Accuracy of Artificial Intelligence in Estimating Best-Corrected Visual Acuity From Fundus Photographs in Eyes With Diabetic Macular Edema

A study published in the scientific journal JAMA Ophthalmology showed how artificial intelligence (AI) systems estimate best-corrected visual acuity (BCVA) from color fundus photographs of study participants undergoing treatment of diabetic macular edema.

Best-corrected visual acuity (BCVA) is a measure used to manage diabetic macular edema (DME). Using artificial intelligence (AI) to estimate BCVA from fundus images could help clinicians manage DME by reducing the personnel needed for refraction, the time presently required for assessing BCVA, or even the number of office visits if imaged remotely.

Analysis included 7185 macular color fundus images of the study and fellow eyes from 459 participants. Overall, the mean age was 62.2 (9.8) years, and 250 (54.5%) were male. The baseline BCVA score for the study eyes ranged from 73 to 24 letters.

This diagnostic/prognostic study found that the mean absolute error of AI-estimated BCVA from macular fundus photographs across all study visits and all treatment groups was within 10 letters of actual BCVA.

This investigation suggests AI can estimate BCVA directly from fundus photographs in patients with DME, without refraction or subjective visual acuity measurements, often within 1 to 2 lines on an ETDRS chart, supporting this AI concept if additional improvements in estimates can be achieved.

https://jamanetwork.com/journals/jamaophthalmology/article-abstract/2805759