Automated Detection of Drusenoid Pigment Epithelial Detachments From Spectral-Domain Optical Coherence Tomography in Patients With AMD.

Autor:	Mukherjee S; Clinical Trials Branch, Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, USA., Duic C; Clinical Trials Branch, Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, USA., De Silva T; Clinical Trials Branch, Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, USA., Keenan TDL; Clinical Trials Branch, Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, USA., Thavikulwat AT; Clinical Trials Branch, Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, USA., Chew EY; Clinical Trials Branch, Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, USA., Cukras C; Clinical Trials Branch, Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, USA.
Jazyk:	angličtina
Zdroj:	Translational vision science & technology [Transl Vis Sci Technol] 2024 Nov 04; Vol. 13 (11), pp. 25.
DOI:	10.1167/tvst.13.11.25
Abstrakt:	Purpose: This study aimed to develop an algorithm for automated detection of drusenoid pigment epithelial detachments (DPEDs) in optical coherence tomography (OCT) volumes of patients with age-related macular degeneration (AMD) and to compare its performance against traditional reading center grading on color-fundus photographs (CFPs). Methods: Eyes with a range of AMD severities, excluding neovascular disease, were imaged using spectral-domain OCT (SD-OCT) and paired CFPs and were followed annually for up to 5 years. DPEDs were automatically identified by segmenting the retinal pigment epithelium (RPE) and Bruch's membrane (BM) layers from the SD-OCT volumes and imposing both a minimum RPE BM height (>75 µm) and a two-dimensional length requirement (>433 µm). Comparisons in detection rates and contoured areas were made between the algorithmic SD-OCT detections and manually graded and contoured CFPs. Results: Of the 1602 visits for the 323 eyes, the automated OCT algorithm identified 139 visits (8.7%) from 50 eyes with DPED, but a reading center review of paired CFPs identified 23 visits (1.4%) from nine eyes as having DPEDs. Eyes identified with DPEDs on OCT received nine-step AMD severity scores ranging from 6 to 10, and those scores had occurrence ratios of 23/160 (14%), 89/226 (39%), 24/99 (24%), 2/63 (3%), and 1/29 (3%), respectively. On a subset of 25 visits that also underwent manual contouring of DPED lesions in CFP, the Pearson correlation coefficient for DPED areas observed by OCT and CFP was 0.85. Conclusions: Our analysis shows the feasibility of using OCT scans to objectively detect features that historically have been detected qualitatively by expert graders on CFPs. Translational Relevance: Automated detection and quantitation of high-risk features can facilitate screening patients for clinical-trial enrollment and could serve as an outcome metric [T1 (Translation-to-Humans) and T4 (Translation-to-Population-Health)].
Databáze:	MEDLINE
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