Deep learning approach analyzes vision loss in Stargardt disease
2022
National Eye Institute, Bethesda, USA
Stargardt disease (ABCA4-associated retinopathy) is the most common form of macular degeneration in adolescence, affecting the centre of the retina, the macula. It leads to progressive loss of central visual acuity. Here, using patient data (optical coherence tomography of the eyes), the researchers demonstrated a Deep Learning-based method for characterizing photoreceptor degeneration over time in ABCA4-associated retinopathy. This approach allowed fully automated assessment of the progression of conventional biomarkers (e.g., ETDRS-based analysis of photoreceptor laminae thinning) and contour line-based analysis of photoreceptor degeneration over time. In addition, the age of loss of light-sensing cells was shown to depend on genotype, and estimates were provided for 31 variants, including 16 variants that have not previously been quantitatively analyzed for clinical severity.
Photoreceptor degeneration in ABCA4-associated retinopathy and its genetic correlates
Brett G Jeffrey, Brian P Brooks
Added on: 02-03-2022
[1] https://insight.jci.org/articles/view/155373[2] https://www.technologynetworks.com/informatics/news/deep-learning-approach-analyzes-vision-loss-in-stargardt-disease-357916
