A computer-based method for evaluating the eye's ability to distinguish object details and shape in patients with age-related macular degeneration (AMD) could provide a more accurate way to assess the effectiveness of eye surgery or vision rehabilitation interventions with devices and training, according to a Canadian study.
The computer method could also vary low-, medium- and high-contrast illumination targets for testing spatial vision, which the authors say might be useful for early detection of AMD.
The tests are described in “Computer-Based Test to Measure Optimal Visual Acuity in Age-Related Macular Degeneration,” (http://www.iovs.org/cgi/content/full/48/10/4838) published in the October issue of Investigative Ophthalmology and Vision Science, a peer-reviewed monthly publication of the Association for Research in Vision and Ophthalmology (ARVO). The researchers are associated with Toronto Western Hospital's Vision Science Research Program, the Centre for Vision Research at Toronto's York University and the Department of Ophthalmology and Vision Sciences at the University of Toronto.
Authors Esther G. González, Luminita Tarita-Nistor, Samuel N. Markowitz and Martin J. Steinbach incorporated four features known to improve visual acuity into their computer-based evaluation method: high contrast; white optotypes (symbols, letters or numbers used in vision testing ) on a black background to reduce intraocular scatter; proportional layout to reduce the effects of crowding; and multiple optotypes to minimize the effects of fixation instability and to maximize the likelihood of optotype detection.
They conducted three experiments: the first measured the best-eye acuity of 24 AMD patients using the ETDRS charts and three versions of the Tumbling E acuity test; the second compared two White E optotype tests with the ETDRS in 14 AMD patients; and the third measured probability summation in 20 people with normal vision.
The authors concluded that a multiple-optotype, reversed-polarity test is most effective in estimating a patient's optimal visual acuity at baseline before vision rehabilitation interventions or surgery. Comparing the results of subsequent evaluations may help assess rehabilitation progress.