概要

体内 小鼠视网膜血管损伤读数以促进可重复性

Published: April 21, 2022
doi:

概要

在这里,我们提出了三种用于荧光素血管造影(FA)和光学相干断层扫描(OCT)图像的数据分析协议,用于视网膜静脉遮挡(RVO)的研究。

Abstract

眼科成像工具的进步为研究神经血管损伤动物模型的研究人员提供了前所未有的访问水平。为了正确利用这种更大的可翻译性,需要设计可重复的方法,从这些图像中提取定量数据。光学相干断层扫描 (OCT) 成像可以在微米分辨率下解析视网膜组织学,并揭示血管血流的功能差异。在这里,我们描绘了无创血管读数,用于在优化的视网膜静脉阻塞(RVO)小鼠模型中表征血管损伤后的病理损伤。这些读数包括视网膜形态的实时成像分析、毛细血管缺血的视网膜内层紊乱 (DRIL) 测量以及视网膜水肿和血管密度的荧光素血管造影测量。这些技术直接对应于临床上用于检查视网膜疾病患者的技术。标准化这些方法可以直接和可重复地比较动物模型与眼科疾病的临床表型,从而提高血管损伤模型的转化能力。

Introduction

神经血管疾病是导致缺血性中风的主要医疗保健问题,缺血性中风是导致死亡和发病的主要原因,以及导致视力丧失的视网膜血管疾病12。为了模拟神经血管疾病,我们采用了视网膜静脉阻塞(RVO)的小鼠模型。该模型是非侵入性的,利用与临床环境中用于检查视网膜血管疾病患者的体内成像技术类似的 体内 成像技术。因此,该模型的使用增加了使用该模型的研究的转化潜力。与所有小鼠模型一样,最大限度地提高模型的可重复性至关重要。

视网膜血管疾病是70岁以下人群视力丧失的主要原因。RVO是仅次于糖尿病视网膜病变第二常见的视网膜血管疾病3。RVO 的临床特征包括缺血性损伤、视网膜水肿和神经元丢失导致的视力丧失34。已经开发和改进了使用激光光凝主要血管的RVO小鼠模型,以复制在人类RVO567中观察到的关键临床病理。眼科成像的进步也允许复制用于人类的无创诊断工具,即荧光素血管造影(FA)和光学相干断层扫描(OCT)6。荧光素血管造影允许使用注射荧光素(一种小荧光染料89)来观察由于血液 – 视网膜屏障(BRB)的破坏以及视网膜中的血流动力学(包括闭塞部位)引起的泄漏。OCT成像允许获取视网膜的高分辨率横截面图像并研究视网膜层的厚度和组织10。对FA图像的分析历来主要是定性的,这限制了研究之间直接和可重复比较的潜力。最近,已经开发了许多用于量化OCT成像中层厚度的方法,尽管目前还没有标准化的分析协议,并且OCT图像采集的地点各不相同11。为了正确利用这些工具,需要标准化、定量和可复制的数据分析方法。在本文中,我们提出了三种这样的血管读数,用于评估RVO-荧光素渗漏,OCT层厚度和视网膜层紊乱的小鼠模型中的病理损伤。

Protocol

该协议遵循视觉和眼科研究协会(ARVO)关于在眼科和视力研究中使用动物的声明。啮齿动物实验由哥伦比亚大学机构动物护理和使用委员会(IACUC)批准和监测。 注意:对重约23g的2个月大的C57BL / 6J雄性小鼠进行成像。 1. 视网膜成像试剂的制备 注射荧光素溶液的制备。注意:荧光素对光非常敏感。避光,准备后不久使用。在…

Representative Results

这些分析方法允许量化FA和OCT成像捕获的视网膜病理。从中提取代表性数据的实验使用C57BL / 6J雄性小鼠,这些小鼠作为未受伤的对照或接受RVO程序并接受Pen1-XBir3治疗眼药水或Pen1-Saline载体滴眼液。RVO损伤模型涉及在尾静脉注射孟加拉玫瑰(一种光活化剂染料12)后,对麻醉小鼠每只眼睛的主要静脉进行激光照射(532 nm)。在距视神经中枢平均375μm的距离处传递三个激光脉冲以诱?…

