EyeArt Accuracy Results Published in British Journal of Ophthalmology

Source: EyeArt

Eyenuk announced that the British Journal of Ophthalmology published the research paper titled “Diagnostic Accuracy of Diabetic Retinopathy Grading by An Artificial Intelligence-Enabled Algorithm Compared with a Human Standard for Wide-Field True-Colour Confocal Scanning and Standard Digital Retinal Images.” According to this independent research paper with authors from the Moorfields Eye Hospital NHS Foundation Trust, the University College London Institute of Ophthalmology, and the Homerton University Hospital NHS Foundation Trust, Eyenuk’s EyeArt AI Eye Screening System achieved 92%-100% sensitivity in diabetic retinopathy (DR) detection with multiple retinal imaging platforms.

A total of consecutive 1,257 patients attending annual diabetic eye screening in the UK were included in the study. The EyeArt System processed images acquired by CenterVue’s EIDON platform with state-of-the-art wide-field true-color confocal scanning technology, as well as images acquired by standard cameras in the English National Diabetic Eye Screening Programme (NDESP). The reference standard for analysis was the human grade of standard NDESP images carried out according to NDESP protocol. With EIDON images, the EyeArt System achieved sensitivities of 92.27% for any retinopathy, 99% for vision-threatening retinopathy, and 100% for proliferative retinopathy. Corresponding EyeArt sensitivities for NDESP images were 92.26% for any retinopathy, 100% for vision-threatening retinopathy and 100% for proliferative retinopathy.

This study was conducted without any involvement by Eyenuk.

“All processing of the screening episodes was performed by the research team. The vendor was not allowed access to the software or to the data set during the study period,” authors wrote in the publication. “With this [impressive] performance, if the [EyeArt] software were to be hypothetically deployed as a part of the English NDESP, the EyeArt could reduce the need to grade R0M0 by half when using EIDON images and by almost two-thirds when using the NDESP images, a considerable workload reduction.”

“Validation results from the world’s leading diabetic retinopathy screening program once again confirm EyeArt System’s strong diagnostic accuracy and its potential to significantly reduce human workload for DR screening,” Kaushal Solanki, PhD, Founder and CEO of Eyenuk, said in a company news release. “We are equally excited to learn that the EyeArt System is shown to be accurate and highly sensitive when used to analyze EIDON images for diabetic retinopathy screening per the English NDESP protocol. True-color wide-field confocal scanning is a novel technology, and we are confident that EyeArt performance can be further optimized for this exciting imaging innovation.”

The EyeArt AI Eye Screening System provides fully automated DR screening, including retinal imaging, DR grading on international standards and immediate reporting, in a single office visit during a diabetic patient’s regular exam. Once the patient’s fundus images have been captured and submitted to the EyeArt AI System, the DR screening results are available in a PDF report in less than 60 seconds.


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