Eric Lorenz

A Complex Automata approach for in-stent restenosis: two-dimensional multiscale modelling and simulations

In-stent restenosis, the maladaptive response of a blood vessel to injury caused by the deployment of a stent, is a multiscale system involving a large number of biological and physical processes. We describe a Complex Automata model for in-stent restenosis, coupling bulk flow, drug diffusion, and smooth muscle cell models, all operating on different time scales. Details of the single scale models and of the coupling interfaces are described, together with first simulation results, obtained with a dedicated software environment for Complex Automata simulations. Preliminary results show that the model can reproduce growth trends observed in experimental studies and facilitate testing of hypotheses concerning the interaction of key factors.

Multi-scale simulations of the dynamics of in-stent restenosis: impact of stent deployment and design

Neointimal hyperplasia, a process of smooth muscle cell re-growth, is the result of a natural wound healing response of the injured artery after stent deployment. Excessive neointimal hyperplasia following coronary artery stenting results in in-stent restenosis (ISR). Regardless of recent developments in the field of coronary stent design, ISR remains a significant complication of this interventional therapy. The influence of stent design parameters such as strut thickness, shape and the depth of strut deployment within the vessel wall on the severity of restenosis has already been highlighted but the detail of this influence is unclear. These factors impact on local haemodynamics and vessel structure and affect the rate of neointima formation. This paper presents the first results of a multi-scale model of ISR. The development of the simulated restenosis as a function of stent deployment depth is compared with an in vivo porcine dataset. Moreover, the influence of strut size and shape is investigated, and the effect of a drug released at the site of injury, by means of a drug-eluting stent, is also examined. A strong correlation between strut thickness and the rate of smooth muscle cell proliferation has been observed. Simulation results also suggest that the growth of the restenotic lesion is strongly dependent on the stent strut cross-sectional profile.

Foundations of distributed multiscale computing: Formalization, specification, and analysis

Inherently complex problems from many scientific disciplines require a multiscale modeling approach. Yet its practical contents remain unclear and inconsistent. Moreover, multiscale models can be very computationally expensive, and may have potential to be executed on distributed infrastructure. In this paper we propose firm foundations for multiscale modeling and distributed multiscale computing. Useful interaction patterns of multiscale models are made predictable with a submodel execution loop (SEL), four coupling templates, and coupling topology properties. We enhance a high-level and well-defined Multiscale Modeling Language (MML) that describes and specifies multiscale models and their computational architecture in a modular way. The architecture is analyzed using directed acyclic task graphs, facilitating validity checking, scheduling distributed computing resources, estimating computational costs, and predicting deadlocks. Distributed execution using the multiscale coupling library and environment (MUSCLE) is outlined. The methodology is applied to two selected applications in nanotechnology and biophysics, showing its capabilities.

Towards a Complex Automata Framework for Multi-scale Modeling: Formalism and the Scale Separation Map

Complex Automata were recently proposed as a paradigm to model multi-scale complex systems. The concept is formalized and the scale separation map is further investigated in relation with its capability to specify the components of Complex Automata. Five classes of scale separation are identified, each potentially giving rise to a specific multi-scale modeling paradigm. A number of canonical examples are briefly discussed.

Complex Automata: Multi-scale Modeling with Coupled Cellular Automata

Cellular Automata (CA) are generally acknowledged to be a powerful way to describe and model natural phenomena [1–3]. There are even tempting claims that nature itself is one big (quantum) information processing system, e.g. [4], and that CA may actually be nature’s way to do this processing [5–7]. We will not embark on this philosophical road, but ask ourselves a more mundane question. Can we use CA to model the inherently multi-scale processes in nature and use these models for efficient simulations on digital computers?

