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Characteristics of a Large Database of Healthy Eyes From Optometry Practices: Implications for a Real-World Reference
Donald C Hood1,2, Mary Durbin3, Sol La Bruna4
1Bernard and Shirlee Brown Glaucoma Research Laboratory, Department of Ophthalmology, Edward S. Harkness Eye Institute, Columbia University Irving Medical Center, New York, NY, USA.
Translational Vision Science & Technology
|October 3, 2024
Summary
A new, larger real-world reference database (RW-RDB) of healthy eyes from optometry practices shows similar characteristics to a commercial database but offers narrower error bands for greater accuracy in optical coherence tomography (OCT) analysis.
Area of Science:
- Ophthalmology
- Medical Imaging
- Data Science
Background:
- Optical coherence tomography (OCT) is crucial for diagnosing eye conditions.
- Reference databases (RDBs) of healthy eyes are essential for accurate OCT interpretation.
- Existing commercial RDBs may have limitations in size and demographic representation.
Purpose of the Study:
- To compare a real-world reference database (RW-RDB) of healthy eyes from optometry practices with a commercial reference database (RDB).
- To evaluate the characteristics and potential advantages of a larger, real-world OCT database.
Main Methods:
- OCT scans from 4932 individuals (4.9K RW-RDB) with healthy eyes were collected from 10 optometry practices.
- The 4.9K RW-RDB was compared to a commercial RDB of 398 eyes.
- Key parameters including retinal nerve fiber layer (RNFL) and ganglion cell layer (GCL) thickness were analyzed.
Main Results:
- The 4.9K RW-RDB and commercial RDB showed similar characteristics and population profiles.
- Minor differences (<1.5%) were observed in fovea-to-disc distance and global circumpapillary RNFL thickness.
- The larger 4.9K RW-RDB demonstrated substantially narrower error bands on quantile regression lines (QRLs).
Conclusions:
- The large-scale 4.9K RW-RDB is comparable to commercial RDBs but offers improved accuracy due to narrower error bands.
- This larger RW-RDB can enhance the characterization of healthy eyes for clinical diagnosis and trials.
- Further research can leverage this RW-RDB to improve AI models and understand ocular health patterns.
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