Quantification of Hypotony Maculopathy Using Spectral-Domain Optical Coherence Tomography

Area of Science:

• Ophthalmology
• Medical Imaging
• Computational Biology

Background:

• Macular hypotony, a complication of glaucoma surgery, causes retinal layer shape changes.
• Optical coherence tomography (OCT) is crucial for assessing hypotony maculopathy severity.
• Current clinical tools lack algorithms to quantify retinal folds in hypotony maculopathy.

Purpose of the Study:

• Introduce a simple, free, open-source algorithm to quantify macular hypotony.
• Develop a metric to assess hypotony maculopathy from OCT B-scans and volumes.
• Provide a tool for informed clinical decisions regarding hypotony maculopathy.

Main Methods:

• Segment Bruch's membrane complex from OCT images.
• Compute a smoothed version of Bruch's membrane to identify deviations from an ideal layer.
• Develop a quantitative metric based on these deviations for OCT B-scans and volumes.

Main Results:

• The algorithm's metric showed high correspondence with expert assessments (Pearson correlation > 0.8).
• Automated analysis demonstrated better agreement than inter-expert agreement.
• Demonstrated reliable results in a pilot study with patients exhibiting varying degrees of hypotony maculopathy.

Conclusions:

• The developed tool quantifies hypotony maculopathy, filling a clinical gap.
• Provides an easily interpretable metric to assist clinicians in evaluating symptom regression.
• Open-source implementation allows for future improvements and wider adoption.