A mathematical model of venous neointimal hyperplasia formation

Computational modeling of in-stent restenosis: Pharmacokinetic and pharmacodynamic evaluation

Persistence of the pathology of in-stent restenosis even with the advent of drug-eluting stents warrants the development of highly resolved in silico models. These computational models assist in gaining insights into the transient biochemical and cellular mechanisms involved and thereby optimize the stent implantation parameters. Within this work, an already established fully-coupled Lagrangian finite element framework for modeling the restenotic growth is enhanced with the incorporation of endothelium-mediated effects and pharmacological influences of rapamycin-based drugs embedded in the polymeric layers of the current generation drug-eluting stents. The continuum mechanical description of growth is further justified in the context of thermodynamic consistency. Qualitative inferences are drawn from the model developed herein regarding the efficacy of the level of drug embedment within the struts as well as the release profiles adopted. The framework is then intended to serve as a tool for clinicians to tune the interventional procedures patient-specifically.

Multiscale Computational Modeling of Vascular Adaptation: A Systems Biology Approach Using Agent-Based Models

The widespread incidence of cardiovascular diseases and associated mortality and morbidity, along with the advent of powerful computational resources, have fostered an extensive research in computational modeling of vascular pathophysiology field and promoted in-silico models as a support for biomedical research. Given the multiscale nature of biological systems, the integration of phenomena at different spatial and temporal scales has emerged to be essential in capturing mechanobiological mechanisms underlying vascular adaptation processes. In this regard, agent-based models have demonstrated to successfully embed the systems biology principles and capture the emergent behavior of cellular systems under different pathophysiological conditions. Furthermore, through their modular structure, agent-based models are suitable to be integrated with continuum-based models within a multiscale framework that can link the molecular pathways to the cell and tissue levels. This can allow improving existing therapies and/or developing new therapeutic strategies. The present review examines the multiscale computational frameworks of vascular adaptation with an emphasis on the integration of agent-based approaches with continuum models to describe vascular pathophysiology in a systems biology perspective. The state-of-the-art highlights the current gaps and limitations in the field, thus shedding light on new areas to be explored that may become the future research focus. The inclusion of molecular intracellular pathways (e.g., genomics or proteomics) within the multiscale agent-based modeling frameworks will certainly provide a great contribution to the promising personalized medicine. Efforts will be also needed to address the challenges encountered for the verification, uncertainty quantification, calibration and validation of these multiscale frameworks.

Effects of the Haemodynamic Stimulus on the Location of Carotid Plaques Based on a Patient-Specific Mechanobiological Plaque Atheroma Formation Model

In this work, we propose a mechanobiological atheroma growth model modulated by a new haemodynamic stimulus. To test this model, we analyse the development of atheroma plaques in patient-specific bifurcations of carotid arteries for a total time of 30 years. In particular, eight geometries (left or right carotid arteries) were segmented from clinical images and compared with the solutions obtained computationally to validate the model. The influence of some haemodynamical stimuli on the location and size of plaques is also studied. Plaques predicted by the mechanobiological models using the time average wall shear stress (TAWSS), the oscillatory shear index (OSI) and a new index proposed in this work are compared. The new index predicts the shape index of the endothelial cells as a combination of TAWSS and OSI values and was fitted using data from the literature. The mechanobiological model represents an evolution of the one previously proposed by the authors. This model uses Navier-Stokes equations to simulate blood flow along the lumen in the transient mode. It also employs Darcy's law and Kedem-Katchalsky equations for plasma and substance flow across the endothelium using the three-pore model. The mass balances of all the substances that have been considered in the model are implemented by convection-diffusion-reaction equations, and finally the growth of the plaques has been computed. The results show that by using the new mechanical stimulus proposed in this study, prediction of plaques is, in most cases, better than only using TAWSS or OSI with a minimal and maximal errors on stenosis ratio of 2.77 and 32.89 %, respectively. However, there are a few geometries in which haemodynamics cannot predict the location of plaques, and other biological or genetic factors would be more relevant than haemodynamics. In particular, the model predicts correctly eleven of the fourteen plaques presented in all the geometries considered. Additionally, a healthy geometry has been computed to check that plaque is not developed with the model in this case.

