Critical Health, University Hospital of Coimbra, Coimbra, Portugal.
Ophthalmologica. 2011;226(4):191-7. doi: 10.1159/000330285. Epub 2011 Aug 25.
To assess a two-step automated system (RetmarkerSR) that analyzes retinal photographs to detect diabetic retinopathy for the purpose of reducing the burden of manual grading.
Anonymous images from 5,386 patients screened in 2007 were obtained from a nonmydriatic diabetic retinopathy screening program in Portugal and graded by an experienced ophthalmologist. RetmarkerSR earmarked microaneurysms, generating two outputs: 'disease' or 'no disease'. A second-step analysis, based on coregistration, combining two visits, was subsequently performed in 289 patients who underwent repeated examinations in 2008. The study was extended by analyzing all referrals considered urgent by the ophthalmologist from 2001 to 2007. Results were compared with those obtained by manual grading.
The RetmarkerSR classified in a first-step analysis 2,560 patients (47.5%) as having 'no disease' and 2,826 patients (52.5%) as having 'disease', thus requiring manual grading. RetmarkerSR detected all eyes considered urgent referrals. The two-step analysis further reduced the number of false-positive results by 26.3%, indicating an overall sensitivity of 95.8% and a specificity of 63.2%.
Automated grading of diabetic retinopathy may safely reduce the burden of grading patients in diabetic retinopathy screening programs. The novel two-step automated analysis system offers improved sensitivity and specificity over published automated analysis systems.
评估一种两步自动化系统（RetmarkerSR），该系统通过分析视网膜照片来检测糖尿病性视网膜病变，以减轻手动分级的负担。
从葡萄牙一项非散瞳性糖尿病视网膜病变筛查项目中获取了 5386 名筛查患者的匿名图像，并由一位经验丰富的眼科医生对这些图像进行分级。RetmarkerSR 标记微动脉瘤，并生成两个输出结果：“有病变”或“无病变”。随后，对 2008 年接受重复检查的 289 名患者进行了基于两次就诊的核心配准的第二步分析。通过分析 2001 年至 2007 年间所有被眼科医生认为是紧急转诊的患者，对该研究进行了扩展。将结果与手动分级的结果进行了比较。
RetmarkerSR 在第一步分析中，将 2560 名（47.5%）患者归类为“无病变”，将 2826 名（52.5%）患者归类为“有病变”，因此需要进行手动分级。RetmarkerSR 检测到了所有被认为是紧急转诊的患者。两步分析进一步减少了 26.3%的假阳性结果，总体敏感性为 95.8%，特异性为 63.2%。
糖尿病性视网膜病变的自动分级可以安全地减轻糖尿病视网膜病变筛查项目中对患者进行分级的负担。这种新的两步自动化分析系统提供了比已发表的自动化分析系统更高的敏感性和特异性。
