Validation of a novel functional test for assessing metamorphopsia using epiretinal membranes as a model

Abstract

Current tests for assessing metamorphopsia do not account for confounders such as perceptual filling-in and spatial redundancy, which affect its sensitivity and repeatability. This proof-of-concept study aimed to assess the performance of a novel laboratory-based psychophysical test (Line Sag Test, LST) which addresses these issues for quantification of metamorphopsia in idiopathic epiretinal membranes. The LST quantifies perpendicular metamorphopsia at three eccentricities (3°, 6°, and 9°) along eight meridians (45° steps). Metamorphopsia was assessed using the LST and Amsler grid and the hit rates of both tests for detecting metamorphopsia were compared. Normal metamorphopsia scores using the LST did not differ significantly from 0 and fell within one step-size (p = 0.500). The LST detected significantly more cases of metamorphopsia than the Amsler grid (14/21 versus 3/21) (p = 0.003). Similarly, significantly more cases of visual distortions in asymptomatic iERMs were detected using the LST than the Amsler grid (11/18 versus 0/18) (p = 0.008). The LST has a higher hit rate compared to the Amsler grid (67% versus 14%). This work demonstrates a psychophysically-robust functional test addressing perceptual confounders is more sensitive for quantifying and localising metamorphopsia in macular disease, particularly in asymptomatic disease.

Prediction of visual field defects from macular optical coherence tomography in glaucoma using cluster analysis

“…35,36 Data from all of the healthy participants and 25 of the glaucoma participants have been reported in part in previous investigations . [31][32][33][36][37][38][39] As per previous studies, [31][32][33]37 exclusion criteria for all cohorts included spherical equivalent refractive error outside the range of ±6.00 dioptres (D), astigmatism greater than 3.00 D and the presence of macula pathology in the included eye. Written consent to utilise clinical data for research purposes was obtained as per protocols approved by the University of New South Wales, Australia, Human Research Ethics Advisory Panel.…”

Measuring image distortions arising from age‐related macular degeneration: An Iterative Amsler Grid (IAG)

“…One such method called the line sag test (LST) is a computerized psychophysical test in which the observer is presented briefly with a curved line and asked to report whether the line appears to bulge inwards or outwards. 44 Using a staircase procedure, an algorithm neutralizes the amount of perceived sag by presenting a curve at the opposite direction to the response of the patient in the next trial. Comparing the results to those obtained with a traditional Amsler Grid, the authors concluded that the LST could capture more cases of deformations in patients with ERM.…”

“…Obtaining a reliable map of deformations having a potential in opening new horizons in developing technologies that would potentially increase the quality of life of patients with macular diseases, it is not surprising that there have been an increasing number of reports in computer‐based metamorphopsia measurement methodologies in the literature in the past few years. One such method called the line sag test (LST) is a computerized psychophysical test in which the observer is presented briefly with a curved line and asked to report whether the line appears to bulge inwards or outwards 44 . Using a staircase procedure, an algorithm neutralizes the amount of perceived sag by presenting a curve at the opposite direction to the response of the patient in the next trial.…”

“…This biharmonic spline interpolation method is based on an algorithm, where the aim is to find the minimum curvature surface that passes through a set of non‐uniformly spaced data points, in this case the intersection points corrected on the Amsler Grids. 44 In the higher order iterations, participants could continue with further and finer corrections by selecting a certain region on the updated image, which was presented at the end of each iteration. The positions of the intersection nodes on the interpolated grids were then fed into the incoming trial as the initial test point positions.…”

“…The data points were then fed into a biharmonic spline interpolation method implemented in Matlab 4 grid data function (with an option "v4," supporting two‐dimensional interpolation) to produce an updated image of the template grid with corrected values sitting on the test points. This biharmonic spline interpolation method is based on an algorithm, where the aim is to find the minimum curvature surface that passes through a set of non‐uniformly spaced data points, in this case the intersection points corrected on the Amsler Grids 44 . In the higher order iterations, participants could continue with further and finer corrections by selecting a certain region on the updated image, which was presented at the end of each iteration.…”