Limited bifurcation asymmetry in coronary arterial tree models generated by constrained constructive optimization

Review of cardiac-coronary interaction and insights from mathematical modeling

Cardiac-coronary interaction is fundamental to the function of the heart. As one of the highest metabolic organs in the body, the cardiac oxygen demand is met by blood perfusion through the coronary vasculature. The coronary vasculature is largely embedded within the myocardial tissue which is continually contracting and hence squeezing the blood vessels. The myocardium-coronary vessel interaction is two-ways and complex. Here, we review the different types of cardiac-coronary interactions with a focus on insights gained from mathematical models. Specifically, we will consider the following: (1) myocardial-vessel mechanical interaction; (2) metabolic-flow interaction and regulation; (3) perfusion-contraction matching, and (4) chronic interactions between the myocardium and coronary vasculature. We also provide a discussion of the relevant experimental and clinical studies of different types of cardiac-coronary interactions. Finally, we highlight knowledge gaps, key challenges, and limitations of existing mathematical models along with future research directions to understand the unique myocardium-coronary coupling in the heart. This article is categorized under: Cardiovascular Diseases > Computational Models Cardiovascular Diseases > Biomedical Engineering Cardiovascular Diseases > Molecular and Cellular Physiology.

A Hybrid Model for Cardiac Perfusion: Coupling a Discrete Coronary Arterial Tree Model with a Continuous Porous-Media Flow Model of the Myocardium

This paper presents a novel hybrid approach for the computational modeling of cardiac perfusion, combining a discrete model of the coronary arterial tree with a continuous porous-media flow model of the myocardium. The constructive constrained optimization (CCO) algorithm captures the detailed topology and geometry of the coronary arterial tree network, while Poiseuille's law governs blood flow within this network. Contrast agent dynamics, crucial for cardiac MRI perfusion assessment, are modeled using reaction-advection-diffusion equations within the porous-media framework. The model incorporates fibrosis-contrast agent interactions and considers contrast agent recirculation to simulate myocardial infarction and Gadolinium-based late-enhancement MRI findings. Numerical experiments simulate various scenarios, including normal perfusion, endocardial ischemia resulting from stenosis, and myocardial infarction. The results demonstrate the model's efficacy in establishing the relationship between blood flow and stenosis in the coronary arterial tree and contrast agent dynamics and perfusion in the myocardial tissue. The hybrid model enables the integration of information from two different exams: computational fractional flow reserve (cFFR) measurements of the heart coronaries obtained from CT scans and heart perfusion and anatomy derived from MRI scans. The cFFR data can be integrated with the discrete arterial tree, while cardiac perfusion MRI data can be incorporated into the continuum part of the model. This integration enhances clinical understanding and treatment strategies for managing cardiovascular disease.

Fractal analysis of perfusion imaging in synovitis: a novel imaging biomarker for grading inflammatory activity based on assessing angiogenesis

Objectives

The mutual and intertwined dependence of inflammation and angiogenesis in synovitis is widely acknowledged. However, no clinically established tool for objective and quantitative assessment of angiogenesis is routinely available. This study establishes fractal analysis as a novel method to quantitatively assess inflammatory activity based on angiogenesis in synovitis.

Methods

First, we established a pathophysiological framework for synovitis including fractal analysis of software perfusion phantoms, which allowed to derive explainability with a known and controllable reference standard for vascular structure. Second, we acquired MRI datasets of patients with suspected rheumatoid arthritis of the hand, and three imaging experts independently assessed synovitis analogue to Rheumatoid Arthritis MRI Scoring (RAMRIS) criteria. Finally, we performed fractal analysis of dynamic first-pass perfusion MRI in vivo to evaluate angiogenesis in relation to inflammatory activity with RAMRIS as reference standard.

Results

Fractal dimension (FD) achieved highly significant discriminability for different degrees of inflammatory activity (p<0.01) in software phantoms with known ground-truth of angiogenic structure. FD indicated increasingly chaotic perfusion patterns with increasing grades of inflammatory activity (Spearman’s ρ=0.94, p<0.001). In 36 clinical patients, fractal analysis quantitatively and objectively discriminated individual RAMRIS scores (p≤0.05). Area under the receiver-operating curve was 0.84 (95% CI 0.7 to 0.89) for fractal analysis when considering RAMRIS as ground-truth. Fractal analysis additionally identified angiogenesis in cases where RAMRIS underestimated inflammatory activity.

