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Rate and Predictors of Misclassification of Active Diabetic Macular Edema as Detected by an Automated Retinal Image

Lamberto La Franca1, Carola Rutigliani2, Lisa Checchin1

  • 1Department of Ophthalmology, IRCCS San Raffaele Scientific Institute, IRCCS Ospedale San Raffaele, University Vita-Salute, Via Olgettina 60, 20132, Milan, Italy.

Ophthalmology and Therapy
|April 8, 2024
PubMed
Abstract

Insights

This study evaluated the automated retinal image analysis system (ARIAS) for diagnosing diabetic macular edema (DME), finding it effective for screening new cases but less reliable for monitoring inactive DME.

Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Artificial Intelligence in Healthcare

Background:

  • Diabetic macular edema (DME) is a leading cause of vision loss in diabetic patients.
  • Accurate and timely diagnosis of active DME is crucial for effective treatment and vision preservation.
  • Automated retinal image analysis systems (ARIAS) offer potential for efficient screening and diagnosis.

Purpose of the Study:

  • To assess the sensitivity, specificity, and misclassification rate of ARIAS in detecting active DME.
  • To identify clinical and imaging factors associated with true and false positive diagnoses by ARIAS.

Main Methods:

  • A cross-sectional study involving 298 eyes of diabetic patients referred for DME evaluation.
  • Fundus photography analyzed by ARIAS (EyeArt V.2.1.0).
  • Active DME defined by spectral-domain optical coherence tomography (SD-OCT).

Main Results:

  • ARIAS demonstrated a sensitivity of 82.61% and specificity of 84.47% for active DME.
  • The overall misclassification rate was 16%.
  • Factors like younger age and shorter diabetes duration were linked to true positives, while longer diabetes duration and history of inactivated DME were associated with false positives.

Conclusions:

  • ARIAS is effective for screening treatment-naïve DME but less suitable for monitoring inactive DME.
  • Sensitivity was lower in older patients and those lacking DME-related fundus lesions.
  • Specificity decreased in patients with a history of inactivated DME.
Keywords:
Artificial intelligenceDiabetic macular edemaDiabetic retinopathySurveillance

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