The analysis of cardiac function: a continuum approach

Generative myocardial motion tracking via latent space exploration with biomechanics-informed prior

Myocardial motion and deformation are rich descriptors that characterize cardiac function. Image registration, as the most commonly used technique for myocardial motion tracking, is an ill-posed inverse problem which often requires prior assumptions on the solution space. In contrast to most existing approaches which impose explicit generic regularization such as smoothness, in this work we propose a novel method that can implicitly learn an application-specific biomechanics-informed prior and embed it into a neural network-parameterized transformation model. Particularly, the proposed method leverages a variational autoencoder-based generative model to learn a manifold for biomechanically plausible deformations. The motion tracking then can be performed via traversing the learnt manifold to search for the optimal transformations while considering the sequence information. The proposed method is validated on three public cardiac cine MRI datasets with comprehensive evaluations. The results demonstrate that the proposed method can outperform other approaches, yielding higher motion tracking accuracy with reasonable volume preservation and better generalizability to varying data distributions. It also enables better estimates of myocardial strains, which indicates the potential of the method in characterizing spatiotemporal signatures for understanding cardiovascular diseases.

Synthesis, Molecular Docking, and Preclinical Evaluation of a New Succinimide Derivative for Cardioprotective, Hepatoprotective and Lipid-Lowering Effects

Cardiac and hepatotoxicities are major concerns in the development of new drugs. Better alternatives to other treatments are being sought to protect these vital organs from the toxicities of these pharmaceuticals. In this regard, a preclinical study is designed to investigate the histopathological effects of a new succinimide derivative (Comp-1) on myocardial and liver tissues, and the biochemical effects on selected cardiac biomarkers, hepatic enzymes, and lipid profiles. For this, an initially lethal/toxic dose was determined, followed by a grouping of selected albino rats into five groups (each group had n = 6). The control group received daily oral saline for 8 days. The 5-FU (5-Fluorouracil) group received oral saline daily for 8 days, added with the administration of a single dose of 5-FU (150 mg/kg I.P.) on day 5 of the study. The atenolol group received oral atenolol (20 mg/kg) for 8 days and 5-FU (150 mg/kg I.P.) on day 5 of the protocol. Similarly, two groups of rats treated with test compound (Comp-1) were administered with 5 mg/kg I.P. and 10 mg/kg I.P. for 8 days, followed by 5-FU (150 mg/kg I.P.) on day 5. Toxicity induced by 5-FU was manifested by increases in the serum creatinine kinase myocardial band (CK-MB), troponin I (cTnI) and lactate dehydrogenase (LDH), lipid profile, and selected liver enzymes, including ALP (alkaline phosphatase), ALT (alanine transaminase), AST (aspartate aminotransferase), BT (bilirubin total), and BD (direct bilirubin). These biomarkers were highly significantly decreased after the administration of the mentioned doses of the test compound (5 mg/kg and 10 mg/kg). Similarly, histological examination revealed cardiac and hepatic tissue toxicity by 5-FU. However, those toxic effects were also significantly recovered/improved after the administration of Comp-1 at the said doses. This derivative showed dose-dependent effects and was most effective at a dose of 10 mg/kg body weight. Binding energy data computed via docking simulations revealed that our compound interacts toward the human beta2-adrenergic G protein-coupled receptor (S = −7.89 kcal/mol) with a slight stronger affinity than the calcium channel T-type (S = −7.07 kcal/mol). In conclusion, the histological and biochemical results showed that the test compound (Comp-1) had prominent cardioprotective, hepatoprotective, and lipolytic effects against 5-FU-induced toxicity in the subjected animal model.

