High-resolution in vivo fundus angiography using a non-adaptive optics imaging system

Mali Okada, Tjebo Heeren, Padraig Mulholland, Peter Maloca, Marketa Cilkova, Vincent Rocco, Marcus Fruttiger, Catherine Egan, RS Anderson, Adnan Tufail

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To provide a proof of concept for the detailed characterization of retinal capillary
features and surrounding photoreceptor mosaic using a customized non-adaptive optics angiography imaging system.

High-resolution fluorescein angiography (FFA) and/or indocyanine green
angiography (ICGA) images were obtained using a modified Heidelberg Retina
Angiograph (HRA2) device with a reduced scan angle enabling 3° field of view. Co-localized images of the photoreceptor mosaic were also captured in vivo using the same instrument. Visibility of vascular sub-branches were compared between high- resolution images and conventional fundus angiography (FA) with a 30° field of view.

High-resolution angiographic and infrared images (3° x 3° field of view, a 10-fold magnification) were obtained in ten participants. These included seven patients with various retinal diseases, including myopic degeneration, diabetic retinopathy, macular telangiectasia and central serous chorioretinopathy, as well as three healthy controls. Images of the retinal vasculature down to the capillary level were obtained on angiography with the ability to visualize a mean 1.2 levels more sub-branches as compared to conventional FA. In addition, imaging of the photoreceptor cone mosaic, to a sufficient resolution to calculate cone density, was possible. Movement of blood cells within the vasculature was also discernible on infrared videography.

This exploratory study demonstrates that fast high-resolution angiography and cone visualization is feasible using a commercially available imaging system.

Translational Relevance:
This offers potential to better understand the relationship between the retinal neuro-vascular system in health and disease and the timing of therapeutic interventions in disease states.
Original languageEnglish
JournalTranslational Vision Science & Technology
Publication statusPublished (in print/issue) - 27 Jun 2019


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