Discussion

无创啮齿动物视网膜成像为研究病理学和开发干预措施提供了途径。以前的研究已经开发并优化了RVO的小鼠模型,限制了变异性并允许对小鼠视网膜中常见临床病理的可靠翻译5713眼科成像技术的发展进一步允许在实验动物中使用临床体内成像技术,如FA和OCT,从而能够将小鼠模型与人类疾病特征

開示

The authors have nothing to disclose.

Acknowledgements

这项工作得到了美国国家科学基金会研究生研究奖学金计划(NSF-GRFP)拨款DGE – 1644869(CKCO),国家眼科研究所(NEI)5T32EY013933(AMP),国家神经疾病和中风研究所(RO1 NS081333,R03 NS099920至CMT)和国防部陆军/空军(DURIP至CMT)的支持。

Materials

AK-Fluor 10% Akorn NDC: 17478-253-10 light-sensitive
Carprofen Rimadyl NADA #141-199 keep at 4 °C
GenTeal Alcon 00658 06401
Image J NIH
InSight 2D Phoenix Technology Group OCT analysis software
Ketamine Hydrochloride Henry Schein NDC: 11695-0702-1
Phenylephrine Akorn NDCL174478-201-15
Phoenix Micron IV Phoenix Technology Group Retinal imaging microscope
Phoenix Micron Meridian Module Phoenix Technology Group Laser photocoagulator software
Phoenix Micron Optical Coherence Tomography Module Phoenix Technology Group OCT imaging software
Phoenix Micron StreamPix Module Phoenix Technology Group Fundus imaging and acquisition targeting
Photoshop Adobe
Refresh Allergan 94170
Tropicamide Akorn NDC: 174478-102-12
Xylazine Akorn NDCL 59399-110-20

