Three-dimensional quantification of capillary networks in healthy and cancerous tissues of two mice

Abstract

A key issue in developing strategies against diseases such as cancer is the analysis of the vessel tree in comparison to the healthy one. In the search for parameters that might be characteristic for tumor capillaries we study the vascularization in mice for cancerous and healthy tissues using synchrotron radiation-based micro computed tomography in absorption and phase contrast modes. Our investigations are based on absorption tomograms of casted healthy and cancerous tissues as well as a phase tomogram of a fixated tumor. We demonstrate how the voxel-based tomography data can be vectorized to assess the capillary networks quantitatively. The processing includes segmentation, skeletonization, and vectorization to finally extract the vessel parameters. The mean diameter of capillaries in healthy and cancerous tissues corresponds to (8.0±1.1) μm and (3.9±1.1) μm, respectively. Further evaluated parameters show marginal or no differences between capillaries in healthy and cancerous tissues, namely fractal dimension 2.3±0.3 vs. 2.3±0.2, tortuosity (SOAM) 0.18 rad/μm vs. 0.24 rad/μm and vessel length 20 μm vs. 17 μm. The bifurcation angles exhibit a narrow distribution around 115°. Furthermore, we show that phase tomography is a powerful alternative to absorption tomography of casts for the vessel visualization omitting any invasive specimen preparation procedure.

Multiscale and multi-modality visualization of angiogenesis in a human breast cancer model

“…Due to its high spatial resolution, μCT is able to resolve blood vessels down to the capillary level [23]. Although the 8 μm isotropic resolution μCT employed in this study cannot resolve the smallest capillaries (~2–3 μm diameter) and angiogenic sprouts, we were able to confirm with optical microscopy that μCT could recapitulate the 3D tumor vasculature down to ~8 μm diameter vessels.…”

“…Therefore, we regarded μCT as the ‘gold standard’ for 3D blood vessel visualization in whole tissue specimens. Others have also demonstrated the utility of μCT for quantifying tumor angiogenesis down to the capillary level [23], as well as for validating tumor vascular response to antiangiogenic therapies [24–26]. Moreover, we recently demonstrated μCT’s usefulness as a tool for validating the accuracy of in vivo susceptibility-contrast based MRI biomarkers of breast cancer angiogenesis such as the FBV, vessel size index and vessel density [21].…”

Image-based modelling of skeletal muscle oxygenation

“…In the case of tissue oxygenation these are most importantly the blood vessels which are supplying the oxygen. That is, the flow of oxygen across the boundary between the blood vessels and the muscle tissue needs to be described by the mathematical model (see (4) in figure 3) and therefore the boundary needs to be identified. This identification and extraction of structures in the images is called segmentation.…”

Fractal analysis of cell boundary ultrastructure imaged by atomic force microscopy

“…Indeed, many biological structures such as cells (Bernard et al 2001;Puškaš et al 2015), organs (Goldberger & West 1987), normal tissues (Masters 2004;Lang et al 2012;Guidolin et al 2014), cancerous tissues (Baish & Jain 2000;Klein et al 2013;Lee et al 2014), and even sub-cellular organelles (Sedivy et al 1999;Cherkezyan et al 2014) exhibit fractal properties and have their own D f values, like other natural objects. The presence of such properties in the abovementioned systems suggests that fractal analysis may be a useful tool by which the morphological properties of cellular ultrastructure can be characterized.…”