Spatiotemporal analysis of blood plasma and blood cell flow fluctuations of cerebral microcirculation in anesthetized rats.

Cerebral hemodynamics fluctuates spontaneously over broad frequency ranges. However, its spatiotemporal coherence of flow oscillations in cerebral microcirculation remains incompletely understood. The objective of this study was to characterize the spatiotemporal fluctuations of red blood cells (RBCs) and plasma flow in the rat cerebral microcirculation by simultaneously imaging their dynamic behaviors. Comparisons of changes in cross-section diameters between RBC and plasma flow showed dissociations in penetrating arterioles. The results indicate that vasomotion has the least effect on the lateral movement of circulating RBCs, resulting in variable changes in plasma layer thickness. Parenchymal capillaries exhibited slow fluctuations in RBC velocity (0.1 to 0.3 Hz), regardless of capillary diameter fluctuations (<0.1 Hz). Temporal fluctuations and the velocity of RBCs decreased significantly at divergent capillary bifurcations. The results indicate that a transit of RBCs generates flow resistance in the capillaries and that slow velocity fluctuations of the RBCs are subject to a number of bifurcations. In conclusion, the high-frequency oscillation of the blood flow is filtered at the bifurcation through the capillary networks. Therefore, a number of bifurcations in the cerebral microcirculation may contribute to the power of low-frequency oscillations.

Automated capillary flow segmentation and mapping for nailfold video capillaroscopy.

OBJECTIVE: This study aimed to develop an automated image analysis method for segmentation and mapping of capillary flow dynamics captured using nailfold video capillaroscopy (NVC). Methods were applied to compare capillary flow structures and dynamics between young and middle-aged healthy controls. METHODS: NVC images were obtained in a resting state, and a region of the vessel in the image was extracted using a conventional U-Net neural network. The approximate length, diameter, and radius of the curvature were calculated automatically. Flow speed and its fluctuation over time were mapped using the Radon transform and frequency spectrum analysis from the kymograph image created along the vessel's centerline. RESULTS: The diameter of the curve segment (14.4 µm and 13.0 µm) and the interval of two straight segments (13.7 µm and 32.1 µm) of young and middle-aged subjects, respectively, were significantly different. Faster flow was observed in older subjects (0.48 mm/s) than in younger subjects (0.26 mm/s). The power spectral analysis revealed a significant correlation between the high-frequency power spectrum and the flow speed. CONCLUSIONS: The present method allows a spatiotemporal characterization of capillary morphology and flow dynamics with NVC, allowing a wide application such as large-scale health assessment.

Time Series Tracking of Cerebral Microvascular Adaptation to Hypoxia and Hyperoxia Imaged with Repeated In Vivo Two-Photon Microscopy.

The present study describes methodological aspects of image analysis for angiographic image data with long-term two-photon microscopy acquired for the investigation of dynamic changes in the three-dimensional (3D) network structure of the capillaries (less than 8 µm in diameter) in the mouse cerebral cortex. Volume images of the identical capillaries over different periods of days up to 32 days were compared for adaptation under either chronic hypoxia (8-9% O2) or hyperoxia (40-50% O2). We observed that the median diameters of measured capillaries were 5.8, 8.4, 9.0, and 8.4 µm at 0, 1, 2, and 3 weeks during exposure to hypoxia, respectively (N = 1, n = 2193 pairs at day 0), and 5.4, 5.7, 5.4, 6.0, and 6.1 µm measured weekly up to 32 days under hyperoxia (N = 1, n = 1025 pairs at day 0). In accordance with these changes in capillary diameters, tissue space was also observed to change in a depth-dependent manner under hypoxia, but not hyperoxia. The present methods provide us with a method to quantitatively determine three-dimensional vascular and tissue morphology with the aid of a computer-assisted graphical user interface, which facilitates morphometric analysis of the cerebral microvasculature and its correlation with the adaptation of brain cells imaged simultaneously with the microvasculature.

Three-dimensional microvascular network reconstruction from in vivo images with adaptation of the regional inhomogeneity in the signal-to-noise ratio.

OBJECTIVE: Quantification of angiographic images with two-photon laser scanning fluorescence microscopy (2PLSM) relies on proper segmentation of the vascular images. However, the images contain inhomogeneities in the signal-to-noise ratio (SNR) arising from regional effects of light scattering and absorption. The present study developed a semiautomated quantification method for volume images of 2PLSM angiography by adjusting the binarization threshold according to local SNR along the vessel centerlines. METHODS: A phantom model made with fluorescent microbeads was used to incorporate a region-dependent binarization threshold. RESULTS: The recommended SNR for imaging was found to be 4.2-10.6 that provide the true size of imaged objects if the binarization threshold was fixed at 50% of SNR. However, angiographic images in the mouse cortex showed variable SNR up to 45 over the depths. To minimize the errors caused by variable SNR and a spatial extent of the imaged objects in an axial direction, the microvascular networks were three-dimensionally reconstructed based on the cross-sectional diameters measured along the vessel centerline from the XY-plane images with adapted binarization threshold. The arterial volume was relatively constant over depths of 0-500 µm, and the capillary volume (1.7% relative to the scanned volume) showed the larger volumes than the artery (0.8%) and vein (0.6%). CONCLUSIONS: The present methods allow consistent segmentation of microvasculature by adapting the local inhomogeneity in the SNR, which will be useful for quantitative comparison of the microvascular networks, such as under disease conditions where SNR in the 2PLSM images varies over space and time.

Mapping of flow velocity using spatiotemporal changes in time-intensity curves from indocyanine green videoangiography.

OBJECTIVE: The present study developed an image-based analysis method that uses indocyanine green videoangiography (ICG-VA) to measure flow velocity in the arteries and veins of the cortical surface in patients undergoing neurosurgery. METHODS: MATLAB-based code was used to correct motion artifacts in the ICG-VA and determine the time-intensity curve of the ICG. The slope of the initial increase in ICG intensity following the bolus injection was measured and normalized using the predicted input function in the imaging field. Flow velocity over a certain distance determined by the user was measured based on a time shift of the time-intensity curves along the centerline of the vessels. RESULTS: The normalized slope of ICG intensity represented the expected differences in the flow velocity among the artery (0.67 ± 0.05 s-1 ), parenchymal tissue (0.49 ± 0.10 s-1 ), and vein (0.44 ± 0.11 s-1 ). The flow velocities measured along the vessel centerline were 2.5 ± 1.1 cm/s and 1.1 ± 0.3 cm/s in the arteries (0.5 ± 0.2 mm in diameter) and veins (0.6 ± 0.2 mm in diameter), respectively. CONCLUSIONS: An image-based analysis method for ICG-VA was developed to map the expected differences in the flow velocity based on the rising slope of ICG intensity and to measure the absolute flow velocities using the flexible zone and cross-correlation methods.