Shroff Sujani, Rao Divya P, Savoy Florian M, Shruthi S, Hsu Chao-Kai, Pradhan Zia S, Jayasree P V, Sivaraman Anand, Sengupta Sabyasachi, Shetty Rohit, Rao Harsha L
Department of Glaucoma, Narayana Nethralaya, Rajajinagar.
Remidio Innovative Solution Inc., Glen Allen, VA.
J Glaucoma. 2023 Apr 1;32(4):280-286. doi: 10.1097/IJG.0000000000002147. Epub 2022 Nov 28.
The offline artificial intelligence (AI) on a smartphone-based fundus camera shows good agreement and correlation with the vertical cup-to-disc ratio (vCDR) from the spectral-domain optical coherence tomography (SD-OCT) and manual grading by experts.
The purpose of this study is to assess the agreement of vCDR measured by a new AI software from optic disc images obtained using a validated smartphone-based imaging device, with SD-OCT vCDR measurements, and manual grading by experts on a stereoscopic fundus camera.
In a prospective, cross-sectional study, participants above 18 years (Glaucoma and normal) underwent a dilated fundus evaluation, followed by optic disc imaging including a 42-degree monoscopic disc-centered image (Remidio NM-FOP-10), a 30-degree stereoscopic disc-centered image (Kowa nonmyd WX-3D desktop fundus camera), and disc analysis (Cirrus SD-OCT). Remidio FOP images were analyzed for vCDR using the new AI software, and Kowa stereoscopic images were manually graded by 3 fellowship-trained glaucoma specialists.
We included 473 eyes of 244 participants. The vCDR values from the new AI software showed strong agreement with SD-OCT measurements [95% limits of agreement (LoA)=-0.13 to 0.16]. The agreement with SD-OCT was marginally better in eyes with higher vCDR (95% LoA=-0.15 to 0.12 for vCDR>0.8). Interclass correlation coefficient was 0.90 (95% CI, 0.88-0.91). The vCDR values from AI software showed a good correlation with the manual segmentation by experts (interclass correlation coefficient=0.89, 95% CI, 0.87-0.91) on stereoscopic images (95% LoA=-0.18 to 0.11) with agreement better for eyes with vCDR>0.8 (LoA=-0.12 to 0.08).
The new AI software vCDR measurements had an excellent agreement and correlation with the SD-OCT and manual grading. The ability of the Medios AI to work offline, without requiring cloud-based inferencing, is an added advantage.
基于智能手机的眼底相机上的离线人工智能（AI）与光谱域光学相干断层扫描（SD-OCT）得出的垂直杯盘比（vCDR）以及专家的手动分级显示出良好的一致性和相关性。
本研究的目的是评估使用经过验证的基于智能手机的成像设备从视盘图像中通过一种新的AI软件测量的vCDR与SD-OCT测量的vCDR以及专家在立体眼底相机上的手动分级之间的一致性。
在一项前瞻性横断面研究中，18岁以上（青光眼患者和正常人）的参与者接受了散瞳眼底评估，随后进行视盘成像，包括一张42度单视盘中心图像（Remidio NM-FOP-10）、一张30度立体视盘中心图像（Kowa非散瞳WX-3D台式眼底相机）以及视盘分析（Cirrus SD-OCT）。使用新的AI软件对Remidio FOP图像进行vCDR分析，3名接受过研究员培训的青光眼专家对Kowa立体图像进行手动分级。
我们纳入了244名参与者的473只眼睛。新AI软件得出的vCDR值与SD-OCT测量结果显示出高度一致性[95%一致性界限（LoA）=-0.13至0.16]。在vCDR较高的眼睛中，与SD-OCT的一致性略好（vCDR>0.8时，95% LoA=-0.15至0.12）。组内相关系数为0.90（95% CI，0.88 - 0.91）。AI软件得出的vCDR值与专家在立体图像上的手动分割显示出良好的相关性（组内相关系数=0.89，95% CI，0.87 - 0.91）（95% LoA=-0.18至0.11），在vCDR>0.8的眼睛中一致性更好（LoA=-0.12至0.08）。
新的AI软件vCDR测量结果与SD-OCT和手动分级具有极好的一致性和相关性。Medios AI能够离线工作，无需基于云的推理，这是一个额外的优势。
