Osteoarthritis year in review 2022: imaging

  • S. Demehri
    Address correspondence and reprint requests to: S. Demehri, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 601 N Caroline St, JHOC 5165, Baltimore, MD 21287, USA. Tel: 1-410-614-6179; Fax: 1-410-502-6454.
    Musculoskeletal Radiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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  • A. Kasaeian
    Musculoskeletal Radiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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  • F.W. Roemer
    Department of Radiology, Boston University School of Medicine, Boston, MA, USA

    Department of Radiology, Universitätsklinikum Erlangen & Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
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  • A. Guermazi
    Department of Radiology, Boston University School of Medicine, Boston, MA, USA
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Published:March 14, 2023DOI:



      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.


      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.


      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).


      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.


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