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2022 年骨关节炎年度回顾:影像学。

Osteoarthritis year in review 2022: imaging.

机构信息

Musculoskeletal Radiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Department of Radiology, Boston University School of Medicine, Boston, MA, USA; Department of Radiology, Universitätsklinikum Erlangen & Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.

出版信息

Osteoarthritis Cartilage. 2023 Aug;31(8):1003-1011. doi: 10.1016/j.joca.2023.03.005. Epub 2023 Mar 15.

Abstract

PURPOSE

This narrative review summarizes original research focusing on imaging in osteoarthritis (OA) published between April 1st 2021 and March 31st 2022. We only considered English publications that were in vivo human studies.

METHODS

The PubMed, Medline, Embase, Scopus, and ISI Web of Science databases were searched for "Osteoarthritis/OA" studies based on the search terms: "Radiography", "Ultrasound/US", "Computed Tomography/CT", "DXA", "Magnetic Resonance Imaging/MRI", "Artificial Intelligence/AI", and "Deep Learning". This review highlights the anatomical focus of research on the structures within the tibiofemoral, patellofemoral, hip, and hand joints. There is also a noted focus on artificial intelligence applications in OA imaging.

RESULTS

Over the last decade, the increasing trend of using open-access large databases has reached a plateau (from 17 to 37). Compositional MRI has had the most prominent use in OA imaging and its biomarkers have been used in the detection of preclinical OA and prediction of OA outcomes. Most noteworthy, there has been an accelerated rate of publications on the implications of artificial intelligence, used in developing prediction models and performing trabecular texture analysis, in OA imaging (from 17 to 154).

CONCLUSIONS

While imaging has maintained its key role in OA research, publication trends have shown an emphasis on the integration of AI. During the past year, MRI has maintained the highest prevalence in usage while US and CT remain as readily available modalities. Finally, there has been a notable uptake in the development and validation of AI techniques used to perform texture analysis and predict OA progression.

摘要

目的

本文对 2021 年 4 月 1 日至 2022 年 3 月 31 日期间发表的关于骨关节炎(OA)影像学的原始研究进行综述。我们仅考虑了基于以下检索词的英语出版物:“骨关节炎/OA”研究:“放射摄影术”、“超声/US”、“计算机断层扫描/CT”、“DXA”、“磁共振成像/MRI”、“人工智能/AI”和“深度学习”。本综述重点介绍了在研究中对胫骨股骨、髌股、髋关节和手部关节结构的解剖学关注点。还特别关注了人工智能在 OA 影像学中的应用。

方法

在 PubMed、Medline、Embase、Scopus 和 ISI Web of Science 数据库中搜索“骨关节炎/OA”研究,基于以下搜索词:“放射摄影术”、“超声/US”、“计算机断层扫描/CT”、“DXA”、“磁共振成像/MRI”、“人工智能/AI”和“深度学习”。本综述重点介绍了在研究中对胫骨股骨、髌股、髋关节和手部关节结构的解剖学关注点。还特别关注了人工智能在 OA 影像学中的应用。

结果

在过去十年中,使用开放获取大型数据库的趋势已经达到了一个高峰(从 17 篇增加到 37 篇)。结构 MRI 在 OA 影像学中的应用最为突出,其生物标志物已用于检测临床前 OA 和预测 OA 结局。最值得注意的是,人工智能在开发预测模型和进行小梁纹理分析方面的应用在 OA 影像学中的出版物数量呈加速增长趋势(从 17 篇增加到 154 篇)。

结论

尽管影像学在 OA 研究中一直保持着重要地位,但出版趋势表明越来越重视人工智能的整合。在过去的一年中,MRI 的使用率仍然最高,而 US 和 CT 仍然是易于使用的方式。最后,人们明显接受了开发和验证用于进行纹理分析和预测 OA 进展的人工智能技术。

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