Purpose: To investigate the optimal frequency of imaging during follow-up to detect glaucoma progression by characterizing variability (noise) in neuroretinal rim area (RA) measured by Heidelberg Retina Tomograph (HRT; Heidelberg Engineering, Heidelberg, Germany).
Methods: RA noise was estimated from patient data and characterized by fitting theoretical distributions to the observed data. Multilevel regression was used to determine factors that significantly affect noise. Computer simulations of disease progression were performed by adding noise generated from the distribution derived from the observed data to the average rate of loss in RA estimated from longitudinal data. Rates of detection of disease progression were investigated for various progression rates, follow-up periods, and rates of imaging.
Results: Noise was not normally distributed and was best characterized by the hyperbolic distribution, which fit averages well while allowing for extreme values. Noise was greatly influenced by image quality, but age did not have a significant effect. Rates of detection improved for more frequent imaging, better quality images, and faster rates of disease progression.
Conclusions: Noise in HRT measurement of RA is well characterized by the hyperbolic distribution. Sensitivity of detection improves with more frequent testing, but if consistently poor-quality images are yielded for a patient, the probability of detection is low. Results from this work could be used to tailor individual follow-up patterns for patients with different rates of RA loss and image quality, especially in a clinical trial setting.