Artificial intelligence for the detection of glaucoma with SD-OCT images: a systematic review and Meta-analysis
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View abstract on PubMed
Summary
This summary is machine-generated.Artificial intelligence (AI) demonstrates high accuracy in detecting glaucoma using spectral-domain optical coherence tomography (SD-OCT) images. Combining AI with expert clinicians enhances glaucoma diagnosis and patient outcomes.
Area Of Science
- Ophthalmology
- Medical Imaging
- Artificial Intelligence
Background
- Glaucoma is a leading cause of irreversible blindness worldwide.
- Early and accurate diagnosis is crucial for effective management and vision preservation.
- Spectral-domain optical coherence tomography (SD-OCT) provides detailed cross-sectional images of the optic nerve head and retinal nerve fiber layer.
Purpose Of The Study
- To systematically evaluate the diagnostic performance of artificial intelligence (AI) algorithms for glaucoma detection using SD-OCT images.
- To quantify the pooled sensitivity, specificity, and other diagnostic metrics of AI-based glaucoma detection models.
- To assess the potential of AI as an adjunct tool in improving glaucoma diagnosis.
Main Methods
- A comprehensive literature search was conducted across major electronic databases (PubMed, Embase, Scopus, etc.) for studies published before May 31, 2023.
- Twenty studies encompassing 51 AI models for glaucoma detection with SD-OCT were selected for systematic review and meta-analysis.
- Statistical analyses including meta-analysis, meta-regression, subgroup analysis, and bias assessment (using QUADAS-2 tool) were performed.
Main Results
- The meta-analysis revealed a pooled sensitivity of 0.91 and specificity of 0.90 for AI in glaucoma detection.
- The pooled positive likelihood ratio (PLR) was 8.79 and the negative likelihood ratio (NLR) was 0.11.
- The area under the curve (AUC) for AI models was high at 0.95, indicating excellent diagnostic accuracy, with no significant threshold effect observed.
Conclusions
- AI demonstrates high accuracy in detecting glaucoma when utilizing SD-OCT imaging.
- AI-based algorithms, particularly when used in conjunction with "doctor + artificial intelligence" approaches, show significant promise for improving the diagnostic accuracy of glaucoma.
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