Where do the platelets go? A simulation study of fully resolved blood flow through aneurysmal vessels

Despite the importance of platelets in the formation of a thrombus, their transport in complex flows has not yet been studied in detail. In this paper we simulated red blood cells and platelets to explore their transport behaviour in aneurysmal geometries. We considered two aneurysms with different aspect ratios (AR = 1.0, 2.0) in the presence of fast and slow blood flows (Re = 10, 100), and examined the distributions of the cells. Low velocities in the parent vessel resulted in a large stagnation zone inside the cavity, leaving the initial distribution almost unchanged. In fast flows, an influx of platelets into the aneurysm was observed, leading to an elevated concentration. The connection of the platelet-rich cell-free layer (CFL) with the outer regions of the recirculation zones leads to their increased platelet concentration. These platelet-enhanced recirculation zones produced a diverse distribution of cells inside the aneurysm, for the different aspect ratios. A thin red blood CFL that was occupied by platelets was observed on the top of the wide-necked aneurysm, whereas a high-haematocrit region very close to the vessel wall was present in the narrow-necked case. The simulations revealed that non-trivial distributions of red blood cells and platelets are possible inside aneurysmal geometries, giving rise to several hypotheses on the formation of a thrombus, as well as to the wall weakening and the possible rupture of an aneurysm.

A distributed multiscale computation of a tightly coupled model using the Multiscale Modeling Language

Abstract Nature is observed at all scales; with multiscale modeling, scientists bring together several scales for a holistic analysis of a phenomenon. The models on these different scales may require significant but also heterogeneous computational resources, creating the need for distributed multiscale computing. A particularly demanding type of multiscale models, tightly coupled, brings with it a number of theoretical and practical issues. In this contribution, a tightly coupled model of in-stent restenosis is first theoretically examined for its multiscale merits using the Multiscale Modeling Language (MML); this is aided by a toolchain consisting of MAPPER Memory (MaMe), the Multiscale Application Designer (MAD), and Gridspace Experiment Workbench. It is implemented and executed with the general Multiscale Coupling Library and Environment (MUSCLE). Finally, it is scheduled amongst heterogeneous infrastructures using the QCG-Broker. This marks the first occasion that a tightly coupled application uses distributed multiscale computing in such a general way.

Parallel performance of an IB-LBM suspension simulation framework

We present performance results from ficsion, a general purpose parallel suspension solver, employing the Immersed-Boundary lattice-Boltzmann method (IB-LBM). ficsion is built on top of the open-source LBM framework Palabos, making use of its data structures and their inherent parallelism. We describe in brief the implementation and present weak and strong scaling results for simulations of dense red blood cell suspensions. Despite its complexity the simulations demonstrate a fairly good, close to linear scaling, both in the weak and strong scaling scenarios.

A Principled Approach to Distributed Multiscale Computing, from Formalization to Execution

In several disciplines, a multiscale approach is being used to model complex natural processes yet a principled background to multiscale modeling is not clear. Additionally, some multiscale models requiring distributed resources to be computed in an acceptable timeframe, while no standard framework for distributed multiscale computing is place. In this paper a principled approach to distributed multiscale computing is taken, formalizing multiscale modeling based on natural processes. Based on these foundations, the Multiscale Modeling Language (MML) is extended as a clear, general, formal, and high-level means to specify scales and interactions in, and as a guide to a uniform approach to crystalize, communicate, develop and execute a multiscale model. With an MML specification, a multiscale model can be analyzed for scheduling or deadlock detection using a task graph. The potential of this method is shown by applying it to two selected applications in nano materials and biophysics.

Towards a Complex Automata Multiscale Model of In-Stent Restenosis

In-stent restenosis, the maladaptive response of a blood vessel to injury caused by the deployment of a stent, is a multiscale problem involving a large number of processes. We describe a Complex Automata Model for in-stent restenosis, coupling a bulk flow, drug diffusion, and smooth muscle cell model, all operating on different time scales. Details of the single scale models and of the coupling interfaces are described, together with first simulation results, obtained with a dedicated software environment for Complex Automata simulations. The results show that the model can reproduce growth trends observed in experimental studies.