Abstract
Purpose:
<br /> To obtain normative database of the different retinal layer thickness, using recently developed automatic retinal segmentation, and to evaluate the relationship between retinal layers and aging.
Methods:
A prospective study of healthy controls, with no clinical evidence of retinal or glaucomatous disease was performed. The automated layer segmentation protocol of the HRA Spectralis and OCT (Heidelberg Engineering, Heidelberg, Germany) was used. The different retinal layers identified were inner limiting membrane (ILM), retinal nerve fiber layer (RNFL), ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer (INL), outer plexiform layer (OPL), external limiting membrane (ELM), interface of the inner and outer segments of the photoreceptor layer (PR1), outer segment-RPE interdigitation (PR2), RPE and Bruch’s membrane complex.The respective measured thickness of each layer was reported beneath the fovea, at 500 µm and 1500 µm intervals, nasally and temporally to the center of the fovea respectively<br /> Inclusion criteria: in the L<br /> Patients presenting at our practice for visual control have been clinically thoroughly examined. They were included in the study if visual acuity on the ETDRS scale was superior to 80 letters and no anomaly was detected until each decade of age group contained 10 subjects. The protocol was then carried out with the Spectralis SD-OCT.
Results:
60 eyes of 30 healthy subjects were included. The groups were distributed between 30 years to 80 years in 10 years gap. Each group comprises a minimum of 10 eyes.<br /> Primary endpoint: obtain the scale of the thickness of the retinal layers, and the different layers shape.<br /> The details of the measures showed that the thickness of the RNFL nasally (at 500 and 1500µm) was thicker as expected than temporally.<br /> Secondary endpoint: point out retinal layers thickness modification through aging.<br /> The PR1 layer is the one that showed a consistant thickness decrease with age. The other layers had a more variable course needing probably a larger asample size.
Conclusions:
This attempt to obtain normative data base of the measure retinal layers with automatic retinal segmentation provides interesting results. This work needs a confirmation in a larger study group before predating pathological studies.