Abstract
Purpose :
We performed a prospective, observational study to analyze the repeatability of measurements of the thicknesses of the macula, retinal nerve fiber layer (RNFL), and ganglion cell inner plexiform layer (GCIPL) using spectral domain optical coherence tomography (SD-OCT) in branch retinal vein occlusion (BRVO).
Methods :
Patients diagnosed with BRVO were analyzed prospectively. An experienced examiner obtained two consecutive measurements from a macular cube 512 × 128 and optic disc cube 200 x 200 scans using SD-OCT. Thickness of central macula, RNFL, and GCIPL of affected eyes with macular edema (before treatment), without macular edema (after treatment), and opposite normal fellow eyes were measured. Also, the repeatability of measurements was evaluated with intraclass correlation coefficient (ICC).
Results :
The average thickness of the central macula, RNFL, and GCIPL was 411.35μm, 104.09μm, 51.03μm, respectively, in the affected eyes with macular edema, 249.35μm, 94.56μm, 81.32μm in the affected eyes without macular edema. The average GCIPL was statistically significant thinner in the patients with macular edema than without macular edema(p<0.05). The ICCs of the central macula, RNFL, and GCIPL were 0.978, 0.919, 0.789, respectively, in the affected eyes with macular edema, 0.999. 0.975, 0.928 in the affected eyes without macular edema, showing high repeatability of GCIPL after treatment. The average thickness of the central macula, RNFL, and GCIPL was 253.12μm, 96.47μm, 85.09μm, respectively, and the ICCs were 0.996, 0.995, 0.994 in the opposite normal fellow eyes.
Conclusions :
The macular contour change with the macular edema in BRVO results in low repeatability and tendency to be measured thinner in GCIPL thickness using SD-OCT. However, the average thickness and repeatability of measurements of GCIPL increased after resolution of macular edema. This can be explained by the unstable gaze of the patient due to decreased visual acuity and auto-segmentation error following changes in the macula.
This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.