An artificial intelligence system for the whole process from diagnosis to treatment suggestion of ischemic retinal diseases

Cell Rep Med. 2023 Oct 17;4(10):101197. doi: 10.1016/j.xcrm.2023.101197. Epub 2023 Sep 20.

Abstract

Ischemic retinal diseases (IRDs) are a series of common blinding diseases that depend on accurate fundus fluorescein angiography (FFA) image interpretation for diagnosis and treatment. An artificial intelligence system (Ai-Doctor) was developed to interpret FFA images. Ai-Doctor performed well in image phase identification (area under the curve [AUC], 0.991-0.999, range), diabetic retinopathy (DR) and branch retinal vein occlusion (BRVO) diagnosis (AUC, 0.979-0.992), and non-perfusion area segmentation (Dice similarity coefficient [DSC], 89.7%-90.1%) and quantification. The segmentation model was expanded to unencountered IRDs (central RVO and retinal vasculitis), with DSCs of 89.2% and 83.6%, respectively. A clinically applicable ischemia index (CAII) was proposed to evaluate ischemic degree; patients with CAII values exceeding 0.17 in BRVO and 0.08 in DR may be associated with increased possibility for laser therapy. Ai-Doctor is expected to achieve accurate FFA image interpretation for IRDs, potentially reducing the reliance on retinal specialists.

Keywords: artificial intelligence; diabetic retinopathy; fundus fluorescein angiography; ischemic retinal diseases; retinal vein occlusion.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Artificial Intelligence
  • Diabetic Retinopathy* / diagnostic imaging
  • Diabetic Retinopathy* / therapy
  • Fluorescein Angiography / methods
  • Humans
  • Ischemia / diagnosis
  • Ischemia / therapy
  • Retinal Vein Occlusion* / diagnosis
  • Retinal Vein Occlusion* / therapy