、CiteSpace软件及VOSvier软件对发文时间、作者、机构、期刊以及关键词进行可视化分析。结果:本研究共纳入441篇文献。近5年的年发文量稳定在80篇以上。研究机构和作者主要集中在高等院校的附属医院,研究者之间的交流合作有限。去除检索词相关的关键词后,关键词频数排在前3位的为“图像质量”(52篇)、“辐射剂量”(17篇)和“金属伪影”(14篇),中心性排在前3位的为“图像质量”(0.23)、“肺腺癌”(0.08)、“影像组学”(0.08)。关键词聚类和突现词图谱提示,该领域新近出现的研究逐渐从VMI提升图像质量等技术验证转向具体疾病的诊断等临床应用。结论:我国VMI临床研究近5年来产出稳定,且发表于质量较高的期刊,但研究机构和作者之间的合作仍有待加强,研究热点逐渐从技术验证转向临床应用。

       

      Abstract: Objective: To visually analyze the literature on computed tomography virtual monoenergetic imaging (VMI) clinical research and discuss the hotspots and trends in this field. Methods: We searched VMI clinical research-related literature, published in China National Knowledge Infrastructure (CNKI) between 1 January 2020 and 28 February 2025, then visually analyzed the number of publications, authors, institutions, journals, and the keywords using CNKI as well as CiteSpace and VOSviewer software tools. Results: We included a total of 441 articles in this study. The number of publications was stable in recent five years at a level of more than 80 articles per year. The authors and institutions of the articles were mainly concentrated in affiliated medical college and university hospitals. The cooperation between authors and institutions remained limited. After search word exclusion, the co-occurrence maps of keywords revealed that the three most frequent keywords were "image quality" (52 articles), "radiation dosage" (17 articles), and "metal artifact" (14 articles), while the three most central keywords were "image quality" (0.23), "lung adenocarcinoma" (0.08), and "radiomics" (0.08). Keyword clustering and burst word mapping suggested that recent research in this field has gradually shifted from technical validation, (e.g., VMI-mediated image quality improvement) to clinical applications (e.g., specific disease diagnosis). Conclusion: In recent five years, VMI clinical research in China displays stable outputs and has been published in high-quality journals. However, collaboration among authors and institutions remains weak and needs to be strengthened. The research hotspots are gradually shifting from technical validation to clinical VMI applications.

       

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