Characterization of single-file flow through human retinal parafoveal capillaries using an adaptive optics scanning laser ophthalmoscope
Spotlight summary: To date, it has been challenging to image and quantify the distribution and single-file flow characteristics of red and white blood cells traversing retinal capillaries in vivo in normal and diseased human eyes. While fluorescein angiography is an established clinical technique that images the retinal and choroidal vascular networks, the method is invasive (requiring the injection of a contrast dye into the blood stream) and, consequently, is typically performed only in diseased eyes. Additionally, fluorescein angiography provides transient visualization of the vascular network and can alter white blood cell function, making it an undesirable method for repeated or longitudinal imaging. Noninvasive techniques have been developed to image the vessel and capillary networks in vivo, including the use of red-free scanning laser ophthalmoscopy (e.g., the Heidelberg Spectralis SLO) and rapid illumination and imaging systems that are combined with intrinsic motion signal processing (e.g., the Retinal Function Imager). However, it has yet to be shown whether these or other methods can quantify blood flow dynamics and directionality in the smallest diameter capillaries in the human eye. Improved methods for measuring capillary blood flow are needed to better understand vascular changes that occur in retinal and systemic diseases.
In this paper, Tam et al. report an exciting new methodology to noninvasively visualize and characterize blood flow through the smallest retinal capillaries in vivo in a normal adult eye. The authors capitalize on the use of an adaptive optics scanning laser ophthalmoscope (AOSLO), a high-resolution imaging modality that can overcome the image degrading effects imposed by the eye’s aberrations, to view single leukoctyes and acquire real-time videos used to measure flow dynamics. When combined with their motion contrast enhancement technique (a method that determines the standard deviation of each pixel throughout a series of registered video frames), the authors are able to construct very impressive images of the perfused capillary bed surrounding the foveal avascular zone. The image quality of these perfusion maps rival (if not exceed) those produced using current clinical instrumentation. However, Tam et al. can also apply their motion contrast enhancement technique to the AOSLO reflectance videos and generate spatiotemporal plots of capillary hemodynamics. Based on these plots, the authors can extract dynamic flow information (i.e., blood flow frequency, direction, speed, and pulsatility) and differentiate capillaries that are dominated by leukocyte flow from those that are primarily dominated by plasma gap flow.
While the current implementation of this technique does have some limitations (e.g., not being able to directly verify which cells are being imaged) and some associated challenges for use in larger diameter vessels, it represents an important step forward in being able to quantify capillary flow dynamics in vivo for scientific and clinical purposes. The acquisition of high-resolution images of the retinal vascular network (including vessels and capillaries) could potentially improve our ability to noninvasively detect the early formation of vascular loops, microaneurysms, and other capillary alterations (such as perfusion losses or capillary drop-out) over the course of retinal disease. Moreover, the authors’ demonstrated methods for measuring flow dynamics in this paper could potentially be used to improve our understanding of blood cell and capillary flow dynamics in normal eyes, as well as in diseases that affect the retinal microcirculation (such as diabetic retinopathy and glaucoma).
ToC Category: Cardiovascular Applications
|OCIS Codes:||(110.2960) Imaging systems : Image analysis|
|(170.1470) Medical optics and biotechnology : Blood or tissue constituent monitoring|
|(170.4460) Medical optics and biotechnology : Ophthalmic optics and devices|
|(110.1080) Imaging systems : Active or adaptive optics|
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