Conclusions

Based on angiogenesis and perfusion pathophysiology, fractal analysis non-invasively enables comprehensive, objective and quantitative characterisation of inflammatory angiogenesis with subjective and qualitative RAMRIS as reference standard. Further studies are required to establish the clinical value of fractal analysis for diagnosis, prognostication and therapy monitoring in inflammatory arthritis.

Mathematical synthesis of the cortical circulation for the whole mouse brain-part II: Microcirculatory closure

Recent advancements in multiphoton imaging and vascular reconstruction algorithms have increased the amount of data on cerebrovascular circulation for statistical analysis and hemodynamic simulations. Experimental observations offer fundamental insights into capillary network topology but mainly within a narrow field of view typically spanning a small fraction of the cortical surface (less than 2%). In contrast, larger-resolution imaging modalities, such as computed tomography (CT) or magnetic resonance imaging (MRI), have whole-brain coverage but capture only larger blood vessels, overlooking the microscopic capillary bed. To integrate data acquired at multiple length scales with different neuroimaging modalities and to reconcile brain-wide macroscale information with microscale multiphoton data, we developed a method for synthesizing hemodynamically equivalent vascular networks for the entire cerebral circulation. This computational approach is intended to aid in the quantification of patterns of cerebral blood flow and metabolism for the entire brain. In part I, we described the mathematical framework for image-guided generation of synthetic vascular networks covering the large cerebral arteries from the circle of Willis through the pial surface network leading back to the venous sinuses. Here in part II, we introduce novel procedures for creating microcirculatory closure that mimics a realistic capillary bed. We demonstrate our capability to synthesize synthetic vascular networks whose morphometrics match empirical network graphs from three independent state-of-the-art imaging laboratories using different image acquisition and reconstruction protocols. We also successfully synthesized twelve vascular networks of a complete mouse brain hemisphere suitable for performing whole-brain blood flow simulations. Synthetic arterial and venous networks with microvascular closure allow whole-brain hemodynamic predictions. Simulations across all length scales will potentially illuminate organ-wide supply and metabolic functions that are inaccessible to models reconstructed from image data with limited spatial coverage.

Adaptive constrained constructive optimisation for complex vascularisation processes

Mimicking angiogenetic processes in vascular territories acquires importance in the analysis of the multi-scale circulatory cascade and the coupling between blood flow and cell function. The present work extends, in several aspects, the Constrained Constructive Optimisation (CCO) algorithm to tackle complex automatic vascularisation tasks. The main extensions are based on the integration of adaptive optimisation criteria and multi-staged space-filling strategies which enhance the modelling capabilities of CCO for specific vascular architectures. Moreover, this vascular outgrowth can be performed either from scratch or from an existing network of vessels. Hence, the vascular territory is defined as a partition of vascular, avascular and carriage domains (the last one contains vessels but not terminals) allowing one to model complex vascular domains. In turn, the multi-staged space-filling approach allows one to delineate a sequence of biologically-inspired stages during the vascularisation process by exploiting different constraints, optimisation strategies and domain partitions stage by stage, improving the consistency with the architectural hierarchy observed in anatomical structures. With these features, the aDaptive CCO (DCCO) algorithm proposed here aims at improving the modelled network anatomy. The capabilities of the DCCO algorithm are assessed with a number of anatomically realistic scenarios.

Image-based morphometric studies of human coronary artery bifurcations with/without coronary artery disease

It is of great clinical significance to study the relationship between coronary bifurcation's morphometrical feature change and coronary artery disease (CAD) lesion. The purpose of this study is to determine the morphological changes in patients with CAD lesion when compared with non-CAD subjects and to find indicators that may be used for cardiovascular disease diagnosis. Computed tomography angiography images from Southern Chinese populations were used to reconstruct three-dimensional coronary arterial trees. Murray's law was introduced to assess the level of deviation of the realistic vascular networks from their optimal state. The results showed CAD Left had the highest deviation values of ARR (0.2552 ± 0.0071 ) and DERR (0.5059 ± 0.0098 ), while non-CAD Right had the lowest values (ARR : 0.1892 ± 0.0066 and DERR : 0.3733 ± 0.0092 , respectively). Moreover, the slope values of the ratio between D m 3 and D s 3 + D l 3 for non-CAD Left, CAD Left, non-CAD Right, and CAD Right were 0.7428, 0.7004, 0.7628, and 0.7577, respectively. Theoretically, the slope value should equal to 1 when the bifurcation structure is in its optimal state. Therefore, these results indicated that coronary bifurcations with CAD lesion deviated from the optimal structure further than those without CAD lesion and coronary bifurcations in right were closer to the optimal structure than those in left. More importantly, the present study found that DERR and AER depended only on the diseased state, but not age, suggesting that DERR and AER were potentially used as two novel indicators for early CAD diagnosis.