A Transmural Path Model Improves the Definition of the Orthotropic Tissue Structure in Heart Simulations

In the past decades, the structure of the heart, human as well as other species, has been explored in a detailed way, e.g., via histological studies or diffusion tensor magnetic resonance imaging. Nevertheless, the assignment of the characteristic orthotropic structure in a patient-specific finite element model remains a challenging task. Various types of rule-based models, which define the local fiber and sheet orientation depending on the transmural depth, have been developed. However, the correct assessment of the transmural depth is not trivial. Its accuracy has a substantial influence on the overall mechanical and electrical properties in rule-based models. The main purpose of this study is the development of a finite element-based approach to accurately determine the transmural depth on a general unstructured grid. Instead of directly using the solution of the Laplace problem as the transmural depth, we make use of a well-established model for the assessment of the transmural thickness. It is based on two hyperbolic first-order partial differential equations for the definition of a transmural path, whereby the transmural thickness is defined as the arc length of this path. Subsequently, the transmural depth is determined based on the position on the transmural path. Originally, the partial differential equations were solved via finite differences on structured grids. In order to circumvent the need of two grids and mapping between the structured (to determine the transmural depth) and unstructured (electromechanical heart simulation) grids, we solve the equations directly on the same unstructured tetrahedral mesh. We propose a finite-element-based discontinuous Galerkin approach. Based on the accurate transmural depth, we assign the local material orientation of the orthotropic tissue structure in a usual fashion. We show that this approach leads to a more accurate definition of the transmural depth. Furthermore, for the left ventricle, we propose functions for the transmural fiber and sheet orientation by fitting them to literature-based diffusion tensor magnetic resonance imaging data. The proposed functions provide a distinct improvement compared to existing rules from the literature.

A rapid electromechanical model to predict reverse remodeling following cardiac resynchronization therapy

Cardiac resynchronization therapy (CRT) is an effective therapy for patients who suffer from heart failure and ventricular dyssynchrony such as left bundle branch block (LBBB). When it works, it reverses adverse left ventricular (LV) remodeling and the progression of heart failure. However, CRT response rate is currently as low as 50-65%. In theory, CRT outcome could be improved by allowing clinicians to tailor the therapy through patient-specific lead locations, timing, and/or pacing protocol. However, this also presents a dilemma: there are far too many possible strategies to test during the implantation surgery. Computational models could address this dilemma by predicting remodeling outcomes for each patient before the surgery takes place. Therefore, the goal of this study was to develop a rapid computational model to predict reverse LV remodeling following CRT. We adapted our recently developed computational model of LV remodeling to simulate the mechanics of ventricular dyssynchrony and added a rapid electrical model to predict electrical activation timing. The model was calibrated to quantitatively match changes in hemodynamics and global and local LV wall mass from a canine study of LBBB and CRT. The calibrated model was used to investigate the influence of LV lead location and ischemia on CRT remodeling outcome. Our model results suggest that remodeling outcome varies with both lead location and ischemia location, and does not always correlate with short-term improvement in QRS duration. The results and time frame required to customize and run this model suggest promise for this approach in a clinical setting.

Prediction of Ventricular Mechanics After Pulmonary Valve Replacement in Tetralogy of Fallot by Biomechanical Modeling: A Step Towards Precision Healthcare

Clinical indicators of heart function are often limited in their ability to accurately evaluate the current mechanical state of the myocardium. Biomechanical modeling has been shown to be a promising tool in addition to clinical indicators. By providing a patient-specific measure of myocardial active stress (contractility), biomechanical modeling can enhance the precision of the description of patient's pathophysiology at any given point in time. In this work we aim to explore the ability of biomechanical modeling to predict the response of ventricular mechanics to the progressively decreasing afterload in repaired tetralogy of Fallot (rTOF) patients undergoing pulmonary valve replacement (PVR) for significant residual right ventricular outflow tract obstruction (RVOTO). We used 19 patient-specific models of patients with rTOF prior to pulmonary valve replacement (PVR), denoted as PSM_pre, and patient-specific models of the same patients created post-PVR (PSM_post)-both created in our previous published work. Using the PSM_pre and assuming cessation of the pulmonary regurgitation and a progressive decrease of RVOT resistance, we built relationships between the contractility and RVOT resistance post-PVR. The predictive value of such in silico obtained relationships were tested against the PSM_post, i.e. the models created from the actual post-PVR datasets. Our results show a linear 1-dimensional relationship between the in silico predicted contractility post-PVR and the RVOT resistance. The predicted contractility was close to the contractility in the PSM_post model with a mean (± SD) difference of 6.5 (± 3.0)%. The relationships between the contractility predicted by in silico PVR vs. RVOT resistance have a potential to inform clinicians about hypothetical mechanical response of the ventricle based on the degree of pre-operative RVOTO.

