Department of Ophthalmology and Visual Sciences, Illinois Eye and Ear Infirmary, University of Illinois at Chicago, Chicago, Illinois.
Department of Ophthalmology and Visual Sciences, Illinois Eye and Ear Infirmary, University of Illinois at Chicago, Chicago, Illinois; Department of Ophthalmology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Ophthalmol Retina. 2022 Dec;6(12):1122-1129. doi: 10.1016/j.oret.2022.05.024. Epub 2022 May 31.
To assess changes in retinopathy of prematurity (ROP) diagnosis in single and serial retinal images.
Cohort study.
Cases of ROP recruited from the Imaging and Informatics in Retinopathy of Prematurity (i-ROP) consortium evaluated by 7 graders.
Seven ophthalmologists reviewed both single and 3 consecutive serial retinal images from 15 cases with ROP, and severity was assigned as plus, preplus, or none. Imaging data were acquired during routine ROP screening from 2011 to 2015, and a reference standard diagnosis was established for each image. A secondary analysis was performed using the i-ROP deep learning system to assign a vascular severity score (VSS) to each image, ranging from 1 to 9, with 9 being the most severe disease. This score has been previously demonstrated to correlate with the International Classification of ROP. Mean plus disease severity was calculated by averaging 14 labels per image in serial and single images to decrease noise.
Grading severity of ROP as defined by plus, preplus, or no ROP.
Assessment of serial retinal images changed the grading severity for > 50% of the graders, although there was wide variability. Cohen's kappa ranged from 0.29 to 1.0, which showed a wide range of agreement from slight to perfect by each grader. Changes in the grading of serial retinal images were noted more commonly in cases of preplus disease. The mean severity in cases with a diagnosis of plus disease and no disease did not change between single and serial images. The ROP VSS demonstrated good correlation with the range of expert classifications of plus disease and overall agreement with the mode class (P = 0.001). The VSS correlated with mean plus disease severity by expert diagnosis (correlation coefficient, 0.89). The more aggressive graders tended to be influenced by serial images to increase the severity of their grading. The VSS also demonstrated agreement with disease progression across serial images, which progressed to preplus and plus disease.
Clinicians demonstrated variability in ROP diagnosis when presented with both single and serial images. The use of deep learning as a quantitative assessment of plus disease has the potential to standardize ROP diagnosis and treatment.
评估在单次和连续视网膜图像中早产儿视网膜病变（ROP）诊断的变化。
队列研究。
由成像和早产儿视网膜病变信息学（i-ROP）联合会评估的ROP 病例，共有 7 名评分者参与。
7 名眼科医生对 15 例 ROP 患者的单次和 3 张连续视网膜图像进行了检查，并将严重程度分为加号、预加号或无号。成像数据是在 2011 年至 2015 年期间常规 ROP 筛查中采集的，为每张图像建立了参考标准诊断。对 i-ROP 深度学习系统进行了二次分析，为每张图像分配一个血管严重程度评分（VSS），范围从 1 到 9，9 表示最严重的疾病。该评分已被证明与国际 ROP 分类相关。通过对每张连续和单次图像的 14 个标签进行平均，计算平均加号疾病严重程度，以减少噪声。
根据加号、预加号或无 ROP 定义 ROP 的严重程度。
超过 50%的评分者对连续视网膜图像的评估严重程度发生了改变，尽管存在很大的差异。Cohen's kappa 范围从 0.29 到 1.0，表明每个评分者的一致性从轻微到完美不等。在预加号病例中更常见到连续视网膜图像的评分变化。在诊断为加号疾病和无疾病的病例中，单次和连续图像之间的平均严重程度没有变化。ROP VSS 与专家分类的加号疾病范围具有良好的相关性，与模式类别的总体一致性（P=0.001）。VSS 与专家诊断的平均加号疾病严重程度相关（相关系数，0.89）。更激进的评分者往往会受到连续图像的影响，增加他们的评分严重程度。VSS 还显示出与连续图像中疾病进展的一致性，这些图像进展为预加号和加号疾病。
当提供单次和连续图像时，临床医生在 ROP 诊断方面表现出了差异。使用深度学习作为加号疾病的定量评估有可能使 ROP 诊断和治疗标准化。
