Rapid Knee MRI Acquisition and Analysis Techniques for Imaging Osteoarthritis.
Rapid Knee MRI Acquisition and Analysis Techniques for Imaging Osteoarthritis.
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DOI：
10.1002/jmri.26991
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发表时间：
2020-11
期刊：
影响因子：
--
通讯作者：
Hargreaves BA
中科院分区：
文献类型：
--
作者：
Chaudhari AS;Kogan F;Pedoia V;Majumdar S;Gold GE;Hargreaves BA
膝关节骨关节炎（OA）是一种主要的残疾来源，没有已知的治疗或治愈。形态和成分MRI通常用于评估膝关节中的骨和软组织，以增强对OA病理生理学的理解。然而，由于成像采集和后处理工具缓慢且效率低下，因此将这些成像方法及其后续分析技术扩展到研究大型人群队列具有挑战性。这可能会在评估早期OA变化和评估新疗法的反应方面产生瓶颈。这篇综述文章的目的是强调最近的发展工具，以提高效率的膝关节MRI方法有用的研究OA。在这篇综述中讨论了用于形态和成分成像的高效MRI数据采集和重建工具、高效自动化图像分析工具以及进一步推动高效成像的硬件改进的进展。对于每个主题，我们讨论了当前的挑战以及未来缓解这些挑战的潜在机会。
Osteoarthritis (OA) of the knee is a major source of disability that has no known treatment or cure. Morphological and compositional MRI is commonly used for assessing the bone and soft tissues in the knee to enhance the understanding of OA pathophysiology. However, it is challenging to extend these imaging methods and their subsequent analysis techniques to study large population cohorts due to slow and inefficient imaging acquisition and postprocessing tools. This can create a bottle-neck in assessing early OA changes and evaluating the responses of novel therapeutics. The purpose of this review article is to highlight recent developments in tools for enhancing the efficiency of knee MRI methods useful to study OA. Advances in efficient MRI data acquisition and reconstruction tools for morphological and compositional imaging, efficient automated image analysis tools, and hardware improvements to further drive efficient imaging are discussed in this review. For each topic, we discuss the current challenges as well as potential future opportunities to alleviate these challenges.
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DOI：
10.1002/jmri.25508
发表时间：
2017-06
期刊：
Journal of magnetic resonance imaging : JMRI
影响因子：
--
作者：
Bao S;Tamir JI;Young JL;Tariq U;Uecker M;Lai P;Chen W;Lustig M;Vasanawala SS
通讯作者：
Vasanawala SS
影响因子：
3.3
作者：
Busse, Reed F.;Brau, Anja C. S.;Vu, Anthony;Michelich, Charles R.;Bayram, Ersin;Kijowski, Richard;Reeder, Scott B.;Rowley, Howard A.
通讯作者：
Rowley, Howard A.
影响因子：
3.3
作者：
Chaudhari AS;Fang Z;Kogan F;Wood J;Stevens KJ;Gibbons EK;Lee JH;Gold GE;Hargreaves BA
通讯作者：
Hargreaves BA
影响因子：
7
作者：
Baum, T.;Joseph, G. B.;Karampinos, D. C.;Jungmann, P. M.;Link, T. M.;Bauer, J. S.
通讯作者：
Bauer, J. S.
影响因子：
2.4
作者：
Bredbenner, Todd L.;Eliason, Travis D.;Potter, Ryan S.;Mason, Robert L.;Havill, Lorena M.;Nicolella, Daniel P.
通讯作者：
Nicolella, Daniel P.