3D Printable Vascular Networks Generated by Accelerated Constrained Constructive Optimization for Tissue Engineering

One of the greatest challenges in fabricating artificial tissues and organs is the incorporation of vascular networks to support the biological requirements of the embedded cells, encouraging tissue formation and maturation. With the advent of 3D printing technology, significant progress has been made with respect to generating vascularized artificial tissues. Current algorithms to generate arterial/venous trees are computationally expensive and offer limited freedom to optimize the resulting structures. Furthermore, there is no method for algorithmic generation of vascular networks that can recapitulate the complexity of the native vasculature for more than two trees, and export directly to a 3D printing format. Here, we report such a method, using an accelerated constructive constrained optimization approach, by decomposing the process into construction, optimization, and collision resolution stages. The new approach reduces computation time to minutes at problem sizes where previous implementations have reported days. With the optimality criterion of maximizing the volume of useful tissue which could be grown around such a network, an approach of alternating stages of construction and batch optimization of all node positions is introduced and shown to yield consistently more optimal networks. The approach does not place a limit on the number of interpenetrating networks that can be constructed in a given space; indeed we demonstrate a biomimetic, liver-like tissue model. Methods to account for the limitations of 3D printing are provided, notably the minimum feature size and infill at sharp angles, through padding and angle reduction, respectively.

Development of a globally optimised model of the cerebral arteries

The cerebral arteries are difficult to reproduce from first principles, featuring interwoven territories, and intricate layers of grey and white matter with differing metabolic demand. The aim of this study was to identify the ideal configuration of arteries required to sustain an entire brain hemisphere based on minimisation of the energy required to supply the tissue. The 3D distribution of grey and white matter within a healthy human brain was first segmented from magnetic resonance images. A novel simulated annealing algorithm was then applied to determine the optimal configuration of arteries required to supply brain tissue. The model was validated through comparison of this ideal, entirely optimised, brain vasculature with the structure and properties of real arteries. This analysis established that the human cerebral vasculature is highly optimised; closely resembling the most energy efficient arrangement of vessels. In addition to local adherence to fluid dynamical optimisation principles, the optimised vasculature reproduced expected brain perfusion territories, featuring well-defined boundaries between anterior, middle and posterior regions. This validated brain vascular model and algorithm can be used for patient-specific modelling of stroke and cerebral haemodynamics, identification of sub-optimal conditions associated with vascular disease, and optimising vascular structures for tissue engineering applications and artificial organ design.

Mathematical synthesis of the cortical circulation for the whole mouse brain-part I. theory and image integration

Microcirculation plays a significant role in cerebral metabolism and blood flow control, yet explaining and predicting functional mechanisms remains elusive because it is difficult to make physiologically accurate mathematical models of the vascular network. As a precursor to the human brain, this paper presents a computational framework for synthesizing anatomically accurate network models for the cortical blood supply in mouse. It addresses two critical deficiencies in cerebrovascular modeling. At the microscopic length scale of individual capillaries, we present a novel synthesis method for building anatomically consistent capillary networks with loops and anastomoses (=microcirculatory closure). This overcomes shortcomings in existing algorithms which are unable to create closed circulatory networks. A second critical innovation allows the incorporation of detailed anatomical features from image data into vascular growth. Specifically, computed tomography and two photon laser scanning microscopy data are input into the novel synthesis algorithm to build the cortical circulation for the entire mouse brain in silico. Computer predictions of blood flow and oxygen exchange executed on synthetic large-scale network models are expected to elucidate poorly understood functional mechanisms of the cerebral circulation.

Simulated annealing approach to vascular structure with application to the coronary arteries

Do the complex processes of angiogenesis during organism development ultimately lead to a near optimal coronary vasculature in the organs of adult mammals? We examine this hypothesis using a powerful and universal method, built on physical and physiological principles, for the determination of globally energetically optimal arterial trees. The method is based on simulated annealing, and can be used to examine arteries in hollow organs with arbitrary tissue geometries. We demonstrate that the approach can generate in silico vasculatures which closely match porcine anatomical data for the coronary arteries on all length scales, and that the optimized arterial trees improve systematically as computational time increases. The method presented here is general, and could in principle be used to examine the arteries of other organs. Potential applications include improvement of medical imaging analysis and the design of vascular trees for artificial organs.

