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Related Concept Videos

Angle Closure Glaucoma: Treatment01:28

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Angle-closure glaucoma, or closed-angle glaucoma, is an eye condition where the iris bulges out and blocks the iridocorneal angle, resulting in a buildup of aqueous humor and increased intraocular pressure. Immediate medical attention is necessary due to the sudden onset of symptoms. The treatment for angle-closure glaucoma includes short-term and long-term approaches. Short-term treatment involves using eye drops like pilocarpine to lower intraocular pressure by increasing aqueous humor...
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Related Experiment Video

Updated: Nov 9, 2025

Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy oSLO and Optical Coherence Tomography OCT
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Towards 'automated gonioscopy': a deep learning algorithm for 360° angle assessment by swept-source optical coherence

Natalia Porporato1, Tin A Tun1, Mani Baskaran1

  • 1Singapore Eye Research Institute/Singapore National Eye Centre, Singapore.

The British Journal of Ophthalmology
|April 13, 2021
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Summary

A deep learning algorithm (DLA) accurately detects gonioscopic angle closure using 360° swept-source optical coherence tomography (SS-OCT) scans. This automated gonioscopy shows promise for efficient glaucoma screening.

Keywords:
angleglaucomaimaging

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Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Glaucoma diagnosis relies on assessing the anterior chamber angle.
  • Traditional gonioscopy can be subjective and time-consuming.
  • Swept-source optical coherence tomography (SS-OCT) offers detailed angle imaging.

Purpose of the Study:

  • To validate a deep learning algorithm (DLA) for automated 360° angle assessment using SS-OCT.
  • To evaluate the diagnostic performance of the DLA in detecting gonioscopic angle closure.

Main Methods:

  • A cross-sectional study analyzed 39,936 SS-OCT scans from 312 phakic subjects.
  • Gonioscopic angle closure was defined as non-visibility of the posterior trabecular meshwork in ≥180°.
  • A VGG-16 based DL algorithm was used for angle-closure detection, with gonioscopy as the reference standard.

Main Results:

  • The DLA achieved an Area Under the Curve (AUC) of 0.85 (95% CI: 0.80-0.90).
  • The algorithm demonstrated 83% sensitivity and 87% specificity for classifying gonioscopic angle closure.
  • Optimal classification occurred at a >35% circumferential angle closure cut-off.

Conclusions:

  • The DLA shows good diagnostic performance for gonioscopic angle closure detection on 360° SS-OCT.
  • This non-contact, automated approach may enhance glaucoma screening efficiency.
  • The algorithm's independence from scleral spur identification is a key advantage.