Extracting full information from OCT scans-signs of early age-related macular degeneration within inner retinal layers by local neighbourhood statistics. Part II: Results.

BACKGROUND AND

objectivesAssociations between the occurrence of early age related macular degeneration (AMD) and alterations in retinal layer thicknesses have been reported, based on classical processing of optical coherence tomography (OCT) data by noise removal and subsequent image segmentation. However, speckle noise within OCT data itself bears a substantial part of the total information. For this reason, we designed an omics-type approach for full exploitation of OCT data, which was able to identify signs of early AMD throughout the retina as a whole.

methodsA nested case-control study was designed with 200 early AMD cases and 200 healthy controls. For each participant, within a randomly selected OCT scan and a randomly selected column therein, manual grading was performed for 26 retinal feature positions. At every position, a total of 3792 descriptors were computed, based on nonlinear transformations of OCT data, first-order neighbourhood statistics and Haralick features. Equivalence and differences between cases and controls were tested for each descriptor at every graded position. Results of multiple testing were expressed in terms of false and true discovery rates controlled by the Benjamini-Yekutieli procedure.

resultsIn terms of the amount and disparity of true discoveries, overall non-equivalence was found for early AMD and healthy groups. Strong difference signals were observed at the internal limiting membrane and two central retinal positions, particularly for descriptors emphasising speckle noise.

conclusionsBetween the retinae of healthy controls and early AMD patients, significant differences were observed at the level of local neighbourhood statistics within OCT data. Thus, independent evidence was obtained for AMD affecting not only the outer retinal layers but the retina as a whole, even in the early stages of the disease. Within OCT data, both cartoon and speckle bear essential parts of the total information. We pursued a constructive, completely documented, traceable and repeatable approach without invoking artificial intelligence methods.