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Automated Retinal Layer Segmentation in CLN2-Associated Disease: Commercially Available Software Characterizing a
Kyle D Kovacs1, Anton Orlin1, Dolan Sondhi2
1Department of Ophthalmology, Retina Service, Weill Cornell Medical College, New York, NY, USA.
Translational Vision Science & Technology
|July 27, 2021
Summary
Automated optical coherence tomography segmentation reveals parafoveal outer nuclear layer thickness as an early indicator of CLN2-associated disease progression. This provides objective biomarkers for monitoring retinal degeneration in patients.
Area of Science:
- Ophthalmology
- Neuroscience
- Genetics
Background:
- CLN2-associated disease is a fatal genetic disorder causing progressive brain and retinal degeneration.
- Current monitoring relies on subjective clinical scales, necessitating more objective measures.
Purpose of the Study:
- To characterize inner and outer retinal degeneration in CLN2-associated disease using automated segmentation of optical coherence tomography (OCT) scans.
- To establish objective, quantifiable metrics for monitoring disease progression.
Main Methods:
- Retrospective analysis of OCT scans from treatment-naïve patients with CLN2-associated disease.
- Automated segmentation software used to measure retinal nerve fiber, ganglion cell layer (GCL), and outer nuclear layer (ONL) thickness.
- Measurements analyzed across different age groups.
Main Results:
- Significant differences in parafoveal ONL thickness were observed between specific age groups (39-45 vs. 46-52 months).
- Perifoveal ONL thickness also showed significant differences between older age cohorts (60-66 vs. >67 months).
- High repeatability and symmetry between eyes were noted.
Conclusions:
- Parafoveal ONL thickness serves as a sensitive, early indicator of retinal degeneration in CLN2-associated disease.
- Outer retinal changes are detectable at younger ages than inner retinal changes.
- Quantitative OCT biomarkers are established for future clinical trials.
