Abstract
We study the problem of segmenting, reconstructing, and analyzing the structure growth of thrombi (clots) in blood vessels in vivo based on 2-photon microscopic image data. First, we develop an algorithm for segmenting clots in 3D microscopic images based on density-based clustering and methods for dealing with imaging artifacts. Next, we apply the union-of-balls (or alpha-shape) algorithm to reconstruct the boundary of clots in 3D. Finally, we perform experimental studies and analysis on the reconstructed clots and obtain quantitative data of thrombus growth and structures. We conduct experiments on laser-induced injuries in vessels of two types of mice (the wild type and the type with low levels of coagulation factor VII) and analyze and compare the developing clot structures based on their reconstructed clots from image data. The results we obtain are of biomedical significance. Our quantitative analysis of the clot composition leads to better understanding of the thrombus development, and is valuable to the modeling and verification of computational simulation of thrombogenesis.
Highlights
Upon vascular injury, to prevent blood loss following a break in the blood vessel, components in the blood and vessel wall interact rapidly to form a thrombus to limit hemorrhage
Direct laser-induced injuries are made in the mesentery veins of mice that either are normal or have different levels of coagulation factor VII
In addition to the confocal video microscopy in one plane, we can generate a vertical stack of 2-photon images that can be compiled to form a 3D reconstruction of thrombi
Summary
To prevent blood loss following a break in the blood vessel, components in the blood and vessel wall interact rapidly to form a thrombus (clot) to limit hemorrhage. Qualitative and, more importantly, quantitative analysis of the structures of developing thrombi formed in vivo is of significant biomedical importance. Such analysis can help identifying the factors altering thrombus growth and the structures affecting thrombus instability. There is a need for computer-based methods for automatically analyzing 3D microscopic images of thrombi (i.e., stacks of 2D image slices of thrombus cross-sections). Such algorithms must be efficient, accurate, and robust, and be able to handle large quantities of high-resolution 3D image data for quantitative analysis. In our multidisciplinary research, such algorithms can help us advance thrombus studies by providing a vital connection between the biological experimental models and the multiscale computational models of thrombogenesis (e.g., [1, 2])
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