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

Souvick Mukherjee, Cameron Duic, Tharindu De Silva, Tiarnan D L Keenan, Alisa T Thavikulwat, Emily Y Chew, Catherine Cukras

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Article in Translational vision science & technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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7 authors.

Souvick MukherjeeClinical Trials Branch, Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, USA.

Cameron DuicClinical Trials Branch, Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, USA.

Tharindu De SilvaClinical Trials Branch, Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, USA.

Tiarnan D L KeenanClinical Trials Branch, Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, USA.

Alisa T ThavikulwatClinical Trials Branch, Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, USA.

Emily Y ChewClinical Trials Branch, Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, USA.

Catherine CukrasClinical Trials Branch, Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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)].

Indexed as

AlgorithmsMacular DegenerationRetinal DetachmentRetinal DrusenRetinal Pigment EpitheliumTomography, Optical CoherenceAgedAged, 80 and overBruch MembraneFemaleHumansMaleMiddle Aged

Identifiers

PMID39565329

DOI10.1167/tvst.13.11.25

PMCPMC11583990

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LicenceCC BY-NC-ND

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