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计算机生成的马赛克照片对早产儿视网膜病变诊断和治疗的影响

Patel SN, Klufas MA, Douglas CE, et al.

期刊名称:JAMA Ophthalmology

卷期:2016年第134卷第11期

摘要

重要性:远程医疗正在成为早产儿视网膜病变临床护理越来越重要的组成部分,但是关于ROP远程医疗诊断的马赛克图像作用的信息很少。目的:检测电脑生成的马赛克图像对ROP诊断和治疗的潜在影响。设计、设置和参与者:在这项2011712日至2015921日的前瞻性队列研究中,收集了8个学术机构的ROP图像,ROP专家解读40ROP婴儿的广角视网膜图像集(20个图像集超过3个视野的单独眼底成像和20个电脑生成的马赛克图像)。所有专家独立回顾这40个图像集,为每组图像提供诊断和治疗计划。主要结果和措施:主要结果测量指标是ROP诊断敏感性和特异性,由专家提供的诊断通过共识参考标准诊断计算,由3位有经验的阅片者提供的眼底成像诊断联合眼底镜检查基础上的诊断共同决定。采用平均非权重κ统计分析专家为区域、阶段、外加疾病和类别等提供的平均中间级协议。结果:9ROP专家(45男)一直从事眼科工作平均10.8年(3-24年)同意参加。与多个单独图像诊断相比,马赛克图像诊断提供了第二阶段或者更差的疾病(95.9% vs 88.9%;差异, 7.0; 95% 可信区间, 3.510.5; P=.02)、外加疾病(85.7% vs 63.5%; 差异, 22.2; 95% 可信区间, 7.636.9; P=.02)和需要治疗的ROP84.4% vs 68.5%; 差异, 15.9; 95%可信区间, 0.831.7; P=.047)的诊断灵敏度。采用卡方检验,与多个单独图像相比,马赛克图像提高了外加疾病或无(0.54 vs 0.40; 平均卡方差异, 0.14; 95% 可信区间, 0.07 0.21; P=.004)、第三级或更差或无疾病(0.60 vs 0.52; 平均卡方差异, 0.06; 95% 可信区间, -0.060.18; P=.04)和2ROP或无(0.58 vs 0.51; 平均卡方差异, 0.07; 95%可信区间, 0.030.11; P=.04)的诊断中间协议一致性。浏览马赛克图像后,专家改变了180例中42例的治疗选择(23.3%; 95% 可信区间, 17.1%-29.5%)。结论和相关性:和多个单独成像相比,计算机生成的马赛克图像与专家进行特定ROP分类的基于图像基础的诊断精度的提高密切相关(例如,外加疾病,第二阶段疾病或者更差,需要治疗的ROP)。然而,这些发现是否具有普遍性尚不清楚,本研究结果可能与其它视网膜血管条件的马赛克分级无关。

Importance:Telemedicine is becoming an increasingly important component of clinical care for retinopathy of prematurity (ROP), but little information exists regarding the role of mosaic photography for ROP telemedicine diagnosis.Objective:To examine the potential effect of computer-generated mosaic photographs on the diagnosis and management of ROP.Design, Setting, and Participants:In this prospective cohort study performed from July 12, 2011, through September 21, 2015, images were acquired from ROP screening at 8 academic institutions, and ROP experts interpreted 40 sets (20 sets with individual fundus photographs with 3 fields and 20 computer-generated mosaic photographs) of wide-angle retinal images from infants with ROP. All experts independently reviewed the 40 sets and provided a diagnosis and management plan for each set presented.Main Outcomes and Measures:The primary outcome measure was the sensitivity and specificity of the ROP diagnosis by experts that was calculated using a consensus reference standard diagnosis, determined from the diagnosis of fundus photographs by 3 experienced readers in combination with the clinical diagnosis based on ophthalmoscopic examination. Mean unweighted κ statistics were used to analyze the mean intergrader agreement among experts for diagnosis of zone, stage, plus disease, and category.Results:Nine ROP experts (4 women and 5 men) who have been practicing ophthalmology for a mean of 10.8 years (range, 3-24 years) consented to participate. Diagnosis by the mosaic photographs compared with diagnosis by multiple individual photographs resulted in improvements in sensitivity for diagnosis of stage 2 disease or worse (95.9% vs 88.9%; difference, 7.0; 95% CI, 3.5 to 10.5; P=.02), plus disease (85.7% vs 63.5%; difference, 22.2; 95% CI, 7.6 to 36.9; P=.02), and treatment-requiring ROP (84.4% vs 68.5%; difference, 15.9; 95% CI, 0.8 to 31.7; P=.047). With use of the κ statistic, mosaic photographs, compared with multiple individual photographs, resulted in improvements in intergrader agreement for diagnosis of plus disease or not (0.54 vs 0.40; mean κ difference, 0.14; 95% CI, 0.07 to 0.21; P=.004), stage 3 disease or worse or not (0.60 vs 0.52; mean κ difference, 0.06; 95% CI, -0.06 to 0.18; P=.04), and type 2 ROP or not (0.58 vs 0.51; mean κ difference, 0.07; 95% CI, 0.03 to 0.11; P=.04). After viewing the mosaic photographs, experts altered their choice of management in 42 of 180 responses (23.3%; 95% CI, 17.1%-29.5%).Conclusions and Relevance:Compared with multiple individual photographs, computer-generated mosaic photographs were associated with improved accuracy of image-based diagnosis for certain categories (eg, plus disease, stage 2 disease or worse, and treatment-requiring ROP) of ROP by experts. It is unclear, however, whether these findings are generalizable, and the results of this study may not be relevant to mosaic grading of other retinal vascular conditions.


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