July 2018
Volume 59, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2018
Real-time quantification of single blood-cell velocity in living human and mouse eye using adaptive optics
Author Affiliations & Notes
  • Aby Joseph
    Institute of Optics, University of Rochester, Rochester, New York, United States
    Center for Visual Science, University of Rochester, Rochester, New York, United States
  • Keith Parkins
    Center for Visual Science, University of Rochester, Rochester, New York, United States
  • Qiang Yang
    Center for Visual Science, University of Rochester, Rochester, New York, United States
  • Andres Guevara-Torres
    Institute of Optics, University of Rochester, Rochester, New York, United States
    Center for Visual Science, University of Rochester, Rochester, New York, United States
  • Jesse Schallek
    The Flaum Eye Institute, University of Rochester , Rochester, New York, United States
    Center for Visual Science, University of Rochester, Rochester, New York, United States
  • Footnotes
    Commercial Relationships   Aby Joseph, Canon Inc. (F), Roche (F), University of Rochester (P); Keith Parkins, University of Rochester (P); Qiang Yang, Canon Inc. (F), Canon Inc. (P), Montana State University (P), Oculus VR (F), University of Rochester (P); Andres Guevara-Torres, Canon Inc. (F), Roche (F), University of Rochester (P); Jesse Schallek, Canon Inc. (F), Roche (F), University of Rochester (P)
  • Footnotes
    Support  Research reported in this publication was supported by the National Eye Institute of the National Institutes of Health under Award No. EY028293 and P30 EY001319. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Inst. of Health. This study was also supported by an Unrestricted Grant to the University of Rochester Department of Ophthalmology, a Stein Innovation Award (to D.R. Williams) and a Career Development Award (J. Schallek) from Research to Prevent Blindness, New York, NY. Work was also supported by the Dana Foundation- David Mahoney Neuroimaging Grant and a research grant from Hoffman-LaRoche Inc.
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 1973. doi:https://doi.org/
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      Aby Joseph, Keith Parkins, Qiang Yang, Andres Guevara-Torres, Jesse Schallek; Real-time quantification of single blood-cell velocity in living human and mouse eye using adaptive optics. Invest. Ophthalmol. Vis. Sci. 2018;59(9):1973. doi: https://doi.org/.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Adaptive optics (AO) resolves single blood cells in the living eye with high spatio-temporal resolution, providing a detailed view of blood flow dynamics in the full spectrum of retinal vessel sizes. An array of functional biomarkers of vascular health can be computed with 1-4 seconds of AO data. However, such data can contain >100,000 cells, needing minutes to hours of post-processing time to quantify single cell velocity. Here we present a real-time strategy that computes cell velocity at image acquisition rate and augments raw images with live overlay of velocities.

Methods : AO linescan imaging (15 kHz) analyzed retinal vessels in one human and 10 anesthetized mice, producing space-time images of moving blood cells with 796 nm backscatter. Optimized computation of the Radon transform automatically determined single cell velocity in up to ~1700 overlapping image analysis regions per second. Colored overlays of velocities and SNR were displayed live on raw image data for instant user feedback (Fig.1). High spatio-temporal imaging resolution was used to quantify indices of heart rate, pulsatility, vessel resistivity and laminar flow, in real-time.

Results : Our algorithm gave real-time automated measurements of blood velocity at 15,000 lines/s (image acquisition rate). Computation was >50 times faster than previous software, thus enabling live visualization of velocities. In 45 mouse arterioles, venules and capillaries of lumen size 3-50 µm, single cell velocities of 0-40 mm/s were observed. In one human venule (55 µm), measured velocity was 12±8.7 mm/s (mean±1SD). Velocities were within measurement bandwidth of 0-850 mm/s. Hemodynamic biomarkers quantified in real-time included heart rate (mouse (m): 185-300, human (h): 61 beats/min), pulsatility index (m: 0.21-1.22, h: 0.52), vascular resistivity (m: 0.20-0.73, h: 0.41) and laminar flow (m: Vmax/Vmean=1-1.26).

Conclusions : Real-time quantification and display of single-cell velocity revealed detailed modulations in velocity due to heart beat and laminar flow in microscopic vessels of the eye. Such live quantitative feedback can enable on-the-fly experiment optimizations by user and quick assessment of retinal vascular health in the clinic, where patient time is limited. In the future, vascular indices measured in the eye may also serve as a ‘window’ to study dynamics of systemic microvascular health.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

 

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