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Updated: Sep 18, 2025

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Challenges for Opticians in Evaluating Small Pigmented Choroidal Lesions: Potential Support From the MelAInoma Deep

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The MelAInoma algorithm significantly improved the diagnostic accuracy of opticians and optometrists in identifying choroidal melanomas, reducing unnecessary referrals and enhancing early detection. This AI tool offers practical support for community eye care professionals.

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Area of Science:

  • Ophthalmology
  • Artificial Intelligence in Healthcare
  • Medical Diagnostics

Background:

  • Small pigmented choroidal lesions require accurate differentiation between benign nevi and malignant melanomas.
  • Opticians and optometrists play a crucial role in the initial triage of these lesions in community settings.
  • Current diagnostic methods, like the MOLES system, have limitations in specificity.

Purpose of the Study:

  • To assess the diagnostic accuracy of Swedish opticians/optometrists in triaging small pigmented choroidal lesions.
  • To determine if the MelAInoma deep learning algorithm enhances referral decisions for these lesions.

Main Methods:

  • Twenty-nine practitioners evaluated 25 fundus photographs (5 melanomas, 20 nevi) using the MOLES system.
  • Practitioners then re-evaluated the images with the assistance of the MelAInoma algorithm.
  • Diagnostic statistics (sensitivity, specificity, PPV, NPV, accuracy) were computed for both methods.

Main Results:

  • The MOLES system showed high sensitivity but low specificity (e.g., MOLES ≥1: 98% sensitivity, 17% specificity).
  • MelAInoma achieved 80% sensitivity and 90% specificity, with 88% overall accuracy.
  • Algorithm guidance quadrupled correct melanoma referrals and reduced false-positive referrals tenfold.

Conclusions:

  • Opticians/optometrists demonstrate high sensitivity but limited specificity in detecting choroidal melanomas.
  • The MelAInoma algorithm significantly improves specificity and reduces unnecessary referrals.
  • AI-powered tools like MelAInoma can streamline referrals and facilitate earlier uveal melanoma treatment.