The SPARC DRC: Building a Resource for the Autonomic Nervous System Community

The Data and Resource Center (DRC) of the NIH-funded SPARC program is developing databases, connectivity maps, and simulation tools for the mammalian autonomic nervous system. The experimental data and mathematical models supplied to the DRC by the SPARC consortium are curated, annotated and semantically linked via a single knowledgebase. A data portal has been developed that allows discovery of data and models both via semantic search and via an interface that includes Google Map-like 2D flatmaps for displaying connectivity, and 3D anatomical organ scaffolds that provide a common coordinate framework for cross-species comparisons. We discuss examples that illustrate the data pipeline, which includes data upload, curation, segmentation (for image data), registration against the flatmaps and scaffolds, and finally display via the web portal, including the link to freely available online computational facilities that will enable neuromodulation hypotheses to be investigated by the autonomic neuroscience community and device manufacturers.

Insights into the passive mechanical behavior of left ventricular myocardium using a robust constitutive model based on full 3D kinematics

Myocardium possesses a hierarchical structure that results in complex three-dimensional (3D) mechanical behavior, forming a critical component of ventricular function in health and disease. A wide range of constitutive model forms have been proposed for myocardium since the first planar biaxial studies were performed by Demer and Yin (J. Physiol. 339 (1), 1983). While there have been extensive studies since, none have been based on full 3D kinematic data, nor have they utilized optimal experimental design to estimate constitutive parameters, which may limit their predictive capability. Herein we have applied our novel 3D numerical-experimental methodology (Avazmohammadi et al., Biomechanics Model. Mechanobiol. 2018) to explore the applicability of an orthotropic constitutive model for passive ventricular myocardium (Holzapfel and Ogden, Philos. Trans. R. Soc. Lond.: Math. Phys. Eng. Sci. 367, 2009) by integrating 3D optimal loading paths, spatially varying material structure, and inverse modeling techniques. Our findings indicated that the initial model form was not successful in reproducing all optimal loading paths, due to previously unreported coupling behaviors via shearing of myofibers and extracellular collagen fibers in the myocardium. This observation necessitated extension of the constitutive model by adding two additional terms based on the I8(C) pseudo-invariant in the fiber-normal and sheet-normal directions. The modified model accurately reproduced all optimal loading paths and exhibited improved predictive capabilities. These unique results suggest that more complete constitutive models are required to fully capture the full 3D biomechanical response of left ventricular myocardium. The present approach is thus crucial for improved understanding and performance in cardiac modeling in healthy, diseased, and treatment scenarios.

Open-Source Routines for Building Personalized Left Ventricular Models From Cardiac Magnetic Resonance Imaging Data

Creating patient-specific models of the heart is a promising approach for predicting outcomes in response to congenital malformations, injury, or disease, as well as an important tool for developing and customizing therapies. However, integrating multimodal imaging data to construct patient-specific models is a nontrivial task. Here, we propose an approach that employs a prolate spheroidal coordinate system to interpolate information from multiple imaging datasets and map those data onto a single geometric model of the left ventricle (LV). We demonstrate the mapping of the location and transmural extent of postinfarction scar segmented from late gadolinium enhancement (LGE) magnetic resonance imaging (MRI), as well as mechanical activation calculated from displacement encoding with stimulated echoes (DENSE) MRI. As a supplement to this paper, we provide MATLAB and Python versions of the routines employed here for download from SimTK.

Local Conduction Velocity in the Presence of Late Gadolinium Enhancement and Myocardial Wall Thinning: A Cardiac Magnetic Resonance Study in a Swine Model of Healed Left Ventricular Infarction

BACKGROUND

Conduction velocity (CV) is an important property that contributes to the arrhythmogenicity of the tissue substrate. The aim of this study was to investigate the association between local CV versus late gadolinium enhancement (LGE) and myocardial wall thickness in a swine model of healed left ventricular infarction.

