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Osteoarthritis year in review 2023: Imaging

医学 磁共振成像 背景(考古学) 骨关节炎 临床试验 叙述性评论 概化理论 模态(人机交互) 医学物理学 放射科 人工智能 病理 心理学 计算机科学 重症监护医学 替代医学 古生物学 发展心理学 生物
作者
Mohamed Jarraya,Ali Guermazi,Frank W. Roemer
出处
期刊:Osteoarthritis and Cartilage [Elsevier]
卷期号:32 (1): 18-27 被引量:2
标识
DOI:10.1016/j.joca.2023.10.005
摘要

Purpose This narrative review summarizes the original research in the field of in vivo osteoarthritis (OA) imaging between 1 January 2022 and 1 April 2023. Methods A PubMed search was conducted using the following several terms pertaining to OA imaging, including but not limited to "Osteoarthritis / OA", "Magnetic resonance imaging / MRI", "X-ray" "Computed tomography / CT", "artificial intelligence /AI", "deep learning", "machine learning". This review is organized by topics including the anatomical structure of interest and modality, AI, challenges of OA imaging in the context of clinical trials, and imaging biomarkers in clinical trials and interventional studies. Ex vivo and animal studies were excluded from this review. Results Two hundred and forty-nine publications were relevant to in vivo human OA imaging. Among the articles included, the knee joint (61%) and MRI (42%) were the predominant anatomical area and imaging modalities studied. Marked heterogeneity of structural tissue damage in OA knees was reported, a finding of potential relevance to clinical trial inclusion. The use of AI continues to rise rapidly to be applied in various aspect of OA imaging research but a lack of generalizability beyond highly standardized datasets limit interpretation and wide-spread application. No pharmacologic clinical trials using imaging data as outcome measures have been published in the period of interest. Conclusions Recent advances in OA imaging continue to heavily weigh on the use of AI. MRI remains the most important modality with a growing role in outcome prediction and classification.
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