参考文献

  1. Tong, X., et al. The burden of cerebrovascular disease in the united states. Preventing Chronic Disease. 16, 180411 (2019).
  2. Nakahara, T., Mori, A., Kurauchi, Y., Sakamoto, K., Ishii, K. Neurovascular interactions in the retina: physiological and pathological roles. Journal of Pharmacological Sciences. 123 (2), 79-84 (2013).
  3. Jaulim, A., Ahmed, B., Khanam, T., Chatziralli, I. Branch retinal vein occlusion: epidemiology, pathogenesis, risk factors, clinical features, diagnosis, and complications. An update of the literature. Retina. 33 (5), 901-910 (2013).
  4. Ho, M., Liu, D. T. L., Lam, D. S. C., Jonas, J. B. Retinal vein occlusions, from basics to the latest treatment. Retina. 36 (3), 432-448 (2016).
  5. Zhang, H., et al. Development of a new mouse model of branch retinal vein occlusion and retinal neovascularization. Japanese Journal of Ophthalmology. 51 (4), 251-257 (2007).
  6. Ebneter, A., Agca, C., Dysli, C., Zinkernagel, M. S. Investigation of retinal morphology alterations using spectral domain optical coherence tomography in a mouse model of retinal branch and central retinal vein occlusion. PLoS One. 10 (3), 0119046 (2015).
  7. Fuma, S., et al. A pharmacological approach in newly established retinal vein occlusion model. Scientific Reports. 7, 43509 (2017).
  8. Cavallerano, A. Ophthalmic fluorescein angiography. Clinical Optometry. 5 (1), 1-23 (1996).
  9. Laatikainen, L. The fluorescein angiography revolution: a breakthrough with sustained impact. Acta Ophthalmologica Scandinavica. 82 (4), 381-392 (2004).
  10. Huang, D., et al. Optical coherence tomography. Science. 254 (5035), 1178-1181 (1991).
  11. Oberwahrenbrock, T., et al. Reliability of intra-retinal layer thickness estimates. PLoS One. 10 (9), 0137316 (2015).
  12. Avrutsky, M. I., et al. Endothelial activation of caspase-9 promotes neurovascular injury in retinal vein occlusion. Nature Communications. 11 (1), 3173 (2020).
  13. Colón Ortiz, C., Potenski, A., Lawson, J., Smart, J., Troy, C. Optimization of the retinal vein occlusion mouse model to limit variability. Journal of Visualized Experiments: JoVE. (174), e62980 (2021).
  14. Schmidt-Erfurth, U., et al. Guidelines for the management of retinal vein occlusion by the European society of retina specialists (EURETINA). Ophthalmologica. 242 (3), 123-162 (2019).
  15. Yoshimura, T., et al. Comprehensive analysis of inflammatory immune mediators in vitreoretinal diseases. PLoS One. 4 (12), 8158 (2009).
  16. Mezu-Ndubuisi, O. J. In vivo angiography quantifies oxygen-induced retinopathy vascular recovery. Optometry and Vision Science. 93 (10), 1268-1279 (2016).
  17. Hui, F., et al. Quantitative spatial and temporal analysis of fluorescein angiography dynamics in the eye. PLoS One. 9 (11), 111330 (2014).
  18. Berry, D., Thomas, A. S., Fekrat, S., Grewal, D. S. Association of disorganization of retinal inner layers with ischemic index and visual acuity in central retinal vein occlusion. Ophthalmology. Retina. 2 (11), 1125-1132 (2018).
  19. Nicholson, L., et al. Diagnostic accuracy of disorganization of the retinal inner layers in detecting macular capillary non-perfusion in diabetic retinopathy. Clinical & Experimental Ophthalmology. 43 (8), 735-741 (2015).
  20. Obrosova, I., Chung, S., Kador, P. Diabetic cataracts: mechanisms and management. Diabetes/Metabolism Research and Reviews. 26 (3), 172-180 (2010).
  21. Hegde, K., Henein, M., Varma, S. Establishment of the mouse as a model animal for the study of diabetic cataracts. Ophthalmic Research. 35 (1), 12-18 (2003).
  22. Takahashi, H., et al. Time course of collateral vessel formation after retinal vein occlusion visualized by OCTA and elucidation of factors in their formation. Heliyon. 7 (1), 05902 (2021).
  23. Haj Najeeb, B., et al. Fluorescein angiography in diabetic macular edema: A new approach to its etiology. Investigation Ophthalmology & Visual Science. 58 (10), 3986-3990 (2017).
  24. Alam, M., et al. Quantitative optical coherence tomography angiography features for objective classification and staging of diabetic retinopathy. Retina. 40 (2), 322-332 (2020).
  25. Uddin, M., Jayagopal, A., McCollum, G., Yang, R., Penn, J. In vivo imaging of retinal hypoxia using HYPOX-4-dependent fluorescence in a mouse model of laser-induced retinal vein occlusion (RVO). Investigation Ophthalmology & Visual Science. 58 (9), 3818-3824 (2017).
  26. Qiang, W., Wei, R., Chen, Y., Chen, D. Clinical pathological features and current animal models of type 3 macular neovascularization. Frontiers in Neuroscience. 15, 734860 (2021).
  27. Park, J., et al. Imaging laser-induced choroidal neovascularization in the rodent retina using optical coherence tomography angiography. Investigation Ophthalmology & Visual Science. 57 (9), 331 (2016).
  28. Chen, J., Qian, H., Horai, R., Chan, C., Caspi, R. Use of optical coherence tomography and electroretinography to evaluate retinal pathology in a mouse model of autoimmune uveitis. PLoS One. 8 (5), 63904 (2013).

Play Video

記事を引用
Chen, C. W., Potenski, A. M., Colón Ortiz, C. K., Avrutsky, M. I., Troy, C. M. In Vivo Vascular Injury Readouts in Mouse Retina to Promote Reproducibility. J. Vis. Exp. (182), e63782, doi:10.3791/63782 (2022).

View Video