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基于吲哚菁绿的手部炎症性疾病荧光光学成像中发现的特征。

Features Found in Indocyanine Green-Based Fluorescence Optical Imaging of Inflammatory Diseases of the Hands.

作者信息

Gedat Egbert, Berger Jörn, Kiesel Denise, Failli Vieri, Briel Andreas, Welker Pia

机构信息

Faculty of Engineering and Natural Sciences, Wildau Technical University of Applied Sciences, 15745 Wildau, Germany.

Xiralite GmbH, 10115 Berlin, Germany.

出版信息

Diagnostics (Basel). 2022 Jul 22;12(8):1775. doi: 10.3390/diagnostics12081775.

DOI:10.3390/diagnostics12081775
PMID:35892489
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9331249/
Abstract

Rheumatologists in Europe and the USA increasingly rely on fluorescence optical imaging (FOI, Xiralite) for the diagnosis of inflammatory diseases. Those include rheumatoid arthritis, psoriatic arthritis, and osteoarthritis, among others. Indocyanine green (ICG)-based FOI allows visualization of impaired microcirculation caused by inflammation in both hands in one examination. Thousands of patients are now documented and most literature focuses on inflammatory arthritides, which affect synovial joints and their related structures, making it a powerful tool in the diagnostic process of early undifferentiated arthritis and rheumatoid arthritis. However, it has become gradually clear that this technique has the potential to go even further than that. FOI allows visualization of other types of tissues. This means that FOI can also support the diagnostic process of vasculopathies, myositis, collagenoses, and other connective tissue diseases. This work summarizes the most prominent imaging features found in FOI examinations of inflammatory diseases, outlines the underlying anatomical structures, and introduces a nomenclature for the features and, thus, supports the idea that this tool is a useful part of the imaging repertoire in rheumatology clinical practice, particularly where other imaging methods are not easily available.

摘要

欧洲和美国的风湿病学家越来越依赖荧光光学成像(FOI,Xiralite)来诊断炎症性疾病。这些疾病包括类风湿性关节炎、银屑病关节炎和骨关节炎等。基于吲哚菁绿(ICG)的FOI能够在一次检查中可视化双手因炎症导致的微循环受损情况。目前已有数千例患者的记录,并且大多数文献都聚焦于炎症性关节炎,这类疾病会影响滑膜关节及其相关结构,这使得它成为早期未分化关节炎和类风湿性关节炎诊断过程中的有力工具。然而,逐渐清楚的是,这项技术的潜力可能不止于此。FOI能够可视化其他类型的组织。这意味着FOI还可以辅助血管病、肌炎、胶原病和其他结缔组织疾病的诊断过程。这项工作总结了在炎症性疾病的FOI检查中发现的最显著的成像特征,概述了潜在的解剖结构,并引入了这些特征的命名法,从而支持了这样一种观点,即该工具是风湿病临床实践中成像方法的有用组成部分,特别是在其他成像方法不易获得的情况下。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9585/9331249/cc2f32d0c867/diagnostics-12-01775-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9585/9331249/372ef0cf652f/diagnostics-12-01775-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9585/9331249/492e330c99d6/diagnostics-12-01775-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9585/9331249/448fcbda6a20/diagnostics-12-01775-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9585/9331249/c6583b9f0147/diagnostics-12-01775-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9585/9331249/096f860eb901/diagnostics-12-01775-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9585/9331249/ebb521f23084/diagnostics-12-01775-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9585/9331249/cc2f32d0c867/diagnostics-12-01775-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9585/9331249/372ef0cf652f/diagnostics-12-01775-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9585/9331249/492e330c99d6/diagnostics-12-01775-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9585/9331249/448fcbda6a20/diagnostics-12-01775-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9585/9331249/c6583b9f0147/diagnostics-12-01775-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9585/9331249/096f860eb901/diagnostics-12-01775-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9585/9331249/ebb521f23084/diagnostics-12-01775-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9585/9331249/cc2f32d0c867/diagnostics-12-01775-g007.jpg

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Rheumatology (Oxford). 2022 Feb 2;61(2):636-647. doi: 10.1093/rheumatology/keab377.
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Innovative Imaging Technique for Visualization of Vascularization and Established Methods for Detection of Musculoskeletal Inflammation in Psoriasis Patients.
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Chem Biomed Imaging. 2024 May 2;2(5):384-397. doi: 10.1021/cbmi.4c00008. eCollection 2024 May 27.
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Fluorescence optical imaging feature selection with machine learning for differential diagnosis of selected rheumatic diseases.基于机器学习的荧光光学成像特征选择用于特定风湿性疾病的鉴别诊断
Front Med (Lausanne). 2023 Aug 21;10:1228833. doi: 10.3389/fmed.2023.1228833. eCollection 2023.
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