Neurodegenerative and neuroinflammatory diseases regularly cause optic nerve and
retinal damage. Evaluating retinal changes using optical coherence tomography (OCT)
in diseases like multiple sclerosis has thus become increasingly relevant. However,
intraretinal segmentation, a necessary step for interpreting retinal changes in the context
of these diseases, is not standardized and often requires manual correction. Here
we present a semi-automatic intraretinal layer segmentation pipeline and establish
normative values for retinal layer thicknesses at the macula, including dependencies on
age, sex, and refractive error. Spectral domain OCT macular 3D volume scans were
obtained from healthy participants using a Heidelberg Engineering Spectralis OCT. A
semi-automated segmentation tool (SAMIRIX) based on an interchangeable third-party
segmentation algorithm was developed and employed for segmentation, correction, and
thickness computation of intraretinal layers. Normative data is reported froma 6mmEarly
Treatment Diabetic Retinopathy Study (ETDRS) circle around the fovea. An interactive
toolbox for the normative database allows surveying for additional normative data. We
cross-sectionally evaluated data from218 healthy volunteers (144 females/74males, age
36.5 ± 12.3 years, range 18–69 years). Average macular thickness (MT) was 313.70 ±
12.02 μm, macular retinal nerve fiber layer thickness (mRNFL) 39.53 ± 3.57 μm, ganglion
cell and inner plexiform layer thickness (GCIPL) 70.81 ± 4.87 μm, and inner nuclear layer
thickness (INL) 35.93 ± 2.34 μm. All retinal layer thicknesses decreased with age. MT
and GCIPL were associated with sex, with males showing higher thicknesses. Layer
thicknesses were also positively associated with each other. Repeated-measurement
reliability for the manual correction of automatic intraretinal segmentation results was excellent, with an intra-class correlation coefficient >0.99 for all layers. The SAMIRIX
toolbox can simplify intraretinal segmentation in research applications, and the normative
data application may serve as an expandable reference for studies, in which normative
data cannot be otherwise obtained
