Analysis of structural effects of sickle cell disease on brain vasculature of mice using three-dimensional quantitative phase imaging

Abstract

Significance: Although the molecular origins of sickle cell disease (SCD) have been extensively studied, the effects of SCD on the vasculature-which can influence blood clotting mechanisms, pain crises, and strokes-are not well understood. Improving this understanding can yield insight into the mechanisms and wide-ranging effects of this devastating disease.

Aim: We aim to demonstrate the ability of a label-free 3D quantitative phase imaging technology, called quantitative oblique back-illumination microscopy (qOBM), to provide insight into the effects of SCD on brain vasculature.

Approach: Using qOBM, we quantitatively analyze the vasculature of freshly excised, but otherwise unaltered, whole mouse brains. We use Townes sickle transgenic mice, which closely recapitulate the pathophysiology of human SCD, and sickle cell trait mice as controls. Two developmental time points are studied: 6-week-old mice and 20-week-old mice. Quantitative structural and biophysical parameters of the vessels (including the refractive index (RI), which is linearly proportional to dry mass) are extracted from the high-resolution images and analyzed.

Results: qOBM reveals structural differences in the brain blood vessel thickness (thinner for SCD in particular brain regions) and the RI of the vessel wall (higher and containing a larger variation throughout the brain for SCD). These changes were only significant in 20-week-old mice. Further, vessel breakages are observed in SCD mice at both time points. The vessel wall RI distribution near these breaks, up to $350\mu m$ away from the breaking point, shows an erratic behavior characterized by wide RI variations. Vessel diameter, tortuosity, texture within the vessel, and structural fractal patterns are found to not be statistically different. As with vessel breaks, we also observe blood vessel blockages only in mice brains with SCD.

Conclusions: qOBM provides insight into the biophysical and structural composition of brain blood vessels in mice with SCD. Data suggest that the RI may be an indirect indicator of vessel rigidity, vessel strength, and/or tensions, which change with SCD. Future ex vivo and in vivo studies with qOBM could improve our understanding of SCD.

Keywords: cerebral vasculature; label-free imaging; phase microscopy; sickle cell disease.

Fig. 1

(a) Schematic of the qOBM imaging system consisting of an inverted brightfield microscope with epi-illumination. The sample (mouse brain) is sequentially illuminated by four optical fibers connected to 720 nm LEDs, followed by quantitative phase recovery. (b) A schematic demonstrating qOBM’s cross sectional capabilities of a blood vessel filled with cells highlighting the tomographic sectioning capabilities of the system, which can be applied to select the widest part of the vessel as indicated in green. Scale bar is $50\mu \mathrm{m}$, and the gray-scale color map represents the RI properties (denoted with the variable $n$).

Fig. 2

Representative qOBM images illustrating segmentation and calculations. (a) Segmentation of the interior vessel (light green) and the vessel wall (dark green). Examples include regions with a blood vessel largely void of blood cells (top), a vessel completely filled with blood cells (middle), and a vessel containing the junction of multiple vessels (bottom). (b) Blood vessel segmentation performed to calculate the percent fill of a vessel, showing a largely empty vessel (top), a vessel in which individual blood cells can be seen (middle), and a blood vessel packed tightly with blood cells (bottom). Scale bars are $100\mu \mathrm{m}$.

Fig. 3

CoW blood vessel quantitative analysis. (a) Images of the blood vessel junction of the MCA and the ACA on the CoW. The top image (blue) is from an AS mouse, and the bottom image (red) is from an SS mouse. (b) Vessel wall thickness at 6-week-old (top) and 20-week-old (bottom). Here, it is clear that the AS has thicker vessel walls than the sickle cell model. The inset bar graphs show the per-animal averages and data points to visualize the differences between the AS and SS groups. (c) Examples of the MCA/ACA/ICA junction showing the lower average RI in the AS mouse brain (top left) and higher RI in the SS brain (top right). The graph also shows the higher RI of the sickle cell brain for the 20-week-old mice. (d) An analysis of the breaks in the CoW vessels, including two visualizations of breaks along the CoW (left), a graph showing the changing mean RI value as a function of distance from the break (center), and a graph showing the standard deviation as a function of distance from the break (right). Arrows in the left figure point to fragmented high-RI fibers seen along the breaking points. All scale bars are $100\mu \mathrm{m}$.

Fig. 4

Cortex vessel quantitative analysis. (a) Percentage of blood vessels filled with blood cells shows a significant difference between sickle cell vessels versus AS vessels in 6-week-old and 20-week-old mice. (b) Histograms showing the distributions of the blood vessel wall thickness of the AS and SS mice in 6-week-old (top) and 20-week-old mice (bottom). These distributions do not show any statistically significant differences between the AS and SS animals. Though insignificant, one can see a skewness of the graphs showing AS animals with blood vessels with skewed thicknesses greater than those of the SS animals. The inset bar graphs show the per-animal averages and data points to visualize the differences between the AS and SS groups as well as inter-animal homogeneity. (c) (Top) a comparison of the RIs and (bottom) representative visualizations of the RI of an AS cortex vessel (left) versus an SS cortex vessel (right). Note the high RI fibers that can be seen and quantified in the AS and SS vessels as indicated by the white arrows. Scale bars are $100\mu \mathrm{m}$. (d) Box and whisker plot to show the higher standard deviation observed in the SCD animals.