Abstract
Purpose :
To demonstrate a fully integrated Home OCT System used by subjects with neovascular age-related macular degeneration and to propose novel reporting parameters of self-imaging performance and retinal fluid volume dynamics.
Methods :
Pilot study of 8 eyes from 4 subjects with mean (SD) age of 74 (4) years (mean baseline VA 20/50). Subjects self-imaged at home daily for 1 month. Automatic secure data transmission to the Cloud was followed by volume scan reconstruction and deep learning-based analysis (Notal OCT Analyzer; NOA). Outcomes included subjects’ ability to self-image daily, comparison of fluid status with human expert grading, and temporal dynamics of intraretinal (IRF) and subretinal fluid (SRF) volumes
Results :
During 232 cumulative study eye-days, the subjects self-imaged 212 times (91%). The mean (SD) self-image acquisition time was 41 (15) seconds. In 100 of the 212 (47%) scans, retinal fluid was identified by the NOA (46% IRF, 46% SRF, 8% both). In 197 of the 212 (93%) scans, there was agreement of fluid status between NOA and human grading. In 5 eyes with a change in fluid status, the mean (maximum) interval between human grading and NOA identifying the change was 1.5 (3) days. In 4 eyes, the change was from fluid absence to presence, and the mean (maximum) fluid volume at detection of recurrence was 1.6 (3) nL. The temporal fluid dynamics over 1 month will be presented, including: identification of fluid status change, interval of fluid increase or decrease in relation to treatment, maximum fluid volume, fluid volume cumulated over time, and spatial distribution of fluid thickness over time.
Conclusions :
To the best of our knowledge, this represents the first longitudinal pilot study of a home OCT system. It fulfils the relevant requirements: self-imaging with a device designed for low cost at large quantities, automatic data transmission, volume scan reconstruction, AI-based image analysis, and fluid volume tracking over time. The biomarker of fluid volume, and its related parameters, may present useful information in the management of retinal diseases.
This is a 2021 ARVO Annual Meeting abstract.