Orugun Ayodele Jacob, Atima Mayor Orezime, Idakwo Ugbede, Komolafe Oyeronke, Oladigbolu Kehinde Kabir, Peter Elijah, Abdulsalam Halima Olufunmilola, Atima-Ayeni Emamoke, Dingwoke Emeka John, Khemlani Rohan, Nakayama Shintaro, Shimizu Eisuke, Balogun Emmanuel Oluwadare
ECWA Eye Hospital, Kano, Kano State, Nigeria.
Department of Ophthalmology, Faculty of Clinical Sciences, Ahmadu Bello University Teaching Hospital, Zaria, Kaduna State, Nigeria.
Eye (Lond). 2025 Apr;39(5):925-930. doi: 10.1038/s41433-024-03489-0. Epub 2024 Dec 2.
BACKGROUND/OBJECTIVES: Limited resources and staffing hinders efforts to reduce preventable blindness, especially in low- to middle-income countries. The slit-lamp examination (SLE), which is essential for ophthalmology practices, is often unavailable in primary and secondary eye care facilities due to the high costs and lengthy training required for operation. We conducted a cross-sectional, multicentre study exploring the potential for a smart eye camera (SEC; a tele-ophthalmology handheld device developed by OUI Inc., Japan) to address the limitations of the SLE.
SUBJECT/METHODS: Ocular diagnoses, visual acuity assessments and examinations of the eyes were performed independently using both a conventional SLE and a SEC. Four independent assessors (blind to the study) reviewed the images captured by the SEC and the SLE as administered by separate investigators. All analyses were performed using R version 4.2.2 for macOS at a 5% level of statistical significance.
The results of the image quality analysis demonstrated that the number of higher-quality images was significantly higher (p < 0.05) for the images captured using the SEC device compared to the SLE machine. Remarkably, up to 96% accuracy of diagnosis was recorded with SEC. Evaluation of diagnostic accuracy rates derived from images obtained from both machines revealed a degree of divergence in assessments among evaluators, yielding a Fleiss's Kappa value of 0.092. The sensitivity analysis for the SEC device revealed a reasonably strong capacity to correctly identify true positive cases, with an average sensitivity score of 90%.
The results of this study indicate that SEC can effectively evaluate anterior segment lesions in ophthalmology.
背景/目的:资源和人员有限阻碍了减少可避免失明的努力,尤其是在低收入和中等收入国家。裂隙灯检查(SLE)对眼科实践至关重要,但由于操作成本高且培训时间长,初级和二级眼科保健设施中往往无法进行。我们开展了一项横断面多中心研究,探讨智能眼相机(SEC;日本OUI公司开发的一种远程眼科手持设备)解决SLE局限性的潜力。
对象/方法:分别使用传统SLE和SEC独立进行眼部诊断、视力评估和眼部检查。四名独立评估人员(对研究不知情)审查了由不同调查人员操作的SEC和SLE所拍摄的图像。所有分析均使用适用于macOS的R 4.2.2版本,统计显著性水平为5%。
图像质量分析结果表明,与SLE机器相比,使用SEC设备拍摄的图像中高质量图像数量显著更多(p < 0.05)。值得注意的是,SEC的诊断准确率高达96%。对两台机器获取的图像诊断准确率的评估显示,评估人员之间的评估存在一定程度的差异,Fleiss卡方值为0.092。SEC设备的敏感性分析显示其正确识别真阳性病例的能力相当强,平均敏感性评分为90%。
本研究结果表明,SEC可有效评估眼科前段病变。