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Marina Garcia Garrido, Susanne C Beck, Regine Lotte Muehlfriedel, Stylianos Michalakis, Martin Biel, Mathias W Seeliger; Quantitative description of murine OCT features based on reflectivity profiles. Invest. Ophthalmol. Vis. Sci. 2014;55(13):2082.
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© ARVO (1962-2015); The Authors (2016-present)
The vast majority of OCTs are currently evaluated qualitatively based on 2D and 3D images, but these data are hard to quantify, not least due to continuing difficulties in automated segmentation. Here, we assess the value of OCT reflectivity profiles as a basis for a quantitative characterization of the murine retinal configuration.
Spectral-Domain Optical Coherence Tomography (OCT), confocal Scanning-Laser Ophthalmoscopy (SLO), and Fluorescein Angiography (FA) were performed in all animals. OCTs were obtained with the Heidelberg Engineering Spectralis system, and SLOs and FAs with the HRA I of the same company. Reflectivity profiles were extracted from 8-bit greyscale OCT images using the ImageJ software package (http://rsb.info.nih.gov/ij/). Structural characteristics were studied in pigmented and non-pigmented mouse lines (C57BL/6 and BALB/c, respectively). Vascular OCT specifics were assessed in αSMA-GFP mice (Fischer et al. 2010), and outer retinal organization in the native and treated CNGB1 model for retinitis pigmentosa (Koch et al. 2012).
OCT scans were reliably obtained from all mouse lines. The respective reflectivity profiles allowed for a quantitative assessment of layer-specific characteristics in both pigmented and non pigmented strains. The comparison of OCT reflectivity profiles with the GFP-tagged anatomical vessel boundaries in αSMA-GFP mice revealed a characteristic pattern in the reflectivity of the retinal vasculature. In addition, the profile data in native and gene therapy-treated CNGB1 mice disclosed further details about outer segment reflectivity.
OCT reflectivity profiles show great potential to support 2D and 3D image data of the retina. We show here that both additional quantitative as well as qualitative information about retinal layers and structures may become available. We see main fields of application in the evaluation of disease models and the assessment of respective therapeutic strategies.
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