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

BACKGROUND AND

OBJECTIVES

Associations 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, an omics-type approach was designed for full exploitation of OCT data, which was able to identify signs of early AMD throughout the retina as a whole.

METHODS

A nested case-control study was designed with 200 early AMD cases and 200 healthy controls. For every participant, within a randomly selected OCT scan and a randomly selected column therein, manual grading was performed for 26 retinal feature positions. At each 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 every descriptor at each graded position. Results of multiple testing were expressed in terms of false and true discovery rates controlled by the Benjamini-Yekutieli procedure.

RESULTS

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

CONCLUSIONS

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