METHODS

Six swine with healed myocardial infarction underwent cardiovascular magnetic resonance imaging and electroanatomic mapping. Two healthy controls (one treated with amiodarone and one unmedicated) underwent electroanatomic mapping with identical protocols to establish the baseline CV. CV was estimated using a triangulation technique. LGE+ regions were defined as signal intensity >2 SD than the mean of remote regions, wall thinning+ as those with wall thickness <2 SD than the mean of remote regions. LGE heterogeneity was defined as SD of LGE in the local neighborhood of 5 mm and wall thickness gradient as SD within 5 mm. Cardiovascular magnetic resonance and electroanatomic mapping data were registered, and hierarchical modeling was performed to estimate the mean difference of CV (LGE+/-, wall thinning+/-), or the change of the mean of CV per unit change (LGE heterogeneity, wall thickness gradient).

RESULTS

Significantly slower CV was observed in LGE+ (0.33±0.25 versus 0.54±0.36 m/s; P<0.001) and wall thinning+ regions (0.38±0.28 versus 0.55±0.37 m/s; P<0.001). Areas with greater LGE heterogeneity ( P<0.001) and wall thickness gradient ( P<0.001) exhibited slower CV.

CONCLUSIONS

Slower CV is observed in the presence of LGE, myocardial wall thinning, high LGE heterogeneity, and a high wall thickness gradient. Cardiovascular magnetic resonance may offer a valuable imaging surrogate for estimating CV, which may support noninvasive identification of the arrhythmogenic substrate.

A Contemporary Look at Biomechanical Models of Myocardium

Understanding and predicting the mechanical behavior of myocardium under healthy and pathophysiological conditions are vital to developing novel cardiac therapies and promoting personalized interventions. Within the past 30 years, various constitutive models have been proposed for the passive mechanical behavior of myocardium. These models cover a broad range of mathematical forms, microstructural observations, and specific test conditions to which they are fitted. We present a critical review of these models, covering both phenomenological and structural approaches, and their relations to the underlying structure and function of myocardium. We further explore the experimental and numerical techniques used to identify the model parameters. Next, we provide a brief overview of continuum-level electromechanical models of myocardium, with a focus on the methods used to integrate the active and passive components of myocardial behavior. We conclude by pointing to future directions in the areas of optimal form as well as new approaches for constitutive modeling of myocardium.

Simulation of Left Ventricular Dynamics Using a Low-Order Mathematical Model

The eventual goal of this study is to develop methods for estimating dynamic stresses in the left ventricle (LV) that could be used on-line in clinical settings, based on routinely available measurements. Toward this goal, a low-order theoretical model is presented, in which LV shape is represented using a small number of parameters, allowing rapid computational simulations of LV dynamics. The LV is represented as a thick-walled prolate spheroid containing helical muscle fibers with nonlinear passive and time-dependent active contractile properties. The displacement field during the cardiac cycle is described by three time-dependent parameters, using a family of volume-preserving mappings based on prolate spheroidal coordinates. Stress equilibrium is imposed in weak form and the resulting force balance equations are coupled to a lumped-parameter model of the circulation, leading to a system of differential-algebraic equations, whose numerical solution yields predictions of LV pressure and volume, together with spatial distributions of stresses and strains throughout the cardiac cycle. When static loading of the passive LV is assumed, this approach yields displacement and stress fields that closely match results from a standard finite-element approach. When dynamic motion with active contraction is simulated, substantial variations of fiber stress and strain through the myocardium are predicted. This approach allows simulations of LV dynamics that run faster than real time, and could be used to determine patient-specific parameters of LV performance on-line from clinically available measurements, with the eventual goal of real-time, patient-specific analysis of cardiac parameters.

