High-resolution optical coherence tomography (HR-OCT) significantly improves the accuracy and reliability of identifying and classifying atrophic lesions associated with age-related macular degeneration (AMD) when compared to standard resolution OCT, according to a study.
The findings highlight the superiority of HR-OCT in both qualitative and quantitative assessments, particularly in identifying specific atrophic features and measuring associated parameters.
In this prospective, observational, cross-sectional study, 60 patients (60 eyes) diagnosed with AMD, underwent volume OCT scanning using both HR-OCT and standard resolution OCT devices. Trained graders reviewed and graded the scans, pinpointing specific regions of interest for subsequent analysis. The primary focus of the study was on identifying and classifying complete retinal pigment epithelium and outer retinal atrophy (cRORA), incomplete RORA (iRORA), and other non-atrophic AMD features.
The results showcased substantial to perfect agreement among readers for classifying atrophic lesions, with a noteworthy agreement of 0.88 for HR-OCT and 0.82 for standard resolution OCT. Notably, HR-OCT demonstrated higher accuracy in identifying iRORA lesions compared to its standard counterpart.
In the realm of qualitative assessment, HR-OCT outshone standard OCT, particularly in identifying external limiting membrane (ELM) and ellipsoid zone (EZ) disruption, with agreements of 0.95 and 0.94, respectively. Quantitative measurements of features such as hypertransmission defects, retinal pigment epithelium attenuation/disruption, EZ disruption width, and ELM disruption width exhibited excellent inter-reader agreement with HR-OCT (> 0.90 for all features). In contrast, standard OCT showed only moderate agreement (0.51-0.60) for these quantitative features.
Reference
Mahmoudi A, Corradetti G, Emamverdi M, et al. Atrophic Lesions Associated with Age-related Macular Degeneration: High-resolution versus Standard Optical Coherence Tomography. Ophthalmol Retina. 2023;S2468-6530(23)00513-4. doi: 10.1016/j.oret.2023.10.011. Epub ahead of print. PMID: 37871680.
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