A Deep Learning Approach for Automated Detection of Shallow Anterior Chamber Depth Based on Hidden Features of Fundus Photographs

The datasets are not redistributable to researchers other than those engaged in the Institutional Review Board-approved research collaborations with the B&VIIt Eye Center, South Korea. The datasets utilized during this study are not publicly available due to reasonable privacy and security concerns. Instead, a sample anonymized fundus photography data with shallow and deep ACD is available in the publicly accessible source. Note that this was not the exact data used in the research, but is a cleaned-up reproduction of our study's key insight.

In the current study, we analyzed the preoperative ocular data of healthy subjects who intended to undergo refractive surgery at the B&VIIT Eye Center from January 2015 to December 2016. All patients underwent preoperative measurements of best-corrected distance visual acuity and manifest refraction, slit-lamp examinations of the anterior segment. We used macula-centered fundus photographs containing posterior pole of eyes which were obtained during preoperative examination. Non-mydriatic fundus photographs were taken using two different retinal cameras including Maestro2 non-mydriatic retinal camera (Topcon Corporation, Tokyo, Japan) and CR-2 non-mydriatic retinal camera (Canon, Tokyo, Japan). Non-contact tonometry and pachymetry device (NT-530P; Nidek Co., Ltd., Aichi, Japan) was used to evaluate the intraocular pressure and central corneal thickness. All these measurements were carried out by trained medical workers and ophthalmologists.

The measurement of ACD was performed using a Pentacam HR Scheimpflug device (Oculus Optikgeräte GmbH, Wetzlar, Germany). Currently, there is the lack of universal definition of shallow ACD due to ethnic differences. In this study, we defined shallow ACD as an ACD measurement of 2.80 mm or lower according to the previous study (Malyugin et al., 2012). This criterion was adopted in both classification and feature map generation.

All fundus photographs were de-identified to share publicly.

Reference
Malyugin, B.E., Shpak, A.A., Pokrovskiy, D.F., 2012. Accommodative changes in anterior chamber depth in patients with high myopia. Journal of Cataract & Refractive Surgery 38, 1403–1407. https://doi.org/10.1016/j.jcrs.2012.04.030

本研究中的数据集不得向除与韩国B&VIIT眼科中心开展经机构审查委员会批准的研究合作之外的科研人员重新分发。由于合理的隐私和安全顾虑，本研究期间使用的数据集并未公开。取而代之的是，一份包含浅层和深层前房深度（ACD）的匿名化眼底摄影数据样本已可在公开渠道获取。请注意，这并非研究中所使用的确切数据，而是我们研究关键洞察的清洗重现。在当前研究中，我们分析了2015年1月至2016年12月期间有意在B&VIIT眼科中心接受屈光手术的健康受试者的术前眼科数据。所有患者均接受了最佳矫正距离视力、显性折射和眼前段裂隙灯检查。我们使用了包含眼底后极部的以黄斑为中心的眼底摄影，这些摄影是在术前检查期间获得的。非散瞳眼底摄影采用两种不同的视网膜相机进行拍摄，包括Topcon公司（东京，日本）的Maestro2非散瞳视网膜相机和佳能公司（东京，日本）的CR-2非散瞳视网膜相机。使用Nidek公司（爱知县，日本）的NT-530P非接触式眼压计和角膜厚度测量仪评估眼内压和中央角膜厚度。所有这些测量均由受过培训的医疗工作者和眼科医生执行。前房深度（ACD）的测量使用Pentacam HR Scheimpflug设备（Oculus Optikgeräte GmbH，韦茨拉尔，德国）进行。目前，由于种族差异，缺乏对浅层ACD的普遍定义。在本研究中，我们根据先前的研究（Malyugin等，2012年）将ACD测量值2.80毫米或以下定义为浅层ACD。这一标准被用于分类和特征图生成。所有眼底摄影均进行了去标识化处理，以便公开共享。

参考文献
Malyugin, B.E.，Shpak, A.A.，Pokrovskiy, D.F.，2012. 高度近视患者的前房深度调节变化。白内障与屈光手术杂志 38，1403–1407. https://doi.org/10.1016/j.jcrs.2012.04.030