Using ultrahigh sensitive optical microangiography to achieve comprehensive depth resolved microvasculature mapping for human retina

Abstract

This paper presents comprehensive and depth-resolved retinal microvasculature images within human retina achieved by a newly developed ultrahigh sensitive optical microangiography (UHS-OMAG) system. Due to its high flow sensitivity, UHS-OMAG is much more sensitive to tissue motion due to the involuntary movement of the human eye and head compared to the traditional OMAG system. To mitigate these motion artifacts on final imaging results, we propose a new phase compensation algorithm in which the traditional phase-compensation algorithm is repeatedly used to efficiently minimize the motion artifacts. Comparatively, this new algorithm demonstrates at least 8 to 25 times higher motion tolerability, critical for the UHS-OMAG system to achieve retinal microvasculature images with high quality. Furthermore, the new UHS-OMAG system employs a high speed line scan CMOS camera (240 kHz A-line scan rate) to capture 500 A-lines for one B-frame at a 400 Hz frame rate. With this system, we performed a series of in vivo experiments to visualize the retinal microvasculature in humans. Two featured imaging protocols are utilized. The first is of the low lateral resolution (16 μm) and a wide field of view (4 × 3 mm(2) with single scan and 7 × 8 mm(2) for multiple scans), while the second is of the high lateral resolution (5 μm) and a narrow field of view (1.5 × 1.2 mm(2) with single scan). The great imaging performance delivered by our system suggests that UHS-OMAG can be a promising noninvasive alternative to the current clinical retinal microvasculature imaging techniques for the diagnosis of eye diseases with significant vascular involvement, such as diabetic retinopathy and age-related macular degeneration.

Figure 1

Schematic of UHS-OMAG system. SLD: superluminescent diode; PC: polarization controller.

Figure 2

FDOCT fundus image. Larger dashed square indicates the region where a typical UHS-OMAG 3D data was captured. Solid square indicate the scanning positions for imaging a large field of view (the number represents the scanning order); the region marked with small dashed square corresponds to the imaging location for high resolution imaging protocol; the dashed line marks the position of a typical B-scan cross section image.

Figure 3

UHS-OMAG cross-sectional images of the retina around the macular region. (a) Typical cross-sectional structure image, from which three layers (GCL, IPL, and OPL) can be clearly identified. (b) Phase difference map between adjacent B-scans (N = 0). (c) UHS-OMAG flow image without phase compensation (N = 0). (d) Phase difference map after one time phase compensation (N = 1). (e) UHS-OMAG flow image after one time phase compensation (N = 1). (f) Phase difference map after high order phase compensation (N = 4). (g) UHS-OMAG flow image after high order phase compensation (N = 4). The color bar of the phase difference map is from −π to π.

Figure 4

UHS-OMAG reveals detailed retinal microvasculature network around macular region. (a), (b), and (c) present the blood vessel networks located at the GCL, IPL, and OPL layers, respectively. (d) False-color depth-encoded blood vessel images by integrating (a), (b), and (c) into one image. The red, green, and blue colors correspond to the vessels within the GCL, IP, and OPL layers, respectively.

Figure 5

Fluorescence angiography ocular vasculature map of the healthy volunteer. The blue square indicates the location of retina blood perfusion map obtained by UHS-OMAG system.

Figure 6

UHS-OMAG is capable of providing (a) retinal microvasculature maps within a large field of view, and (b) the corresponding color depth-encoded retinal vasculature map (the red, green, and blue colors represent the GCL, IPL, and OPL, respectively).

Figure 7

High resolution UHS-OMAG retinal vasculature network images reveal clear details of the vessel interconnections, particularly for the capillary blood vessels. (a), (b), and (c) present the blood vessel networks located at the GCL, IPL, and OPL layers, respectively. (d) False color depth-encoded blood vessel images by combining the vessels presented in (a), (b), and (c). The red, green, and blue colors correspond to GCL, IPL, and OPL, respectively.