Wilson Clare M, Wong Karen, Ng Jeffery, Cocker Kenneth D, Ells Anna L, Fielder Alistair R
Department of Visual Science, UCL Institute of Ophthalmology, University College London, UK.
J AAPOS. 2012 Jun;16(3):223-8. doi: 10.1016/j.jaapos.2011.11.015.
To evaluate vessel selection methods to distinguish between eyes with and without retinopathy of prematurity (ROP) and between different stages of ROP when quantifying the associated vessel changes in width and tortuosity semiautomatically from digital retinal images.
Color digital images from 75 infants screened for ROP were cropped to a standardized diameter of 240 pixels and evaluated by semiautomated vessel analysis software, Computer-Aided Image Analysis of the Retina (CAIAR), to measure retinal vessel width and tortuosity. Two methods of vessel selection were used: (1) clinical observer selecting the most prominent arteriole or venule in each retinal quadrant (4-vessel analysis) and then separately the 4 most prominent arterioles and venules from each quadrant (8-vessel analysis); (2) CAIAR selecting, regardless of retinal quadrant, the 4 widest or most tortuous arterioles or venules. Selected vessels were measured by CAIAR for tortuosity and width.
When comparing ROP stages, whether observer or CAIAR selected and whether 4 or 8 vessels were analyzed, we found that arteriolar tortuosity was significantly greater with advancing ROP stage for stage 0 versus stage 2; stage 0 or 1 versus stage 3; stages 1+2 combined versus stage 3; and stage 0 versus 1+2+3 combined (P < 0.01). Venular tortuosity was significantly greater with advancing ROP stage for stage 0 versus stage 3 and stage 0 versus stages 1 and 2+3 combined (P < 0.01). Width parameters did not help us to distinguish between stages.
Distinguishing between arterioles and venules is not necessary to differentiate stage 0 ROP from stage 2 or 3 ROP when one is using CAIAR. Tortuosity shows more promise than width at providing a reliable vessel parameter for distinguishing between eyes without and with ROP.
当从数字视网膜图像中半自动定量分析相关血管宽度和迂曲度的变化时，评估血管选择方法，以区分有无早产儿视网膜病变（ROP）的眼睛以及ROP的不同阶段。
对75名接受ROP筛查的婴儿的彩色数字图像进行裁剪，使其标准化直径为240像素，并通过半自动血管分析软件视网膜计算机辅助图像分析（CAIAR）进行评估，以测量视网膜血管宽度和迂曲度。使用了两种血管选择方法：（1）临床观察者在每个视网膜象限中选择最突出的小动脉或小静脉（四血管分析），然后分别从每个象限中选择4条最突出的小动脉和小静脉（八血管分析）；（2）CAIAR无论视网膜象限如何，选择4条最宽或最迂曲的小动脉或小静脉。通过CAIAR测量所选血管的迂曲度和宽度。
在比较ROP阶段时，无论观察者还是CAIAR选择，也无论分析4条还是8条血管，我们发现，对于0期与2期；0期或1期与3期；1 + 2期合并与3期；以及0期与1 + 2 + 3期合并，随着ROP阶段的进展，小动脉迂曲度显著增加（P < 0.01）。对于0期与3期以及0期与1期和2 + 3期合并，随着ROP阶段的进展，小静脉迂曲度显著增加（P < 0.01）。宽度参数无助于我们区分不同阶段。
使用CAIAR时，区分小动脉和小静脉对于区分0期ROP与2期或3期ROP并非必要。在提供区分有无ROP眼睛的可靠血管参数方面，迂曲度比宽度更有前景。
