Abstract
Purpose :
To compare macular thickness measurement algorithms of two different spectral-domain optical coherence tomography (SD-OCT) devices.
Methods :
In this IRB-approved study, patients and normal controls from the retina clinics of the Doheny Eye Center-UCLA were imaged using two different SD-OCT devices: RS 3000 Advance (Nidek Co. Ltd.) and Cirrus HD-OCT (Carl Zeiss Meditec, Inc.). Ninety-one diseased eyes from 51 patients and 10 normal healthy eyes from 5 normal volunteers were included in this study. Patients had various pathologies including exudative and nonexudative age-related macular degeneration, cystoid macular edema, epiretinal membrane and macular hole. The commercial instrument software was used to generate the macular retinal thickness measurements, and measurements were compared between devices.
Results :
The macular thickness measurements generated by the two instruments are different in mean retinal thickness in the foveal center subfield (259.59 ± 51.79 µm Nidek OCT vs. 239.40 ± 52.55 µm Cirrus OCT, p<0.001). The macular thickness measurements, as evaluated by the two different instruments, however, showed excellent correlation (r=0.99, p<0.001) with an intraclass correlation coefficient of 0.99 (95% confidence interval, 0.98 – 0.99). The mean difference between two measurements, considering the control and diseases eyes, was 20.19 ± 8.74 µm, and appeared to be related to slightly different selection of the outer retinal boundary. The mean difference between two measurements for control eyes was 18.70±4.32 and 20.36±9.10 for diseases eyes, not statistically different (p>0.05). Post hoc evaluation of cases with larger differences also showed differences in foveal center selection as well as variabilities in boundary selection with specific pathologies.
Conclusions :
Macular thickness measurements provided by the Nidek and Cirrus OCT instruments are highly correlated, but show a consistent difference, which may allow a correction factor to be applied to inter-relate measurements between devices.
This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.