Radiomic Characterization and Automated Classification of Drusen Substructure Phenotype Associated with High-Risk Dry Age-Related Macular Degeneration.

Background/

Objectives

Optical coherence tomography (OCT)-reflective drusen substructures (ODSs) are associated with the conversion of intermediate AMD to geographic atrophy (GA). However, ODSs must be manually identified, a laborious process introducing bias and variation. This study proposes objective radiomic metrics of drusen phenotypes and validates them for the prediction of GA development and GA growth rate.

Methods

A total of 104 drusen with high-reflective cores (H-type), 105 with low-reflective cores (L-type), 129 conical drusen (C-type), and 101 normal drusen (N-type) were segmented from OCT images. Radiomic features were extracted from these drusen, and the most important features for drusen classification were extracted from the retinal pigment epithelium-Bruch's membrane compartment of 743 OCT scans of eyes with dry AMD and used to predict GA conversion and fast growth.

Results

Radiomic features classified drusen phenotypes with AUC = 0.87-0.95. H-type drusen have a higher reflectivity, greater variation in reflectivity, and coarser texture (p < 0.001). L-type drusen have a lower reflectivity and greater variation in reflectivity (p < 0.0001). C-type drusen have a less spherical shape and more disordered internal reflectivity (p < 0.001). N-type drusen have a more spherical shape and more uniform internal reflectivity (p < 0.001). These radiomic features predict the conversion from intermediate AMD to GA and top-quartile GA growth rate with AUC = 0.59-0.74 at years 1-3.

Conclusions

These results demonstrate the potential of clinical phenotype-grounded radiomics for objective automated drusen analysis, GA risk stratification, and clinical prediction.