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实时 OCT 引导和多模态成像监测兔眼视网膜下注射诱导的脉络膜新生血管。

Real-time OCT guidance and multimodal imaging monitoring of subretinal injection induced choroidal neovascularization in rabbit eyes.

机构信息

Department of Ophthalmology, Xiangya Hospital, Central South University, NO. 87 Xiangya Road, Kaifu District, Changsha, Hunan, 410008, PR China; Department of Ophthalmology and Visual Sciences, University of Michigan, 1000 Wall Street, Ann Arbor, MI, 48105, United States.

Department of Biomedical Engineering, University of Michigan, 2200 Bonisteel Blvd, Ann Arbor, MI, 48109, United States.

出版信息

Exp Eye Res. 2019 Sep;186:107714. doi: 10.1016/j.exer.2019.107714. Epub 2019 Jul 6.

Abstract

Choroidal neovascularization (CNV) is a major cause of vision loss that consists of abnormal growth of new blood vessels from the choroidal vasculature. High resolution in vivo imaging of animal models is essential to better elucidate and conduct research on CNV. This study evaluates a novel multimodal imaging platform combining optical coherence tomography (OCT) and photoacoustic microscopy (PAM). Using real-time OCT guidance subretinal injection to induce and multimodality imaging system to monitor CNV over time in rabbit eyes. The significance of our work lies in providing the optimal setting and conditions to make use of the OCT image guided system to improve the consistency and reproducibility of experimental results in subretinal injection induced CNV model in rabbits. For the first time, this study successfully demonstrated the dual-modality PAM-OCT system, without using exogenous contrast agents, can detect and visualize CNV in the rabbit eye with high resolution. This is promising system for diagnosing and monitoring CNV.

摘要

脉络膜新生血管(CNV)是导致视力丧失的主要原因,它由脉络膜血管系统的异常新血管生长引起。对动物模型进行高分辨率的体内成像对于更好地阐明和进行 CNV 研究至关重要。本研究评估了一种结合光学相干断层扫描(OCT)和光声显微镜(PAM)的新型多模态成像平台。该平台使用实时 OCT 引导下的视网膜下注射来诱导 CNV,并利用多模态成像系统随时间监测兔眼的 CNV。我们工作的意义在于提供最佳的设置和条件,以利用 OCT 图像引导系统来提高兔眼视网膜下注射诱导 CNV 模型中实验结果的一致性和可重复性。本研究首次成功地展示了双模态 PAM-OCT 系统,该系统无需使用外源性对比剂,即可高分辨率地检测和可视化兔眼中的 CNV。这是一种很有前途的 CNV 诊断和监测系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e82/6745701/55c7e3f15c1a/nihms-1535014-f0001.jpg

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