Imaging oxygenation of retinal capillaries with depth resolution
Year: 2020
Type: article
Abstract: The inner retina has a three-tiered vascular supply, with capillary beds stratifying in the nerve fiber layer/ganglion cell layer, the inner plexiform layer, and the outer plexiform layer (1). While this trilaminar architecture likely functions to serve the metabolic needs of individual retinal layers, we do not know how metabolism and blood flow regulation differ across layers in the healthy retina. In particular, no noninvasive imaging technique with the potential for human translation has yet successfully distinguished the subtle metabolic signals that arise from these thin layers. For the past decade, visible light optical coherence tomography (OCT) (2, 3) has held the promise of imaging retinal oxygenation based on hemoglobin absorption. However, efforts have been largely limited to quantifying oxygenation of large vessels (4), with rare exceptions (5). In their latest work, Pi et al. (6) take a step toward making visible light OCT a tool for studying depth-resolved oxygenation of retinal capillary beds.
First, they show that their oximetry method is highly repeatable, a must for any measurement to make it to the clinic. Next, they turn their attention toward accuracy. The closest analog of a retinal capillary saturation measurement is a phosphorescence lifetime-based oxygen tension probe (7) or invasive tissue oxygen electrodes (8). How does one validate a technique for which there is no direct and noninvasive gold standard? The authors propose a creative, albeit indirect, method to gauge accuracy. As noted previously by the authors (9), the superficial vascular plexus supply in Brown Norway rats appears to consist predominantly of arterioles and their higher-order two-dimensional capillary branches that supply the surrounding tissue. In this model vascular bed (Fig. 1 …
[↵][1]1To whom correspondence may be addressed. Email: vjsriniv{at}ucdavis.edu.
[1]: #xref-corresp-1-1
Authors: Vivek J. Srinivasan, Ala Moshiri
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3035814549
