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ORIGINAL RESEARCH article
Front. Surg.
Sec. Orthopedic Surgery
Volume 11 - 2024 |
doi: 10.3389/fsurg.2024.1387351
Knowledge mapping and bibliometric analysis of medical knee magnetic resonance imaging for knee osteoarthritis (2004-2023)
Provisionally accepted- Henan University of Chinese Medicine, Zhengzhou, China
Objectives: Magnetic resonance imaging (MRI) is increasingly used to detect knee osteoarthritis (KOA). In this study, we aimed to systematically examine the global research status on the application of medical knee MRI in the treatment of KOA, analyze research hotspots, explore future trends, and present results in the form of a knowledge graph.The Web of Science core database was searched for studies on medical knee MRI scans in patients with KOA between 2004 and 2023. CiteSpace, SCImago Graphica, and VOSviewer were used for the country, institution, journal, author, reference, and keyword analyses.Results: A total of 2,904 articles were included. The United States and Europe are leading countries.Boston University is the main institution. Osteoarthritis and cartilage is the main magazine. The most frequently cocited article was "Radiological assessment of osteoarthrosis." Guermazi A was the author with the highest number of publications and total references. The keywords most closely linked to MRI and KOA were "cartilage," "pain," and "injury."The application of medical knee MRI in KOA can be divided into the following parts: 1). MRI was used to assess the relationship between the characteristics of local tissue damage and pathological changes and clinical symptoms. 2).The risk factors of KOA were analyzed by MRI to determine the early diagnosis of KOA. 3). MRI was used to evaluate the efficacy of multiple interventions for KOA tissue damage (e.g., cartilage defects, bone marrow edema, bone marrow microfracture, and subchondral bone remodeling). Artificial intelligence, particularly deep learning, has become the focus of research on MRI applications for KOA.
Keywords: Bibliometric, knee osteoarthritis, Magnetic Resonance Imaging, knowledge graph, Citespace, VOSviewer
Received: 21 Feb 2024; Accepted: 29 Aug 2024.
Copyright: © 2024 Chen, Xu, zhou, Wang, LI, GUO and Zhou. 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:
Juntao Chen, Henan University of Chinese Medicine, Zhengzhou, China
Yunfeng Zhou, Henan University of Chinese Medicine, Zhengzhou, China
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