Purpose:
Knowledge of the macular thickness in a normal population is important for the evaluation of pathological macular change. Spectral-domain optical coherence tomography (SD-OCT) is a high-speed scanning technology capable of rapidly acquiring a large, volumetric dataset. The purpose of this study was to define and measure macular thickness in normal eyes using SD-OCT.
Methods:
Seventy eyes from seventy subjects (42 men and 28 women) were scanned with a prototype SD-OCT (8µm axial resolution). We used a raster scan pattern uniformly covering a retinal area of 6 x 6 mm. Subjects ranged in age from 22 to 95 and were selected on a self-declared normal basis. Each scan was reviewed by a clinician and screened for abnormalities and/or eye movements. We developed a computer algorithm that automatically identifies specific retinal boundaries producing accurate and reproducible retinal thickness maps. It should be noted that our algorithm defines retinal thickness as the distance between the ILM and the RPE (Stratus OCT instead measures from the ILM to the IS/OS junction). Approximately 40% of the subjects were also scanned with Stratus OCT and the macular thickness measurements were then compared to measurements on the SD-OCT system.
Results:
After centering the fovea, the mean and standard deviation for retinal thickness were calculated point wise, as well as averaged on standard regions (Table 1). On patients scanned with both systems the measurements from SD-OCT were consistently 30-40µm larger compared to measurements from Stratus OCT.
Conclusions:
Using SD-OCT it is possible to acquire retinal datasets containing an unprecedented number of data points. Furthermore it is possible to use OCT fundus images to evaluate the scan quality and to center the measurement at the fovea. These advantages, together with good automated segmentation can produce more accurate retinal thickness measurements. Incorporation of the photoreceptor layer in the measurements is anatomically meaningful and may be significant in evaluating various retinal pathologies and visual acuity outcomes.
Keywords: macula/fovea • imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound) • retina