In silico assessment of biomedical products: The conundrum of rare but not so rare events in two case studies

In silico clinical trials, defined as "The use of individualized computer simulation in the development or regulatory evaluation of a medicinal product, medical device, or medical intervention," have been proposed as a possible strategy to reduce the regulatory costs of innovation and the time to market for biomedical products. We review some of the the literature on this topic, focusing in particular on those applications where the current practice is recognized as inadequate, as for example, the detection of unexpected severe adverse events too rare to be detected in a clinical trial, but still likely enough to be of concern. We then describe with more details two case studies, two successful applications of in silico clinical trial approaches, one relative to the University of Virginia/Padova simulator that the Food and Drug Administration has accepted as possible replacement for animal testing in the preclinical assessment of artificial pancreas technologies, and the second, an investigation of the probability of cardiac lead fracture, where a Bayesian network was used to combine in vivo and in silico observations, suggesting a whole new strategy of in silico-augmented clinical trials, to be used to increase the numerosity where recruitment is impossible, or to explore patients' phenotypes that are unlikely to appear in the trial cohort, but are still frequent enough to be of concern.

The Virtual Physiological Human: Ten Years After

Biomedical research and clinical practice are struggling to cope with the growing complexity that the progress of health care involves. The most challenging diseases, those with the largest socioeconomic impact (cardiovascular conditions; musculoskeletal conditions; cancer; metabolic, immunity, and neurodegenerative conditions), are all characterized by a complex genotype-phenotype interaction and by a "systemic" nature that poses a challenge to the traditional reductionist approach. In 2005 a small group of researchers discussed how the vision of computational physiology promoted by the Physiome Project could be translated into clinical practice and formally proposed the term Virtual Physiological Human. Our knowledge about these diseases is fragmentary, as it is associated with molecular and cellular processes on the one hand and with tissue and organ phenotype changes (related to clinical symptoms of disease conditions) on the other. The problem could be solved if we could capture all these fragments of knowledge into predictive models and then compose them into hypermodels that help us tame the complexity that such systemic behavior involves. In 2005 this was simply not possible-the necessary methods and technologies were not available. Now, 10 years later, it seems the right time to reflect on the original vision, the results achieved so far, and what remains to be done.

Multiphysics and multiscale modelling, data-model fusion and integration of organ physiology in the clinic: ventricular cardiac mechanics

With heart and cardiovascular diseases continually challenging healthcare systems worldwide, translating basic research on cardiac (patho)physiology into clinical care is essential. Exacerbating this already extensive challenge is the complexity of the heart, relying on its hierarchical structure and function to maintain cardiovascular flow. Computational modelling has been proposed and actively pursued as a tool for accelerating research and translation. Allowing exploration of the relationships between physics, multiscale mechanisms and function, computational modelling provides a platform for improving our understanding of the heart. Further integration of experimental and clinical data through data assimilation and parameter estimation techniques is bringing computational models closer to use in routine clinical practice. This article reviews developments in computational cardiac modelling and how their integration with medical imaging data is providing new pathways for translational cardiac modelling.

Computational Modeling of Healthy Myocardium in Diastole

In order to better understand the mechanics of the heart and its disorders, engineers increasingly make use of the finite element method (FEM) to investigate healthy and diseased cardiac tissue. However, FEM is only as good as the underlying constitutive model, which remains a major challenge to the biomechanics community. In this study, a recently developed structurally based constitutive model was implemented to model healthy left ventricular myocardium during passive diastolic filling. This model takes into account the orthotropic response of the heart under loading. In-vivo strains were measured from magnetic resonance images (MRI) of porcine hearts, along with synchronous catheterization pressure data, and used for parameter identification of the passive constitutive model. Optimization was performed by minimizing the difference between MRI measured and FE predicted strains and cavity volumes. A similar approach was followed for the parameter identification of a widely used phenomenological constitutive law, which is based on a transversely isotropic material response. Results indicate that the parameter identification with the structurally based constitutive law is more sensitive to the assigned fiber architecture and the fit between the measured and predicted strains is improved with more realistic sheet angles. In addition, the structurally based model is capable of generating a more physiological end-diastolic pressure-volume relationship in the ventricle.

From Finite Element Meshes to Clouds of Points: A Review of Methods for Generation of Computational Biomechanics Models for Patient-Specific Applications

It has been envisaged that advances in computing and engineering technologies could extend surgeons' ability to plan and carry out surgical interventions more accurately and with less trauma. The progress in this area depends crucially on the ability to create robustly and rapidly patient-specific biomechanical models. We focus on methods for generation of patient-specific computational grids used for solving partial differential equations governing the mechanics of the body organs. We review state-of-the-art in this area and provide suggestions for future research. To provide a complete picture of the field of patient-specific model generation, we also discuss methods for identifying and assigning patient-specific material properties of tissues and boundary conditions.

