Validated System for Centralized Grading of Retinopathy of Prematurity Telemedicine Approaches to Evaluating Acute-Phase Retinopathy of Prematurity (e-ROP) Study

Validated System for Centralized Grading of Retinopathy of Prematurity Telemedicine Approaches to Evaluating Acute-Phase Retinopathy of Prematurity (e-ROP) Study
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DOI:
10.1001/jamaophthalmol.2015.0460
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发表时间:
2015-06-01
期刊:
影响因子:
8.1
通讯作者:
Ying, Gui-Shuang
Ying, Gui-Shuang
中科院分区:
医学1区
文献类型:
--
作者:
Daniel, Ebenezer;Quinn, Graham E.;Ying, Gui-Shuang

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重要性在使用阅读中心评估有早产儿视网膜病变(ROP)风险的婴儿的视网膜眼底图像的研究中,从数字图像分级的全面和高级培训中获得的可衡量的能力至关重要。认证为nonphysician训练有素的读者(TR)的细节尚未described. ObjectiveTo描述一个集中的系统分级ROP数字图像TR在远程医疗方法评价急性期视网膜病变的早产儿(e-ROP)Study.DESIGN,SETTING,AND PARTICIPANTS多中心观察性队列研究从2010年7月1日,2014年6月30日进行。TR由经验丰富的ROP专家进行培训,并在眼科医生阅读中心主任的监督下通过认证检测数字视网膜图像中的ROP形态。ROP阅读中心的开发具有标准硬件、安全的互联网接入和定制的图像查看软件以及电子评分表。制定了详细的分级方案。根据TR分级结果,计算机化算法确定2011年5月25日至2013年10月31日入组的出生体重小于1251 g的婴儿的数字图像中是否存在母亲保证的ROP(RW-ROP;定义为+疾病、I区ROP和3期或更差ROP)。独立的双重分级是由TRs与裁定的差异领域进行的阅读中心主任。曝光数字视网膜图像。主要结果和措施Intragrader和intergrader的变异性和监测的时间drift. ResultsFour TRs进行了严格的培训和认证。共对5520个图像集进行了双重分级,其中24.5%的图像集需要对至少1个RW-ROP组件进行裁定。对于单个RW-ROP组分,阳性疾病的裁定率为3.9%,I区ROP为12.4%,3期或更差ROP为16.9%。的加权。RW-ROP的综合一致性(n = 80个图像集)为0.72(95%CI,0.52-0.93),+疾病为0.57(95%CI,0.37-0.77),I区ROP为0.43(95%CI,0.24-0.63),3期或更差ROP为0.67(95%CI,0.47-0.88)。的加权。等级-重新等级一致性为0.77(95% CI,0.57-0.97)RW-ROP,0.87(95% CI,0.67-1.00)+疾病,0.70(95% CI,0.51-0.90),对于I区ROP和0.77(95%可信区间,0.57-0.97)。结论和相关性这些数据表明,用于培训和认证非医师在阅读中心主任的监督下对ROP图像进行分级的ROP系统可靠地检测潜在的严重ROP,具有良好的分级器内和分级器间一致性和最小的时间漂移。
IMPORTANCE Measurable competence derived from comprehensive and advanced training in grading digital images is critical in studies using a reading center to evaluate retinal fundus images from infants at risk for retinopathy of prematurity (ROP). Details of certification for nonphysician trained readers (TRs) have not yet been described.OBJECTIVE To describe a centralized system for grading ROP digital images by TRs in the Telemedicine Approaches to Evaluating Acute-Phase Retinopathy of Prematurity (e-ROP) Study.DESIGN, SETTING, AND PARTICIPANTS Multicenter observational cohort study conducted from July 1, 2010, to June 30, 2014. The TRs were trained by experienced ROP specialists and certified to detect ROP morphology in digital retinal images under supervision of an ophthalmologist reading center director. An ROP reading center was developed with standard hardware, secure Internet access, and customized image viewing software with an electronic grading form. A detailed protocol for grading was developed. Based on results of TR gradings, a computerized algorithm determined whether referral-warranted ROP (RW-ROP; defined as presence of plus disease, zone I ROP, and stage 3 or worse ROP) was present in digital images from infants with birth weight less than 1251 g enrolled from May 25, 2011, through October 31, 2013. Independent double grading was done by the TRs with adjudication of discrepant fields performed by the reading center director.EXPOSURE Digital retinal images.MAIN OUTCOMES AND MEASURES Intragrader and intergrader variability and monitoring for temporal drift.RESULTS Four TRs underwent rigorous training and certification. A total of 5520 image sets were double graded, with 24.5% requiring adjudication for at least 1 component of RW-ROP. For individual RW-ROP components, the adjudication rate was 3.9% for plus disease, 12.4% for zone I ROP, and 16.9% for stage 3 or worse ROP. The weighted. for intergrader agreement (n = 80 image sets) was 0.72 (95% CI, 0.52-0.93) for RW-ROP, 0.57 (95% CI, 0.37-0.77) for plus disease, 0.43 (95% CI, 0.24-0.63) for zone I ROP, and 0.67 (95% CI, 0.47-0.88) for stage 3 or worse ROP. The weighted. for grade-regrade agreement was 0.77 (95% CI, 0.57-0.97) for RW-ROP, 0.87 (95% CI, 0.67-1.00) for plus disease, 0.70 (95% CI, 0.51-0.90) for zone I ROP, and 0.77 (95% CI, 0.57-0.97) for stage 3 or worse ROP.CONCLUSIONS AND RELEVANCE These data suggest that the e-ROP system for training and certifying nonphysicians to grade ROP images under the supervision of a reading center director reliably detects potentially serious ROP with good intragrader and intergrader consistency and minimal temporal drift.