Abstract
Purpose :
Macular Thickness Analysis (MTA) is a widely used tool for diagnosing and monitoring patients with ocular pathologies. The robustness of MTA is directly connected to the quality of the optical coherence tomography (OCT) system used to image the eye, which can be limited in low-cost devices. In this study we statistically compare the performance of MTA between a commercial OCT device and a low-cost OCT prototype.
Methods :
A low-cost OCT prototype system (ZEISS, Dublin, CA) and a CIRRUSTM HD-OCT 5000 (ZEISS, Dublin, CA) were used to image 70 eyes with a range of ocular pathologies, including age-related macular degeneration (AMD). On each case the resulting OCT volumes were segmented to delineate the inner limiting membrane (ILM) and the retinal pigment epithelium (RPE). The prototype segmentation was used to generate macular thickness maps with 512x512 pixels over an area of 5.78mmx5.78mm. The two maps were registered to each other and the ETDRS grid was centered using the foveal location, manually selected on the CIRRUS scan (Figure 1). The ETDRS grid consists of three concentric circles with radii of 0.5, 1.5 and 2.89mm. A linear regression and Bland-Altman analysis were used to compare the two groups. The coefficient of determination (R2), slope and intercept of the regression analysis, mean difference and 95% limits are reported for each of the 9 sectors of the ETDRS grid.
Results :
A total of 70 eyes from 43 patients were imaged during this study. Table 1 shows the statistical comparison between OCT systems for each sector of the ETDRS grid. The low-cost OCT prototype measured macular thickness slightly higher than the CIRRUS, with mean differences ranging between 4 and 7 microns depending on the retinal sector. R2 values varied between 0.90 and 0.98.
Conclusions :
This study demonstrates the ability of our low-cost OCT prototype to accurately measure macular thickness with similar performance to that of a commercial OCT system. The small differences in thickness measurements are likely not clinically significant and could be compensated. This technology could be useful for monitoring patients with chronic diseases in a cost-efficient way.
This is a 2021 ARVO Annual Meeting abstract.