A computational bio-chemo-mechanical model of in vivo tissue-engineered vascular graft development

Stenosis is the primary complication of current tissue-engineered vascular grafts used in pediatric congenital cardiac surgery. Murine models provide considerable insight into the possible mechanisms underlying this situation, but they are not efficient for identifying optimal changes in scaffold design or therapeutic strategies to prevent narrowing. In contrast, computational modeling promises to enable time- and cost-efficient examinations of factors leading to narrowing. Whereas past models have been limited by their phenomenological basis, we present a new mechanistic model that integrates molecular- and cellular-driven immuno- and mechano-mediated contributions to in vivo neotissue development within implanted polymeric scaffolds. Model parameters are inferred directly from in vivo measurements for an inferior vena cava interposition graft model in the mouse that are augmented by data from the literature. By complementing Bayesian estimation with identifiability analysis and simplex optimization, we found optimal parameter values that match model outputs with experimental targets and quantify variability due to measurement uncertainty. Utility is illustrated by parametrically exploring possible graft narrowing as a function of scaffold pore size, macrophage activity, and the immunomodulatory cytokine transforming growth factor beta 1 (TGF-β1). The model captures salient temporal profiles of infiltrating immune and synthetic cells and associated secretion of cytokines, proteases, and matrix constituents throughout neovessel evolution, and parametric studies suggest that modulating scaffold immunogenicity with early immunomodulatory therapies may reduce graft narrowing without compromising compliance.

Simulation of atherosclerotic plaque growth using computational biomechanics and patient-specific data

Atherosclerosis is the one of the major causes of mortality worldwide, urging the need for prevention strategies. In this work, a novel computational model is developed, which is used for simulation of plaque growth to 94 realistic 3D reconstructed coronary arteries. This model considers several factors of the atherosclerotic process even mechanical factors such as the effect of endothelial shear stress, responsible for the initiation of atherosclerosis, and biological factors such as the accumulation of low and high density lipoproteins (LDL and HDL), monocytes, macrophages, cytokines, nitric oxide and formation of foams cells or proliferation of contractile and synthetic smooth muscle cells (SMCs). The model is validated using the serial imaging of CTCA comparing the simulated geometries with the real follow-up arteries. Additionally, we examine the predictive capability of the model to identify regions prone of disease progression. The results presented good correlation between the simulated lumen area (P < 0.0001), plaque area (P < 0.0001) and plaque burden (P < 0.0001) with the realistic ones. Finally, disease progression is achieved with 80% accuracy with many of the computational results being independent predictors.

A multiphase model of growth factor-regulated atherosclerotic cap formation

Atherosclerosis is characterised by the growth of fatty plaques in the inner artery wall. In mature plaques, vascular smooth muscle cells (SMCs) are recruited from adjacent tissue to deposit a collagenous cap over the fatty plaque core. This cap isolates the thrombogenic plaque content from the bloodstream and prevents the clotting cascade that leads to myocardial infarction or stroke. Despite the protective role of the cap, the mechanisms that regulate cap formation and maintenance are not well understood. It remains unclear why some caps become stable, while others become vulnerable to rupture. We develop a multiphase PDE model with non-standard boundary conditions to investigate collagen cap formation by SMCs in response to diffusible growth factor signals from the endothelium. Platelet-derived growth factor stimulates SMC migration, proliferation and collagen degradation, while transforming growth factor (TGF)-[Formula: see text] stimulates SMC collagen synthesis and inhibits collagen degradation. The model SMCs respond haptotactically to gradients in the collagen phase and have reduced rates of migration and proliferation in dense collagenous tissue. The model, which is parameterised using in vivo and in vitro experimental data, reproduces several observations from plaque growth in mice. Numerical and analytical results demonstrate that a stable cap can be formed by a relatively small SMC population and emphasise the critical role of TGF-[Formula: see text] in effective cap formation. These findings provide unique insight into the mechanisms that may lead to plaque destabilisation and rupture. This work represents an important step towards the development of a comprehensive in silico plaque model.

