Purpose: Optical coherence tomography (OCT) is a reliable method used to quantify discrete layers of the retina. Spectralis OCT is a device used for this purpose. Spectralis OCT macular scan imaging acquisition can be obtained on either the horizontal or vertical plane. The vertical protocol has been proposed as favorable, due to postulated reduction in confound of Henle's fibers on segmentation-derived metrics. Yet, agreement of the segmentation measures of horizontal and vertical macular scans remains unexplored. Our aim was to determine this agreement.
Materials And Methods: Horizontal and vertical macular scans on Spectralis OCT were acquired in 20 healthy controls (HCs) and 20 multiple sclerosis (MS) patients. All scans were segmented using Heidelberg software and a Johns Hopkins University (JHU)-developed method. Agreement was analyzed using Bland-Altman analyses and intra-class correlation coefficients (ICCs).
Results: Using both segmentation techniques, mean differences (agreement at the cohort level) in the thicknesses of all macular layers derived from both acquisition protocols in MS patients and HCs were narrow (<1 µm), while the limits of agreement (LOA) (agreement at the individual level) were wider. Using JHU segmentation mean differences (and LOA) for the macular retinal nerve fiber layer (RNFL) and ganglion cell layer + inner plexiform layer (GCIP) in MS were 0.21 µm (-1.57-1.99 µm) and -0.36 µm (-1.44-1.37 µm), respectively.
Conclusions: OCT segmentation measures of discrete retinal-layer thicknesses derived from both vertical and horizontal protocols on Spectralis OCT agree excellently at the cohort level (narrow mean differences), but only moderately at the individual level (wide LOA). This suggests patients scanned using either protocol should continue to be scanned with the same protocol. However, due to excellent agreement at the cohort level, measures derived from both acquisitions can be pooled for outcome purposes in clinical trials.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6097232 | PMC |
| http://dx.doi.org/10.1080/02713683.2017.1406526 | DOI Listing |
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