Toward an optimal design principle in symmetric and asymmetric tree flow networks

Fluid flow in tree-shaped networks plays an important role in both natural and engineered systems. This paper focuses on laminar flows of Newtonian and non-Newtonian power law fluids in symmetric and asymmetric bifurcating trees. Based on the constructal law, we predict the tree-shaped architecture that provides greater access to the flow subjected to the total network volume constraint. The relationships between the sizes of parent and daughter tubes are presented both for symmetric and asymmetric branching tubes. We also approach the wall-shear stresses and the flow resistance in terms of first tube size, degree of asymmetry between daughter branches, and rheological behavior of the fluid. The influence of tubes obstructing the fluid flow is also accounted for. The predictions obtained by our theory-driven approach find clear support in the findings of previous experimental studies.

A computational approach to generate concurrent arterial networks in vascular territories

In this work, a computational procedure is proposed to vascularize anatomical regions supplied by many inflow sites. The proposed methodology creates a partition of the territory to be vascularized into nonoverlapping subdomains that are independently supplied by the so-called perforator arteries (inflow sites). Then, in each subdomain, the constrained constructive optimization method is used to generate a network of vessels. The identification of subdomains in a certain vascular territory perfused by many perforator arteries turns out to be a fundamental problem towards understanding the morphological conformation of peripheral beds in the cardiovascular system. The methodology is assessed through two academic examples showing the main structural features of the so-defined vascular territory partition and the corresponding arterial networks. In addition, the vascularization of a three-dimensional sheet-like tissue is presented with potential application in flap planning and design.

Comparative structural and hemodynamic analysis of vascular trees

The availability of detailed three-dimensional images of vascular trees from mammalian organs provides a wealth of essential data for understanding the processes and mechanisms of vascular patterning. Using this detailed geometric data requires the ability to compare individual representations of vascular trees in statistically meaningful ways. This article provides some comparisons of geometry and also of simulated hemodynamics, enabling the identification of similarities and differences among 10 individual specimens (5 placenta specimens and 5 lung specimens). Similar comparisons made with a series of models (starting with the simplest and increasing in complexity) enable the identification of essential features that are needed to account for the patterns and function of vascular arborization.

Error estimation of geometrical data obtained by histomorphometry of oblique vessel sections: a computer model study

The errors of radius and wall thickness of a single vessel due to oblique sectioning in histomorphometry are expressed as a function of the circular shape factor (CSF) of the section's lumen, assuming cylindrical geometry and the absence of tissue deformation. Using computer model trees generated by constrained constructive optimization, mean errors are estimated for an ensemble of vessel segments. A geometrical exclusion criterion for segments cut too obliquely is defined on the basis of a CSF-cutoff value. It is shown that CSF-values ranging from 0.95 to 0.9 are reasonable choices for a cutoff and lead to mean errors of the same order of magnitude (9.6% [9.3%] to 15.4% [14.8%] for the radius [wall thickness]) as errors due to histological tissue processing.

Optimized arterial trees supplying hollow organs

Computer models of arterial trees can be generated from optimization principles using the algorithm of constrained constructive optimization (CCO). Up to now this algorithm could handle only tissue areas of convex shape, without concavities. CCO is now generalized to cope also with non-convex organ shapes, possibly featuring external as well as internal concavities. This allows the modeling of a much larger class of interesting real arterial systems. The concept of a generalized domain-potential was developed to represent arbitrary non-convex shapes mathematically and incorporate them as boundary conditions to optimization. Domain-potentials may be derived from analytical representations as well as from finite element triangulations obtained from organ images. To demonstrate the feasibility of the concept, the optimized growth of an arterial tree model is confined to some part of an elliptical shell, representing the free wall of the left ventricle of the heart.

Heterogeneous perfusion is a consequence of uniform shear stress in optimized arterial tree models

Using optimized computer models of arterial trees we demonstrate that flow heterogeneity is a necessary consequence of a uniform shear stress distribution. Model trees are generated and optimized under different modes of boundary conditions. In one mode flow is delivered to the tissue as homogeneously as possible. Although this primary goal can be achieved, resulting shear stresses between blood and the vessel walls show very large spread. In a second mode, models are optimized under the condition of uniform shear stress in all segments which in turn renders flow distribution heterogeneous. Both homogeneous perfusion and uniform shear stress are desirable goals in real arterial trees but each of these goals can only be approached at the expense of the other. While the present paper refers only to optimized models, we assume that this dual relation between the heterogeneities in flow and shear stress may represent a more general principle of vascular systems.

