In micro-Particle Image Velocimetry, the requirement of a large field-of-view often results in a large depth-of-correlation, i.e. large depth of the measurement volume. When the velocity varies substantially over the depth-of-correlation, special attention should be paid to a correct interpretation of the measured velocities. When a specialized microscope is needed to meet the requirements of a setup, the resulting more complex optical arrangements can have additional effects on the measurement results. In order to determine flow parameters such as the flow rate, it is sufficient to have a robust estimate of the maximum velocity when the flow is Poiseuille flow. In this paper, an interpretation of the results from particle image velocimetry measurements with low magnification in a round capillary is given for two types of microscopes: a conventional and a specialized microscope. The measured velocity appears to be lower than the maximum velocity, yet is still above the average velocity. The interpretation of the measured velocity differs for the two types of microscopes. The under-estimation of the maximum velocity obtained from the conventional microscope remains small (within 6%) for low-magnification measurements, while the under-estimation of the maximum velocity obtained from the specialized microscope increases up to 25% for a large depth-of-correlation. The images of the in-and outof-focus particles turn out to play a crucial role in this difference between the two microscopes. Validation of the optical properties of a microscope is important, especially for specialized microscopes where particle images deviate substantially from the existing theory, and this theory is also used to derive the analytical expression for the depthof-correlation. A procedure is recommended to obtain a correct interpretation of the measured velocity. This procedure is generally applicable, but mainly of importance for specialized microscopes.

Imaging-based blood flow measurement techniques, such as particle image velocimetry, have become an important tool in cardiovascular research. They provide quantitative information about blood flow, which benefits applications ranging from developmental biology to tumor perfusion studies. Studies using these methods can be classified based on whether they use artificial tracers or red blood cells to visualize the fluid motion. We here present the first direct comparison in vivo of both methods. For high magnification cases, the experiments using red blood cells strongly underestimate the flow (up to 50% in the present case), as compared to the tracer results. For medium magnification cases, the results from both methods are indistinguishable as they give the same underestimation of the real velocities (approximately 33%, based on in vitro reference measurements). These results suggest that flow characteristics reported in literature cannot be compared without a careful evaluation of the imaging characteristics. A method to predict the expected flow averaging behavior for a particular facility is presented.

Since fluid dynamics plays a critical role in vascular remodeling, quantification of the hemodynamics is crucial to gain more insight into this complex process. Better understanding of vascular development can improve prediction of the process, and may eventually even be used to influence the vascular structure. In this study, a methodology to quantify hemodynamics and network structure of developing vascular networks is described. The hemodynamic parameters and topology are derived from detailed local blood flow velocities, obtained by in vivo micro-PIV measurements. The use of such detailed flow measurements is shown to be essential, as blood vessels with a similar diameter can have a large variation in flow rate. Measurements are performed in the yolk sacs of seven chicken embryos at two developmental stages between HH 13+ and 17+. A large range of flow velocities (1 µm/s to 1 mm/s) is measured in blood vessels with diameters in the range of 25–500 µm. The quality of the data sets is investigated by verifying the flow balances in the branching points. This shows that the quality of the data sets of the seven embryos is comparable for all stages observed, and the data is suitable for further analysis with known accuracy. When comparing two subsequently characterized networks of the same embryo, vascular remodeling is observed in all seven networks. However, the character of remodeling in the seven embryos differs and can be non-intuitive, which confirms the necessity of quantification. To illustrate the potential of the data, we present a preliminary quantitative study of key network topology parameters and we compare these with theoretical design rules.

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