Mathematical modelling of the restenosis process after stent implantation

The stenting procedure has evolved to become a highly successful technique for the clinical treatment of advanced atherosclerotic lesions in arteries. However, the development of in-stent restenosis remains a key problem. In this work, a novel two-dimensional continuum mathematical model is proposed to describe the complex restenosis process following the insertion of a stent into a coronary artery. The biological species considered to play a key role in restenosis development are growth factors, matrix metalloproteinases, extracellular matrix, smooth muscle cells and endothelial cells. Diffusion-reaction equations are used for modelling the mass balance between species in the arterial wall. Experimental data from the literature have been used in order to estimate model parameters. Moreover, a sensitivity analysis has been performed to study the impact of varying the parameters of the model on the evolution of the biological species. The results demonstrate that this computational model qualitatively captures the key characteristics of the lesion growth and the healing process within an artery subjected to non-physiological mechanical forces. Our results suggest that the arterial wall response is driven by the damage area, smooth muscle cell proliferation and the collagen turnover among other factors.

A two-phase model of early fibrous cap formation in atherosclerosis

Atherosclerotic plaque growth is characterised by chronic, non-resolving inflammation that promotes the accumulation of cellular debris and extracellular fat in the inner artery wall. This material is highly thrombogenic, and plaque rupture can lead to the formation of blood clots that occlude major arteries and cause myocardial infarction or stroke. In advanced plaques, vascular smooth muscle cells (SMCs) are recruited from deeper in the artery wall to synthesise a cap of fibrous tissue that stabilises the plaque and sequesters the thrombogenic plaque content from the bloodstream. The fibrous cap provides crucial protection against the clinical consequences of atherosclerosis, but the mechanisms of cap formation are poorly understood. In particular, it is unclear why certain plaques become stable and robust while others become fragile and dangerously vulnerable to rupture. We develop a multiphase model with non-standard boundary conditions to investigate early fibrous cap formation in the atherosclerotic plaque. The model is parameterised using data from a range of in vitro and in vivo studies, and includes highly nonlinear mechanisms of SMC proliferation and migration in response to an endothelium-derived chemical signal. We demonstrate that the model SMC population naturally evolves towards a steady-state, and predict a rate of cap formation and a final plaque SMC content consistent with experimental observations in mice. Parameter sensitivity simulations show that SMC proliferation makes a limited contribution to cap formation, and demonstrate that stable cap formation relies primarily on a critical balance between the rates of SMC recruitment to the plaque, chemotactic SMC migration within the plaque and SMC loss by apoptosis or phenotype change. This model represents the first detailed in silico study of fibrous cap formation in atherosclerosis, and establishes a multiphase modelling framework that can be readily extended to investigate many other aspects of plaque development.

The innate immune response to ischemic injury: a multiscale modeling perspective

Background

Cell death as a result of ischemic injury triggers powerful mechanisms regulated by germline-encoded Pattern Recognition Receptors (PRRs) with shared specificity that recognize invading pathogens and endogenous ligands released from dying cells, and as such are essential to human health. Alternatively, dysregulation of these mechanisms contributes to extreme inflammation, deleterious tissue damage and impaired healing in various diseases. The Toll-like receptors (TLRs) are a prototypical family of PRRs that may be powerful anti-inflammatory targets if agents can be designed that antagonize their harmful effects while preserving host defense functions. This requires an understanding of the complex interactions and consequences of targeting the TLR-mediated pathways as well as technologies to analyze and interpret these, which will then allow the simulation of perturbations targeting specific pathway components, predict potential outcomes and identify safe and effective therapeutic targets.

