Using Small Samples to Evaluate Normative Reference Ranges for Retinal Imaging Measures

Area of Science:

• Ophthalmology
• Medical Imaging
• Biostatistics

Background:

• Retinal nerve fiber layer (RNFL) deviation maps are crucial for diagnosing optic neuropathies.
• Existing methods may misclassify healthy eyes due to inherent variability in RNFL thickness and shape.
• Early identification of false positives in normative databases is essential for accurate clinical interpretation.

Purpose of the Study:

• To investigate the cause of false-positive wedge defects in RNFL deviation maps of healthy eyes.
• To propose a method for early detection of such issues during normative database development.
• To improve the accuracy of RNFL analysis in clinical and research settings.

Main Methods:

• RNFL thickness was measured in 60 healthy young adults and 30 healthy older adults.
• Deviation maps were generated using RNFL shape variability data from subsets of participants.
• Between-subject variability in RNFL shape was assessed across different age groups and eyes.

Main Results:

• Significant between-subject variability in RNFL shape led to wedge patterns in deviation maps for a substantial percentage of healthy eyes (up to 58% in one cohort).
• These wedge patterns were observed across different groups of young and older healthy adults.
• The findings indicate that RNFL shape variability is a common cause of false positives.

Conclusions:

• RNFL thickness map evaluation in healthy individuals is sufficient to identify between-subject variability.
• This variability can manifest as wedge patterns in RNFL deviation maps, affecting many healthy eyes.
• The study highlights the need to account for RNFL shape variability in normative database construction to prevent misdiagnosis.