On the principles of the vascular network branching

We propose an explanation of Murray's law without applying the minimality principles. The model deals with a "delivering" artery system of an organ that is characterized, first, by the space-filling embedding into the organ tissue and, second, by the uniform distribution of the blood pressure drop over it. The latter assumption is justified using the available physiological data and the idea about conditions needed for perfect self-regulation. Based on the two statements we get Murray's law, and so, demonstrate that it can be also regarded as a direct consequence of the organism's capacity for controlling finely the blood flow redistribution over peripheral vascular networks.

Functional characteristics of optimized arterial tree models perfusing volumes of different thickness and shape

The relationship between the 'shape of an organ' and the 'cost of blood transport' to perfuse its tissue was evaluated on the basis of optimized arterial model trees simulated to perfuse square-based 100-cm(3) volumes of different shape ('flat' versus 'thick' as defined by the ratio of thickness to side-length h/s < or =1). Specifically, the effects of 'shape' on tree structure, blood transport, and on hemodynamic characteristics were investigated. Branching models of arterial trees were generated by constrained constructive optimization (CCO), based on an identical set of model parameters. All model trees were geometrically and topologically optimized for intravascular volume. Tree structures achieved tremendous savings of blood (transport medium) in comparison to a system of separate tubes. Thickening the perfusion volume (increasing h/s) resulted in a significant decrease of mean transport length, deposition time, and intravascular total volume in the tree. 'Thick' perfusion volumes induced CCO trees to branch more symmetrically into a number of equivalent subtrees repetitiously splitting into smaller ones; 'flat' structures were dominated throughout by a few asymmetrically branching major vessels. In summary, we conclude from systematic variation of shape that thicker perfusion volumes (h/s >0.1) facilitate efficient delivery of blood in comparison to large amounts of 'dead volume' to be carried over long distances in very thin pieces of tissue.

Structure-function relationships in the pulmonary arterial tree

Knowledge of the relationship between structure and function of the normal pulmonary arterial tree is necessary for understanding normal pulmonary hemodynamics and the functional consequences of the vascular remodeling that accompanies pulmonary vascular diseases. In an effort to provide a means for relating the measurable vascular geometry and vessel mechanics data to the mean pressure-flow relationship and longitudinal pressure profile, we present a mathematical model of the pulmonary arterial tree. The model is based on the observation that the normal pulmonary arterial tree is a bifurcating tree in which the parent-to-daughter diameter ratios at a bifurcation and vessel distensibility are independent of vessel diameter, and although the actual arterial tree is quite heterogeneous, the diameter of each route, through which the blood flows, tapers from the arterial inlet to essentially the same terminal arteriolar diameter. In the model the average route is represented as a tapered tube through which the blood flow decreases with distance from the inlet because of the diversion of flow at the many bifurcations along the route. The taper and flow diversion are expressed in terms of morphometric parameters obtained using various methods for summarizing morphometric data. To help put the model parameter values in perspective, we applied one such method to morphometric data obtained from perfused dog lungs. Model simulations demonstrate the sensitivity of model pressure-flow relationships to variations in the morphometric parameters. Comparisons of simulations with experimental data also raise questions as to the "hemodynamically" appropriate ways to summarize morphometric data.

A three-dimensional model for arterial tree representation, generated by constrained constructive optimization

The computational method of constrained constructive optimization (CCO) has been generalized in two important respects: (1) arterial model trees are now grown within a convex, three-dimensional piece of tissue and (2) terminal flow variability has been incorporated into the model to account for the heterogeneity of blood flow observed in real vascular beds. Although no direct information from topographic anatomy enters the model, computer-generated CCO trees closely resemble corrosion casts of real arterial trees, both on a visual basis and with regard to morphometric parameters. Terminal flow variability was found to induce transitions in the connective structure early in the trees' development. The present generalization of CCO offers--for the first time--the possibility to generate optimized arterial model trees in three dimensions, representing a realistic geometrical substrate for hemodynamic simulation studies. With the implementation of terminal flow variability the model is ready to simulate processes such as the adaptation of arterial diameters to changes in blood flow rate or the formation of different patterns of angiogenesis induced by changing needs of blood supply.