Results

We constructed a multiscale mathematical model that spans the tissue and intracellular scales, and captures the consequences of targeting various regulatory components of injury-induced TLR4 signal transduction on potential pro-inflammatory or pro-healing outcomes. We applied known interactions to simulate how inactivation of specific regulatory nodes affects dynamics in the context of injury and to predict phenotypes of potential therapeutic interventions. We propose rules to link model behavior to qualitative estimates of pro-inflammatory signal activation, macrophage infiltration, production of reactive oxygen species and resolution. We tested the validity of the model by assessing its ability to reproduce published data not used in its construction.

Conclusions

These studies will enable us to form a conceptual framework focusing on TLR4-mediated ischemic repair to assess potential molecular targets that can be utilized therapeutically to improve efficacy and safety in treating ischemic/inflammatory injury.

Patient-Specific, Multi-Scale Modeling of Neointimal Hyperplasia in Vein Grafts

Neointimal hyperplasia is amongst the major causes of failure of bypass grafts. The disease progression varies from patient to patient due to a range of different factors. In this paper, a mathematical model will be used to understand neointimal hyperplasia in individual patients, combining information from biological experiments and patient-specific data to analyze some aspects of the disease, particularly with regard to mechanical stimuli due to shear stresses on the vessel wall. By combining a biochemical model of cell growth and a patient-specific computational fluid dynamics analysis of blood flow in the lumen, remodeling of the blood vessel is studied by means of a novel computational framework. The framework was used to analyze two vein graft bypasses from one patient: a femoro-popliteal and a femoro-distal bypass. The remodeling of the vessel wall and analysis of the flow for each case was then compared to clinical data and discussed as a potential tool for a better understanding of the disease. Simulation results from this first computational approach showed an overall agreement on the locations of hyperplasia in these patients and demonstrated the potential of using new integrative modeling tools to understand disease progression.

Impact of Needles in Vascular Access for Hemodialysis

This article reviews pragmatic aspects of cannulation practice and types of cannulation devices, as well as their impact in vascular access for hemodialysis. Hemodialysis treatment requires successful insertion of two needles for each dialysis treatment. The first needle is the arterial needle; it removes blood with toxin accumulation from the patient and delivers it to the dialysis machine. The second needle, called the venous needle, returns the purified blood from the dialyzer to the patient. Mechanical and hemodynamic trauma related to needle insertions will be discussed.

Doppler ultrasound and calcification score: improving vascular access surveillance

AIM

Vascular access (VA) dysfunction limits hemodialysis delivery, which increases morbidity and mortality. The most com mon cause of VA failure is thrombosis, due to flow limiting stenosis resulting from neointimal hyperplasia. This occurs not only due to hemodynamic factors but also by systemic ones related to vascular atherosclerosis, inflammation and calcification, which has developed a simple vascular calcification score (SVCS) predictor of vascular calcification and arterial stiffness. The NKF-K/DOQ recommends several diagnostic procedures for VA surveillance. Blood access flow (Qa) has predictive power for the detection of stenosis. Our aim was to evaluate the role of systemic factors, especially SCVS, on Qa.

MATERIAL AND METHODS

Transversal study in 50 patients. Qa value was obtained with Blood Temperature Monitor and Doppler method. Pearson coefficient evaluated correlation between them. Clinical, lab and radiological variables were recorded and non-parametric tests evaluated how both Qa varied with them.

RESULTS

Pearson's corelation between DU-Qa and TD-Qa was 0.851 (p-value <0.001). DU-Qa varied significantly with age (p = 0.012), VA type (p = 0.021), SCVS (p = 0.030), intra-access arterial pressure (p = 0.015) and time on dialysis (p = 0.002). BTM-Qa varied significantly with diabetes status (p = 0.027), age (p = 0.017), first VA status (p = 0.036), intra-access arterial pressure (p = 0.028) and dialysis time (p = 0.001). Nevertheless, gender, hypertensive status and analitical parameters did not change the flow values.

