Fractal analysis of vascular networks : insights from morphogenesis

Considering their extremely complicated and hierarchical structure, a long standing question in vascular physio-pathology is how to characterize blood vessels patterns, including which parameters to use. Another question is how to define a pertinent taxonomy, with applications to normal development and to diagnosis and/or staging of diseases. To address these issues, fractal analysis has been applied by previous investigators to a large variety of healthy or pathologic vascular networks whose fractal dimensions have been sought. A review of the results obtained on healthy vascular networks first shows that no consensus has emerged about whether normal networks must be considered as fractals or not. Based on a review of previous theoretical work on vascular morphogenesis, we argue that these divergences are the signature of a two-step morphogenesis process, where vascular networks form via progressive penetration of arterial and venous quasi-fractal arborescences into a pre-existing homogeneous capillary mesh. Adopting this perspective, we study the multi-scale behavior of generic patterns (model structures constructed as the superposition of homogeneous meshes and quasi-fractal trees) and of healthy intracortical networks in order to determine the artifactual and true components of their multi-scale behavior. We demonstrate that, at least in the brain, healthy vascular structures are a superposition of two components: at low scale, a mesh-like capillary component which becomes homogeneous and space-filling over a cut-off length of order of its characteristic length; at larger scale, quasi-fractal branched (tree-like) structures. Such complex structures are consistent with all previous studies on the multi-scale behavior of vascular structures at different scales, resolving the apparent contradiction about their fractal nature. Consequences regarding the way fractal analysis of vascular networks should be conducted to provide meaningful results are presented. Finally, consequences for vascular morphogenesis or hemodynamics are discussed, as well as implications in case of pathological conditions, such as cancer

Simulation study of brain blood flow regulation by intra-cortical arterioles in an anatomically accurate large human vascular network. Part II: Flow variations induced by global or localized modifications of arteriolar diameters

In a companion paper (Lorthois et al., Neuroimage, inpress),we perform the first simulations of blood flow in an anatomically accurate large human intra-cortical vascular network (~10000 segments), using a 1D non-linear model taking into account the complex rheological properties of blood flow in microcirculation. This model predicts blood pressure, blood flow and hematocrit distributions, volumes of functional vascular territories, regional flow at voxel and network scales, etc. Using the same approach, we study flow reorganizations induced by global arteriolar vasodilations (an isometabolic global increase in cerebral blood flow). For small to moderate global vasodilations, the relationship between changes in volume and changes in flowis in close agreement with Grubb's law, providing a quantitative tool for studying the variations of its exponent with underlying vascular architecture. A significant correlation between blood flow and vascular structure at the voxel scale, practically unchanged with respect to baseline, is demonstrated. Furthermore, the effects of localized arteriolar vasodilations, representative of a local increase in metabolic demand, are analyzed. In particular, localized vasodilations induce flowchanges, including vascular steal, in the neighboring arteriolar trunks at small distances (< 300 μm), while their influence in the neighboring veins is much larger (about 1 mm), which provides an estimate of the vascular point spread function.More generally, for the first time, the hemodynamic component of various functional neuroimaging techniques has been isolated from metabolic and neuronal components, and a direct relationship with several known characteristics of the BOLD signal has been demonstrated

Simulation study of brain blood flow regulation by intra-cortical arterioles in an anatomically accurate large human vascular network : Part I : Methodology and baseline flow

Hemodynamically based functional neuroimaging techniques, such as BOLD fMRI and PET, provide indirect measures of neuronal activity. The quantitative relationship between neuronal activity and the measured signals is not yet precisely known, with uncertainties remaining about the relative contribution by their metabolic and hemodynamic components. Empirical observations have demonstrated the importance of the latter component and suggested that micro-vascular anatomy has a potential influence. The recent development of a 3D computer-assisted method for micro-vascular cerebral network analysis has produced a large quantitative library on the microcirculation of the human cerebral cortex (Cassot et al., 2006), which can be used to investigate the hemodynamic component of brain activation through fluid dynamic modeling. For this purpose, we perform the first simulations of blood flow in an anatomically accurate large human intra-cortical vascular network (~10000 segments), using a 1D non-linear model taking account of the complex rheological properties of blood flow in microcirculation. This model predicts blood pressure, blood flow and hematocrit distributions, as well as volumes of functional vascular territories, and regional flow at voxel and network scales. First, the influence of the prescribed boundary conditions (BCs) on the baseline flow structure is investigated, highlighting relevant lower- and upper-bound BCs. Independent of these BCs, large heterogeneities of baseline flow from vessel to vessel and from voxel to voxel, are demonstrated. These heterogeneities are controlled by the architecture of the intra-cortical vascular network. In particular, a correlation between the blood flow and the proportion of vascular volume occupied by arterioles or venules, at voxel scale, is highlighted. Then, the extent of venous contamination downstream to the sites of neuronal activation is investigated, demonstrating a linear relationship between the catchment surface of the activated area and the diameter of the intra-cortical draining vein

