Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Skeletal Radiol. 2023 Nov;52(11):2123-2135. doi: 10.1007/s00256-023-04311-w. Epub 2023 Mar 16.
Imaging plays a pivotal role in osteoarthritis research, particularly in epidemiological and clinical trials of knee osteoarthritis (KOA), with the ultimate goal being the development of an effective drug treatment for future prevention or cessation of disease. Imaging assessment methods can be semi-quantitative, quantitative, or a combination, with quantitative methods usually relying on software to assist. The software generally attempts image segmentation (outlining of relevant structures). New techniques using artificial intelligence (AI) or deep learning (DL) are currently a frequent topic of research. This review article provides an overview of the literature to date, focusing primarily on the current status of quantitative software-based assessment techniques of KOA using magnetic resonance (MR) imaging. We will concentrate on the imaging evaluation of three specific structural imaging biomarkers: bone marrow lesions (BMLs), meniscus, and synovitis consisting of effusion synovitis (ES) and Hoffa's synovitis (HS). A brief clinical and imaging background review of osteoarthritis evaluation, particularly relating to these three structural markers, is provided as well as a general summary of the software methods. A summary of the literature with respect to each KOA assessment method will be presented overall as well as with respect to each specific biomarker individually. Novel techniques, as well as future goals and directions using quantitative imaging assessment, will be discussed.
影像学在骨关节炎研究中起着至关重要的作用，特别是在膝关节骨关节炎（KOA）的流行病学和临床试验中，其最终目标是开发有效的药物治疗方法，以预防或停止疾病的发生。影像学评估方法可以是半定量、定量或两者的结合，定量方法通常依赖于软件来辅助。该软件通常尝试进行图像分割（相关结构的轮廓）。目前，使用人工智能（AI）或深度学习（DL）的新技术是研究的热门话题。本文综述了迄今为止的文献，主要关注基于磁共振成像（MR）的 KOA 定量软件评估技术的现状。我们将集中讨论三种特定的结构影像学生物标志物的影像学评估：骨髓病变（BMLs）、半月板和滑膜炎，包括渗出性滑膜炎（ES）和Hoffa 滑膜炎（HS）。还提供了骨关节炎评估的临床和影像学背景综述，特别是与这三个结构标志物相关的综述，以及软件方法的概述。将总体呈现每种 KOA 评估方法的文献综述，以及每种特定生物标志物的文献综述。还将讨论新技术以及使用定量成像评估的未来目标和方向。