CONCLUSION

Higher SVCS was associated only with lower DU-Qas, giving this method an advantage towards the indirect one. Additionally, a simple method like SVCS may be used to guide new surveillance recommendations accordingly to risk stratification.

Role of vascular function in predicting arteriovenous fistula outcomes: an observational pilot study

BACKGROUND

Many arteriovenous fistula (AVF) fail prior to use due to lack of maturation or thrombosis. Determining vascular function prior to surgery may be helpful to predict subsequent AVF success. This is a feasibility study to describe the vascular function in a cohort of chronic kidney disease (CKD) patients who are awaiting AVF creation.

METHODS

A prospective cohort of 28 CKD patients expected to progress to HD underwent arterial stiffness (pulse wave velocity, PWV) and endothelial function testing (flow mediated dilation FMD, and peripheral arterial tonometry, PAT) one week prior to AVF creation. AVF success was defined as maintaining patency and achieving maturation. Post operative fistula assessment at 8 weeks evaluated maturation (clinical assessment of adequate fistula flowand ultrasound diameter ≥ 0.5 cm).

RESULTS

The median age 72 years (62 - 78), 75% males, eGFR 15 ml/min/1.73 m(2) (12 - 18). 20 (71%) patients had successful AVF surgery with a mature AVF at 8 weeks. Patients with AVF success had higher mean PAT values 1.87 ± 0.52 than those with failed AVF 1.41 ± 0.24 p = 0.03.

CONCLUSIONS

Microvascular endothelial function as measured using PAT may be useful as a predictor of AVF maturation and function. This simple non invasive marker of vascular function may be a useful tool to predict AVF outcomes.

Mathematical modelling of atheroma plaque formation and development in coronary arteries

Atherosclerosis is a vascular disease caused by inflammation of the arterial wall, which results in the accumulation of low-density lipoprotein (LDL) cholesterol, monocytes, macrophages and fat-laden foam cells at the place of the inflammation. This process is commonly referred to as plaque formation. The evolution of the atherosclerosis disease, and in particular the influence of wall shear stress on the growth of atherosclerotic plaques, is still a poorly understood phenomenon. This work presents a mathematical model to reproduce atheroma plaque growth in coronary arteries. This model uses the Navier-Stokes equations and Darcy's law for fluid dynamics, convection-diffusion-reaction equations for modelling the mass balance in the lumen and intima, and the Kedem-Katchalsky equations for the interfacial coupling at membranes, i.e. endothelium. The volume flux and the solute flux across the interface between the fluid and the porous domains are governed by a three-pore model. The main species and substances which play a role in early atherosclerosis development have been considered in the model, i.e. LDL, oxidized LDL, monocytes, macrophages, foam cells, smooth muscle cells, cytokines and collagen. Furthermore, experimental data taken from the literature have been used in order to physiologically determine model parameters. The mathematical model has been implemented in a representative axisymmetric geometrical coronary artery model. The results show that the mathematical model is able to qualitatively capture the atheroma plaque development observed in the intima layer.

A computational model of fibroblast and macrophage spatial/temporal dynamics in foreign body reactions

The implantation of medical devices often triggers several immune responses, one kind of which is categorized as foreign body reactions. It is well established that macrophages and many other cells participate in the complex processes of foreign body reactions, and cause severe inflammations and fibrotic capsule formation in surrounding tissues. However, the detailed mechanisms of macrophage responses, recruitment and activation, in foreign body reactions are not totally understood. In the meantime, mathematical models have been proposed to systematically decipher the behavior of this complex system of multiple cells, proteins and biochemical processes in wound healing responses. Based on these early works, this study introduces a mathematical model in two spatial dimensions to investigate the transient behavior of macrophages, fibroblasts and their interactions during the formation of fibrotic tissue. We find that the simulation results are consistent with the experimental observations. These findings support that the model can reveal quantitative insights for studying foreign body reaction processes.