Tortuosity and other vessel attributes for arterioles and venules of the human cerebral cortex

Despite its demonstrated potential in the diagnosis and/or staging of disease, especially in oncology, tortuosity has not received a formal and unambiguous clinical definition yet. Using idealized three-dimensional vessel models (wavy helices) with known characteristics, we first demonstrate that, among various possible tortuosity indices, the standard deviation of the curvature Ksd best satisfies i) scale invariance and ii) positive monotonic response with respect to the amplitude and frequency of vessel oscillations. Ksd can thus be considered as a robust measure of tortuosity. On the contrary, indices previously considered as tortuosity metrics, such as the distance factor metrics (DFM), are highly scale dependent and inappropriate for that purpose. The tortuosity and other vessel attributes (curvature, length-to-diameter ratio (LDR),…) of more than 15,000 cortical vessels are subsequently studied, establishing their statistical properties as a function of the vessel nature (arterioles versus venules) or topological order (hierarchical position). In particular, arterioles have a higher LDR than venules, but the two kinds of vessels have the same mean curvature and tortuosity.Moreover, the lower the order of the vessels, i.e. the nearer to the capillary network, the more curved and tortuous they are. These results provide an essential reference both for diagnosis and for a future large reconstruction of the cerebral microvascular network

Fast macro-scale transmission imaging of microvascular networks using KESM

Accurate microvascular morphometric information has significant implications in several fields, including the quantification of angiogenesis in cancer research, understanding the immune response for neural prosthetics, and predicting the nature of blood flow as it relates to stroke. We report imaging of the whole mouse brain microvascular system at resolutions sufficient to perform accurate morphometry. Imaging was performed using Knife-Edge Scanning Microscopy (KESM) and is the first example of this technique that can be directly applied to clinical research. We are able to achieve ≈ 0.7μm resolution laterally with 1μm depth resolution using serial sectioning. No alignment was necessary and contrast was sufficient to allow segmentation and measurement of vessels

Identifying Vessel Branching from Fluid Stresses on Microscopic Robots

Objects moving in fluids experience patterns of stress on their surfaces determined by the geometry of nearby boundaries. Flows at low Reynolds number, as occur in microscopic vessels such as capillaries in biological tissues, have relatively simple relations between stresses and nearby vessel geometry. Using these relations, this paper shows how a microscopic robot moving with such flows can use changes in stress on its surface to identify when it encounters vessel branches.Comment: Version 2 has minor clarification

Maximal wall shear stress in arterial stenoses: application to the internal carotid arteries

Maximal wall shear stress (MWSS) in the convergent part of a stenosis is calculated by the interactive boundary-layer theory. A dimensional analysis of the problem shows that MWSS depends only on a few measurable parameters. A simple relationship between MWSS and these parameters is obtained, validated, and used to calculate the magnitude of MWSS in a carotid stenosis, as a function of the patency of the circle of Willis and the stenotic pattern. This demonstrates the huge effect of collateral pathways. Elevated MWSS are observed even in moderate stenoses, provided they are associated with a contralateral occlusion, a large anterior, and narrow posterior communicating arteries, suggesting a potential risk of embolus release in this configuration

X-ray micro-tomography and pore network modeling of single-phase fixed-bed reactors.

A three-dimensional (3D) irregular and unstructured pore network was built using local topological and geometrical properties of an isometric bead pack imaged by means of a high-resolution X-ray computed micro-tomography technique. A pore network model was developed to analyze the 3D laminar/inertial(non-Darcy) flows at the mesoscopic (pore level) and macroscopic (after ensemble-averaging) levels. The non-linear laminar flow signatures were captured at the mesoscale on the basis of analogies with contraction and expansion friction losses. The model provided remarkably good predictions of macroscopic frictional loss gradient in Darcy and non-Darcy regimes with clear-cut demarcation using channel-based Reynolds number statistics. It was also able to differentiate contributions due to pore and channel linear losses, and contraction/expansion quadratic losses. Macroscopic mechanical dispersion was analyzed in terms of retroflow channels, and transverse and longitudinal Péclet numbers. The model qualitatively retrieved the Péclet-Reynolds scaling law expected for heterogeneous networks with predominance of mechanical dispersion. Advocated in watermark is the potential of pore network modeling to build a posteriori constitutive relations for the closures of the more conventional macroscopic Euler approaches to capture more realistically single-phase flow phenomena in fixed-bed reactor applications in chemical engineering