Xu Heping, Koch Philippe, Chen Mei, Lau Annie, Reid Delyth M, Forrester John V
Department of Ophthalmology, University of Aberdeen, Institute of Medical Sciences, Foresterhill, Aberdeen, AB25 2ZD, UK.
Exp Eye Res. 2008 Oct;87(4):319-26. doi: 10.1016/j.exer.2008.06.012. Epub 2008 Jun 26.
Experimental autoimmune uveoretinitis (EAU), a widely used animal model of human posterior/pan-uveitis, is extremely valuable in allowing understanding of the pathogenesis of uveitis as well as in developing new treatments. Depending on the animal strain and immunization protocol used, the clinical course of EAU can be acute, severe and involving the anterior and posterior part of the eye, or chronic, mild and involving only the posterior part of the eye. Clinical signs of EAU can be examined by bio-microscopy. Using appropriate criteria EAU can be quantitatively evaluated clinically in living animals. However, correlation of research within different laboratories is difficult since clinical grading systems are subjective and susceptible to considerable variability. In this study, we have developed a recordable, image-based clinical grading system for the chronic models of EAU. Fundus images were taken from EAU mice using an endoscopic imaging system. Fundus changes were classified as (1) inflammatory changes (including optic disc inflammation, vasculitis and retinal tissue inflammation) and (2) retinal structural damage. Each element was scored separately based on the severity of the lesions, and the average score of the three inflammatory elements was used as the overall EAU clinical inflammation grade of the eye. The validity and reproducibility of the grading system was tested using a set of images scored independently in a masked manner by 5 individuals. The grading system proved robust, easy to use and reliable. We offer this image-based EAU clinical grading system as a useful quantitative evaluation method for clinical grading of the severity of inflammation in the chronic EAU model, in which the inflammation can be mild and mainly involves posterior part of the eye.
实验性自身免疫性葡萄膜视网膜炎(EAU)是一种广泛应用的人类后部/全葡萄膜炎动物模型,对于理解葡萄膜炎的发病机制以及开发新的治疗方法具有极高的价值。根据所使用的动物品系和免疫方案,EAU的临床病程可以是急性、严重的,累及眼的前部和后部;也可以是慢性、轻度的,仅累及眼的后部。EAU的临床体征可通过生物显微镜检查。使用适当的标准,可以在活体动物中对EAU进行临床定量评估。然而,由于临床分级系统具有主观性且易受显著变异性影响,不同实验室之间的研究相关性较差。在本研究中,我们为EAU慢性模型开发了一种基于图像的可记录临床分级系统。使用内镜成像系统从EAU小鼠获取眼底图像。眼底变化分为(1)炎症变化(包括视盘炎症、血管炎和视网膜组织炎症)和(2)视网膜结构损伤。根据病变的严重程度对每个要素分别评分,将三种炎症要素的平均评分用作该眼的整体EAU临床炎症分级。通过让5名人员以盲法独立对一组图像进行评分,测试了该分级系统的有效性和可重复性。该分级系统证明是稳健、易于使用且可靠的。我们提供这种基于图像的EAU临床分级系统,作为一种有用的定量评估方法,用于对慢性EAU模型中炎症严重程度进行临床分级,在该模型中炎症可能较轻且主要累及眼的后部。