Inflammation, oxidation and venous neointimal hyperplasia precede vascular injury from AVF creation in CKD patients

PURPOSE

Intimal hyperplasia (IH), a well-recognized cause of dialysis vascular access failure, is generally believed to be an acquired pathologic lesion. Recent data suggests that IH is present prior to AVF creation. We sought to determine whether pre-existing inflammation and oxidation co-exist with IH prior to their incorporation into an AVF conduit, as their presence may predispose the AVF to further IH following AVF creation.

METHODS

At the time of first AV access surgery, vein segments were collected from ten Stage 4 and 5 CKD patients undergoing AVF creation 6-12 months prior to anticipated dialysis initiation. Morphometry and immunohistochemistry was performed to detect inflammatory markers IL-6, TGF-ß1, and TNFa, and markers of DNA oxidative damage (8-Hydroxy-2'-deoxyguanosine [HNE]) and lipid peroxidation (4-Hydroxy-2-Nonenal [8OHdG]).

RESULTS

The degree of IH severity was variable. IL-6, TGF-ß1, and TNFa co-localized with a-smooth muscle actin prominently within the venous intima and media. Although more diffuse, HNE and 8OHdG were intensely expressed in parallel with the inflammatory markers. In spite of these findings, however, neither extant IH nor the intensity of inflammatory or oxidative markers were associated with primary or secondary AVF failure at 12 month follow-up.

CONCLUSIONS

Not only does venous IH pre-exist, but inflammation and oxidation markers are present within veins used for the AVF conduit prior to its creation in CKD patients as early as one year before dialysis is commenced. Nevertheless, short and long-term AVF outcomes were not associated with the inflammatory or oxidative burden, suggesting the complexity of AVF dysfunction in humans with CKD.

Mathematical modeling of solid cancer growth with angiogenesis

Background

Cancer arises when within a single cell multiple malfunctions of control systems occur, which are, broadly, the system that promote cell growth and the system that protect against erratic growth. Additional systems within the cell must be corrupted so that a cancer cell, to form a mass of any real size, produces substances that promote the growth of new blood vessels. Multiple mutations are required before a normal cell can become a cancer cell by corruption of multiple growth-promoting systems.

Methods

We develop a simple mathematical model to describe the solid cancer growth dynamics inducing angiogenesis in the absence of cancer controlling mechanisms.

Results

The initial conditions supplied to the dynamical system consist of a perturbation in form of pulse: The origin of cancer cells from normal cells of an organ of human body. Thresholds of interacting parameters were obtained from the steady states analysis. The existence of two equilibrium points determine the strong dependency of dynamical trajectories on the initial conditions. The thresholds can be used to control cancer.

Conclusions

Cancer can be settled in an organ if the following combination matches: better fitness of cancer cells, decrease in the efficiency of the repairing systems, increase in the capacity of sprouting from existing vascularization, and higher capacity of mounting up new vascularization. However, we show that cancer is rarely induced in organs (or tissues) displaying an efficient (numerically and functionally) reparative or regenerative mechanism.

The dynamics of vein graft remodeling induced by hemodynamic forces: a mathematical model

Although vein bypass grafting is one of the primary options for the treatment of arterial occlusive disease and provides satisfactory results at an early stage of the treatment, the patency is limited to a few months in many patients. When the vein is implanted in the arterial system, it adapts to the high flow rate and high pressure of the arterial environment by changing the sizes of its layers, and this remodeling is believed to be a precursor of future graft failure. Hemodynamic forces, such as wall shear stress (WSS) and wall tension, have been recognized as major factors impacting vein graft remodeling. Although a wide range of experimental evidence relating hemodynamic forces to vein graft remodeling has been reported, a comprehensive mathematical model describing the relationship among WSS, wall tension, and the structural adaptation of each individual layer of the vein graft wall is lacking. The current manuscript presents a comprehensive and robust framework for treating the complex interaction between the WSS, wall tension, and the structural adaptation of each individual layer of the vein graft wall. We modeled the intimal and medial area and the radius of external elastic lamina, which in combination dictate luminal narrowing and the propensity for graft occlusion. Central to our model is a logistic relationship between independent and dependent variables to describe the initial increase and later decrease in the growth rate. The detailed understanding of the temporal changes in vein graft morphology that can be extracted from the current model is critical in identifying the dominant contributions to vein graft failure and the further development of strategies to improve their longevity.

