he lymphatic system plays an important role in human circulatory and immune homeostasis. Peripheral lymph nodes (LNs) are regional hubs that receive interstitial fluid as well as circulating blood. They contain large numbers of immune cells and the complex internal architecture of LNs constitutes an interface between the cellular and molecular constituents of lymph and blood. Cellular debris is filtered and primary immune responses can be generated in LNs to pathogens (1). LN blood vessels are highly specialized for facilitating T-cell entry to the node (2). The spatial distribution of surface area for exchange of fluid with blood vessels in LNs determines the amount of local fluid movement, and it is therefore important to quantify the three-dimensional distribution of LN blood vessels. In patients with cancer, tumor cells can also traffic through lymphatic channels to regional LNs (3). Recent studies have demonstrated that metastatic cells migrate toward and into LN blood vessels (4,5). Malignant processes are associated with both angiogenesis and lymphangiogenesis (6). LNs may even act as a permissive niche to support the proliferation of metastatic cells and promote movement to distant sites (7). The accurate identification and quantification of metastatic LNs remains essential for prognosis and treatment planning (8).
Effects of fluid dynamics on cells are often studied by growing the cells on the base of cylindrical wells or dishes that are swirled on the horizontal platform of an orbital shaker.The swirling culture medium applies a shear stress to the cells that varies in magnitude and directionality from the center to the edge of the vessel. Computational fluid dynamics methods are used to simulate the flow and hence calculate shear stresses at the base of the well. The shear characteristics at each radial location are then compared with cell behavior at the same position. Previous simulations have generally ignored effects of surface tension and wetting, and results have only occasionally been experimentally validated. We investigated whether such idealized simulations are sufficiently accurate, examining a commonly-used swirling well configuration. The breaking wave predicted by earlier simulations was not seen, and the edge-to-center difference in shear magnitude (but not directionality) almost disappeared, when surface tension and wetting were included. Optical measurements of fluid height and velocity agreed well only with the computational model that incorporated surface tension and wetting. These results demonstrate the importance of including accurate fluid properties in computational models of the swirling well method.
Abnormal blood flow and wall shear stress (WSS) can cause and be caused by cardiovascular disease. To date, however, no standard method has been established for mapping WSS in vivo. Here we demonstrate wide-field assessment of WSS in the rabbit abdominal aorta using contrast-enhanced ultrasound image velocimetry (UIV). Flow and WSS measurements were made independent of beam angle, curvature or branching. Measurements were validated in an in silico model of the rabbit thoracic aorta with moving walls and pulsatile flow. Mean errors over a cardiac cycle for velocity and WSS were 0.34 and 1.69%, respectively. In vivo time average WSS in a straight segment of the suprarenal aorta correlated highly with simulations (PC = 0.99) with a mean deviation of 0.29 Pa or 5.16%. To assess fundamental plausibility of the measurement, UIV WSS was compared to an analytic approximation derived from the Poiseuille equation; the discrepancy was 17%.Mapping of WSS was also demonstrated in regions of arterial branching. High time average WSS (TAWSS xz = 3.4 Pa) and oscillatory flow (OSI xz = 0.3) were observed near the origin of conduit arteries. In conclusion, we have demonstrated that contrast-enhanced UIV is capable of measuring spatiotemporal variation in flow velocity, arterial wall location and hence WSS in vivo with high accuracy over a large field of view.
Perfusion by the microcirculation is key to the development, maintenance and pathology of tissue. Its measurement with high spatiotemporal resolution is consequently valuable but remains a challenge in deep tissue. Ultrasound Localization Microscopy (ULM) provides very high spatiotemporal resolution but the use of microbubbles requires low contrast agent concentrations, a long acquisition time, and gives little control over the spatial and temporal distribution of the microbubbles. The present study is the first to demonstrate Acoustic Wave Sparsely-Activated Localization Microscopy (AWSALM) and fast-AWSALM for in vivo super-resolution ultrasound imaging, offering contrast on demand and vascular selectivity. Three different formulations of acoustically activatable contrast agents were used. We demonstrate their use with ultrasound mechanical indices well within recommended safety limits to enable fast on-demand sparse activation and destruction at very high agent concentrations. We produce super-localization maps of the rabbit renal vasculature with acquisition times between 5.5 s and 0.25 s, and a 4-fold improvement in spatial resolution. We present the unique selectivity of AWSALM in visualizing specific vascular branches and downstream microvasculature, and we show super-localized kidney structures in systole (0.25 s) and diastole (0.25 s) with fast-AWSALM outdoing microbubble based ULM. In conclusion, we demonstrate the feasibility of fast and selective measurement of microvascular dynamics in vivo with subwavelength resolution using ultrasound and acoustically activatable nanodroplet contrast agents.
Being able to measure 3D flow velocity and volumetric flow rate effectively in the cardiovascular system is valuable but remains a significant challenge in both clinical practice and research. Currently there has not been an effective and practical solution to the measurement of volume flow using ultrasound imaging systems due to challenges in existing 3D imaging techniques and high system cost. In this study, a new technique for quantifying volumetric flow rate from the crosssectional imaging plane of the blood vessel was developed by using speckle decorrelation, 2D high frame rate imaging with a standard 1D array transducer, microbubble contrast agents, and ultrasound imaging velocimetry (UIV). Through speckle decorrelation analysis of microbubble signals acquired with a very high frame rate and by using UIV to estimate the two in-plane flow velocity components, the third and out-of-plane velocity component can be obtained over time and integrated to estimate volume flow. The proposed technique was evaluated on a wall-less flow phantom in both steady and pulsatile flow. UIV in the longitudinal direction was conducted as a reference. The influences of frame rate, mechanical index, orientation of imaging plane, and compounding on velocity estimation were also studied. In addition, an in vivo trial on the abdominal aorta of a rabbit was conducted. The results show that the new system can estimate volume flow with an averaged error of 3.65±2.37% at a flow rate of 360 ml/min and a peak velocity of 0.45 m/s, and an error of 5.03±2.73% at a flow rate of 723 ml/min and a peak velocity of 0.8 m/s. The accuracy of the flow velocity and volumetric flow rate estimation directly depend on the imaging frame rate. With a frame rate of 6000 Hz, a velocity up to 0.8 m/s can be correctly estimated. A higher mechanical index (MI=0.42) is shown to produce greater errors (up to 21.78±0.49%, compared to 3.65±2.37% at MI=0.19). An in vivo trial, where velocities up to 1 m/s were correctly measured, demonstrated the potential of the technique in clinical applications.
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