Fundamental constraints of vessels network architecture properties revealed by reconstruction of a rat brain vasculature

The studies of mammalian vasculature are an essential part of biomedical research, enabling the development of physiological understanding and forming the background of medical techniques and therapy. Despite the fact that the basic principles of vessel network description were established in the first quarter of the twentieth century, a digital model describing the vasculature in full accordance with experimental data has not yet been created. In the present study, we combine the determined structure design of basic arterial vessels with the stochastic creation of small vessel networks. By the example of rat brain arterial network model it was shown that the arterial blood volume and the magnitude of the blood flow impose a limitation on the network architecture. In particular, the bifurcation exponent (γ) should not be less than 2.7, and the optimal value of this parameter lies in the range of 2.9-3.0. Although the networks with a low γ appear as branched and complex, they do not fill out the phantom properly. Thus, the architecture of the vasculature is fundamentally determined by topological geometrical parameters.

A novel method of artery stenosis diagnosis using transfer function and support vector machine based on transmission line model: A numerical simulation and validation study

BACKGROUND AND OBJECTIVE

Transfer function (TF) is an important parameter for the analysis and understanding of hemodynamics when arterial stenosis exists in human arterial tree. Aimed to validate the feasibility of using TF to diagnose arterial stenosis, the forward problem and inverse problem were simulated and discussed.

METHODS

A calculation method of TF between ascending aorta and any other artery was proposed based on a 55 segment transmission line model (TLM) of human artery tree. The effects of artery stenosis on TF were studied in two aspects: stenosis degree and position. The degree of arterial stenosis was specified to be 10-90% in three representative arteries: carotid, aorta and iliac artery, respectively. In order to validate the feasibility of diagnosis of artery stenosis using TF and support vector machine (SVM), a database of TF was established to simulate the real conditions of artery stenosis based on the TLM model. And a diagnosis model of artery stenosis was built by using SVM and the database.

RESULTS

The simulating results showed the modulus and phase of TF were decreasing sharply from frequency 2 to 10Hz with the stenosis degree increasing and displayed their unique and nonlinear characteristics when frequency is higher than 10Hz. The diagnosis results showed the average accuracy was above 76% for the stenosis from 10% to 90% degree, and the diagnosis accuracies of moderate (50%) and serious (90%) stenosis were 87% and 99%, respectively. When the stenosis degree increased to 90%, the accuracy of stenosis localization reached up to 94% for most of arteries.

CONCLUSIONS

The proposed method of combining TF and SVM is a theoretically feasible method for diagnosis of artery stenosis.

Comparison of the Windkessel model and structured-tree model applied to prescribe outflow boundary conditions for a one-dimensional arterial tree model

One-dimensional (1D) modeling is a widely adopted approach for studying wave propagation phenomena in the arterial system. Despite the frequent use of the Windkessel (WK) model to prescribe outflow boundary conditions for 1D arterial tree models, it remains unclear to what extent the inherent limitation of the WK model in describing wave propagation in distal vasculatures affect hemodynamic variables simulated at the arterial level. In the present study, a 1D model of the arterial tree was coupled respectively with a WK boundary model and a structured-tree (ST) boundary model, yielding two types of arterial tree models. The effective resistances, compliances and inductances of the WK and ST boundary models were matched to facilitate quantitative comparisons. Obtained results showed that pressure/flow waves simulated by the two models were comparable in the aorta, whereas, their discrepancies increased towards the periphery. Wave analysis revealed that the differences in reflected waves generated by the boundary models were the major sources of pressure wave discrepancies observed in large arteries. Additional simulations performed under aging conditions demonstrated that arterial stiffening with age enlarged the discrepancies, but with the effects being partly counteracted by physiological aortic dilatation with age. These findings suggest that the method adopted for modeling the outflow boundary conditions has considerable influence on the performance of a 1D arterial tree model, with the extent of influence varying with the properties of the arterial system.

Comparing Carotid and Brachial Artery Stiffness: A First Step Toward Mechanical Mapping of the Arterial Tree

Arterial stiffness is a predictor of cardiovascular mortality. It increases with age and is accelerated by hypertension and other cardiovascular risk factors. In addition to the disease state, arterial stiffness increases from the proximal to the distal arterial compartments. Concurrent assessment of various vessels from the same subjects is unavailable in the literature. The aim of this work was to quantify an intrinsic mechanical feature, namely, wall stiffness, of the common carotid artery (CCA) and brachial artery (BA). CCAs and BAs of healthy adolescents were investigated. Cine loops of CCA and BA B-mode data were digitally recorded at the same clinical examination, and arterial elastic moduli were estimated off-line with our proprietary non-invasive Imaging-based BioMarker (ImBioMark) algorithm. The 11 study subjects were 14.4 ± 1.2 years old, with normal body habitus and blood pressures 112.3 ± 10.6/63.6 ± 5.7 mm Hg. BAs had a higher elastic modulus than CCAs (arterial elastic moduli: 129.73 ± 25.67 kPa vs. 49.55 ± 14.75 kPa, p < 0.001). There was a positive correlation between the BA and CCA (slope = 0.36, intercept = 111.62 kPa, R(2) = 0.045). This article documents, for the first time, a correlation between the CCA and BA of the same subject, under the same conditions. We previously reported preliminary data for the aorta and documented the effect of aging on the CCA; we now intend to study the femoral artery as well and include age stratification to pursue our investigations. The results reported here can be seen as the first step toward mechanical mapping of the arterial tree.