A mathematical model for foreign body reactions in 2D

The foreign body reactions are commonly referred to the network of immune and inflammatory reactions of human or animals to foreign objects placed in tissues. They are basic biological processes, and are also highly relevant to bioengineering applications in implants, as fibrotic tissue formations surrounding medical implants have been found to substantially reduce the effectiveness of devices. Despite of intensive research on determining the mechanisms governing such complex responses, few mechanistic mathematical models have been developed to study such foreign body reactions. This study focuses on a kinetics-based predictive tool in order to analyze outcomes of multiple interactive complex reactions of various cells/proteins and biochemical processes and to understand transient behavior during the entire period (up to several months). A computational model in two spatial dimensions is constructed to investigate the time dynamics as well as spatial variation of foreign body reaction kinetics. The simulation results have been consistent with experimental data and the model can facilitate quantitative insights for study of foreign body reaction process in general.

"Venopathy" at work: recasting neointimal hyperplasia in a new light

Hemodialysis vascular access is a unique form of vascular anastomosis. Although it is created in a unique disease state, it has much to offer in terms of insights into venous endothelial and anastomotic biology. The development of neointimal hyperplasia (NH) has been identified as a pathologic entity, decreasing the lifespan and effectiveness of hemodialysis vascular access. Subtle hints and new data suggest a contrary idea-that NH, to some extent an expected response, if controlled properly, may play a beneficial role in the promotion of maturation to a functional access. This review attempts to recast our understanding of NH and redefine research goals for an evolving discipline that focuses on a life-sustaining connection between an artery and vein.

ART-ML - a novel XML format for the biological procedures modeling and the representation of blood flow simulation

The paper proposes a novel Extensible Markup Language (XML) based format called ART-ML that aims at supporting the interoperability and the reuse of models of blood flow, mass transport and plaque formation, exported by ARTool. ARTool is a platform for the automatic processing of various image modalities of coronary and carotid arteries. The images and their content are fused to develop morphological models of the arteries in easy to handle 3D representations. The platform incorporates efficient algorithms which are able to perform blood flow simulation. In addition atherosclerotic plaque development is estimated taking into account morphological, flow and genetic factors. ART-ML provides a XML format that enables the representation and management of embedded models within the ARTool platform and the storage and interchange of well-defined information. This approach influences in the model creation, model exchange, model reuse and result evaluation.

The role of transforming growth factor-beta-mediated tumor-stroma interactions in prostate cancer progression: an integrative approach

We have implemented a hybrid cellular automata model based on the structure of human prostate that recapitulates key interactions in nascent tumor foci between tumor cells and adjacent stroma. Model simulations show how stochastic interactions between tumor cells and stroma may lead to a structural suppression of tumor growth, modest proliferation, or unopposed tumor growth. The model incorporates key aspects of prostate tumor progression, including transforming growth factor-beta (TGF-beta), matrix-degrading enzyme activity, and stromal activation. It also examines the importance of TGF-beta during tumor progression and the role of stromal cell density in regulating tumor growth. The validity of one of the key predictions of the model about the effect of epithelial TGF-beta production on glandular stability was tested in vivo. These experimental results confirmed the ability of the model to generate testable biological predictions in addition to providing new avenues of experimental interest. This work underscores the need for more pathologically representative models to cooperatively drive computational and biological modeling, which together could eventually lead to more accurate diagnoses and treatments of prostate cancer.