Ophthalmology, Shimane University Faculty of Medicine, Izumo, Japan
Nidek Technologies Srl, Albignasego (PD), Italy.
Br J Ophthalmol. 2020 May;104(5):636-641. doi: 10.1136/bjophthalmol-2019-314320. Epub 2019 Aug 30.
To assess the pigmentation distribution in the iridocorneal angle using an established algorithm with gonioscopically obtained images.
Manual and automatically modified Scheie's pigmentation grading (ie, 0/I=0, II=1 and III/IV=2) of trabecular meshwork was performed using an established algorithm on the 75 open-angle eyes of 75 subjects obtained by automated gonioscopy. All images were collected at the Matsue Red Cross Hospital in 2016. The differences in the pigmentation density were compared statistically between the automated and manual techniques and among the four sectors (ie, inferior, superior, temporal and nasal) and the four quadrants.
There was substantial agreement between both grading methods (kappa value=0.70). There was no significant difference between the automated and manual grading in any sectors except for the superior (p=0.0004). The automated pigmentation grade was significantly (p<0.05) higher in the inferior sector (mean grade, 1.43) than in the others (mean grade, 0.480.76), and it was also significantly (p<0.05) higher in the inferior quadrant (mean grade, 3.56) than in the others (mean grade, 1.642.24). The findings were similar for manual grading.
The entire distribution of the pigmentation in the anterior chamber angle was classified successfully using the algorithm, and the automated versus manual grading comparison showed good agreement. The automated pigmentation grading scores in the inferior sector and inferior quadrant were significantly higher than in the others as previously reported. Similar findings also were seen for manual grading.
利用已建立的算法,评估眼前房角的色素分布。
在 2016 年于日本松江红十字医院收集的 75 名受试者的 75 只开角眼中,使用已建立的算法,对自动眼前房角镜获得的图像分别进行手动和自动改良的 Scheie 色素分级(即 0/I=0,II=1,III/IV=2)。所有图像均采用自动眼前房角镜收集。统计学比较自动和手动技术以及四个象限(即下方、上方、颞侧和鼻侧)之间色素密度的差异。
两种分级方法之间具有高度一致性(kappa 值=0.70)。除上方(p=0.0004)外,两种分级方法在任何象限均无显著差异。与其他象限相比,下方象限的自动色素分级(平均分级 1.43)显著较高(p<0.05),与其他象限相比,下方象限的自动色素分级(平均分级 1.43)也显著较高(p<0.05)。手动分级也有类似发现。
该算法成功地对前房角的整个色素分布进行了分类,自动分级与手动分级的比较显示出良好的一致性。与之前的报道一样,下方象限和下方象限的自动色素分级评分明显高于其他象限。手动分级也有类似发现。