Dynamic Analysis of Retinal Image Quality Metrics for Predicting Manifest Refraction

Purpose

Modern autorefractors have demonstrated high accuracy and higher repeatability than manifest refraction in adults yet are not considered precise enough to substitute the gold standard, even in low-resource settings where there is a severe shortage of experienced refractionists. This work evaluates a novel approach that combines dynamic wavefront aberrometry data, acquired using an affordable portable autorefractor, with the analysis of retinal image quality metrics (IQMs) to predict subjective refraction.

Methods

56 subjects (34±14 years) were recruited for the analysis. Each participant underwent standard clinical refraction followed by a 10-second video acquisition using a QuickSee (QS) wavefront aberrometer (PlenOptika, USA). Shack-Hartmann images of each video for the right eye were processed to obtain Zernike coefficients up to the 4^th order. Coefficients obtained for each image were mathematically corrected with the closest sphero-cylindrical correction and the residual wavefront error was used to calculate the Point Spread Function (PSF) and IQMs (e.g., Strehl Ratio) describing some performance parameter of the corrected eye. Since each IQM is part of a dynamic sequence, it is possible to build a dynamic signal for each metric which contains information about fluctuations in image quality during the measurement. The final refraction is obtained as the average of the refractions corresponding to the images whose IMQs provided optimal performance.
To assess this method, we compared the results of the QS with those obtained by the new algorithm (using 6 different IQMs, Table 1) against the standard clinical refraction. Figures of merit were mean bias error (MBE), 95% limits of agreement (LOA), mean absolute error (MAE), and the percentages of agreement (0.25 and 0.5D thresholds) between refractions.