Identification and quantification of fibrotic areas in the human retina using polarization-sensitive OCT

Subretinal fibrosis is one of the most prevalent causes of blindness in the elderly population, but a true gold standard to objectively diagnose fibrosis is still lacking. Since fibrotic tissue is birefringent, it can be detected by polarization-sensitive optical coherence tomography (PS-OCT). We present a new algorithm to automatically detect, segment, and quantify fibrotic lesions within 3D data sets recorded by PS-OCT. The algorithm first compensates for the birefringence of anterior ocular tissues and then uses the uniformity of the birefringent optic axis as an indicator to identify fibrotic tissue, which is then segmented and quantified. The algorithm was applied to 3D volumes recorded in 57 eyes of 57 patients with neovascular age-related macular degeneration using a spectral domain PS-OCT system. The results of fibrosis detection were compared to the clinical diagnosis based on color fundus photography (CFP), and the precision of fibrotic area measurement was assessed by three repeated measurements in a sub-set of 15 eyes. The average standard deviation of the fibrotic area obtained in eyes with a lesion area 0.7 mm(2) was 15%. Fibrosis detection by CFP and PS-OCT agreed in 48 cases, discrepancies were only observed in cases of lesion area < 0.7 mm(2). These remaining discrepancies are discussed, and a new method to treat ambiguous cases is presented. Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License.

Automated summary

A new algorithm for automatic detection, segmentation, and quantification of fibrotic lesions in 3D data sets recorded by PS-OCT was presented in this study. The algorithm showed high precision in detecting fibrosis and agreement with clinical diagnosis, particularly in cases of smaller lesion areas.