ArticleTranslational vision science & technology2021
Automated Retinal Layer Segmentation in CLN2-Associated Disease: Commercially Available Software Characterizing a Progressive Maculopathy.
Article in Translational vision science & technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Recreating pathophysiology of CLN2 disease and demonstrating reversion by TPP1 gene therapy in hiPSC-derived retinal organoids and retina-on-chip.Cell reports. Medicine · 2025Article
- OCT Biomarkers in Ocular CLN2 Disease in Patients Treated With Intraventricular Enzyme Replacement Therapy.Investigative ophthalmology & visual science · 2024Article
- Peripapillary Retinal Nerve Fiber Layer (pRNFL) Thickness - A Novel Biomarker of Neurodegeneration in Late-Infantile CLN2 Disease.Eye and brain · 2024Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Purpose: CLN2-associated disease is a hereditary, fatal lysosomal storage disorder characterized by progressive brain and retinal deterioration. Here, we characterize the inner and outer retinal degeneration using automated segmentation software in optical coherence tomography scans, providing an objective, quantifiable metric for monitoring subtle changes previously identified with a validated disease classification scale (the Weill Cornell Batten Scale). Methods: This study is a retrospective, single-center cohort review of images from examinations under anesthesia in treatment-naïve patients with CLN2-associated disease. Automated segmentation software was used to delineate retinal nerve fiber, ganglion cell layer (GCL), and outer nuclear layer (ONL) thickness measurements in the fovea, parafovea, and perifovea based on age groups (months): 30 to 38, 39 to 45, 46 to 52, 53 to 59, 60 to 66, and 67 or older. Results: Twenty-seven eyes from 14 patients were included, with 8 serial images yielding 36 interpretable optical coherence tomography scans. There was a significant difference in parafoveal ONL thickness between 39 to 45 and 46 to 52 months of age (P = 0.032) not seen in other regions or retinal layers. Perifoveal ONL demonstrated a difference in thickness between the 60 to 66 and greater than 67 months age cohorts (P = 0.047). There was strong symmetry between eyes, and high segmentation repeatability. Conclusions: Parafoveal ONL thickness represents a sensitive, early age indicator of CLN2-associated degeneration. Outer retinal degeneration is apparent at younger ages than inner retinal changes though in treatment-naïve patients all retinal layers showed significant differences between 60 to 66 and more than 67 months of age. Translational Relevance: This study establishes sensitive, quantitative biomarkers for assessing retinal degeneration in a large cohort natural history study in anticipation of future clinical trials.
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Registered trials
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