A displacement-based finite element formulation for incompressible and nearly-incompressible cardiac mechanics

The Lagrange Multiplier (LM) and penalty methods are commonly used to enforce incompressibility and compressibility in models of cardiac mechanics. In this paper we show how both formulations may be equivalently thought of as a weakly penalized system derived from the statically condensed Perturbed Lagrangian formulation, which may be directly discretized maintaining the simplicity of penalty formulations with the convergence characteristics of LM techniques. A modified Shamanskii-Newton-Raphson scheme is introduced to enhance the nonlinear convergence of the weakly penalized system and, exploiting its equivalence, modifications are developed for the penalty form. Focusing on accuracy, we proceed to study the convergence behavior of these approaches using different interpolation schemes for both a simple test problem and more complex models of cardiac mechanics. Our results illustrate the well-known influence of locking phenomena on the penalty approach (particularly for lower order schemes) and its effect on accuracy for whole-cycle mechanics. Additionally, we verify that direct discretization of the weakly penalized form produces similar convergence behavior to mixed formulations while avoiding the use of an additional variable. Combining a simple structure which allows the solution of computationally challenging problems with good convergence characteristics, the weakly penalized form provides an accurate and efficient alternative to incompressibility and compressibility in cardiac mechanics.

Interventional heart wall motion analysis with cardiac C-arm CT systems

Today, quantitative analysis of three-dimensional (3D) dynamics of the left ventricle (LV) cannot be performed directly in the catheter lab using a current angiographic C-arm system, which is the workhorse imaging modality for cardiac interventions. Therefore, myocardial wall analysis is completely based on the 2D angiographic images or pre-interventional 3D/4D imaging. In this paper, we present a complete framework to study the ventricular wall motion in 4D (3D+t) directly in the catheter lab. From the acquired 2D projection images, a dynamic 3D surface model of the LV is generated, which is then used to detect ventricular dyssynchrony. Different quantitative features to evaluate LV dynamics known from other modalities (ultrasound, magnetic resonance imaging) are transferred to the C-arm CT data. We use the ejection fraction, the systolic dyssynchrony index a 3D fractional shortening and the phase to maximal contraction (ϕi, max) to determine an indicator of LV dyssynchrony and to discriminate regionally pathological from normal myocardium. The proposed analysis tool was evaluated on simulated phantom LV data with and without pathological wall dysfunctions. The LV data used is publicly available online at https://conrad.stanford.edu/data/heart. In addition, the presented framework was tested on eight clinical patient data sets. The first clinical results demonstrate promising performance of the proposed analysis tool and encourage the application of the presented framework to a larger study in clinical practice.

Impact of weightlessness on cardiac shape and left ventricular stress/strain distributions

In this paper, a finite element model of the heart is developed to investigate the impact of different gravitational loadings of Earth, Mars, Moon, and microgravity on the cardiac shape and strain/stress distributions in the left ventricle. The finite element model is based on realistic 3D heart geometry, detailed fiber/sheet micro-architecture, and a validated orthotropic cardiac tissue model and constitutive relationship that capture the passive behavior of the heart at end-diastole. The model predicts the trend and magnitude of cardiac shape change at different gravitational levels with great fidelity in comparison to recent cardiac sphericity measurements performed during simulated reduced-gravity parabolic flight experiments. Moreover, the numerical predictions indicate that although the left ventricular strain distributions remain relatively unaltered across the gravitational fields and the strain extrema values occur at the same relative locations, their values change noticeably with decreasing gravity. As for the stress, however, both the magnitude and location of the extrema change with a decrease in the gravitational field. Consequently, tension regions of the heart on Earth can change into compression regions in space.

Structural remodeling and mechanical function in heart failure

The cardiac extracellular matrix (ECM) is the three-dimensional scaffold that defines the geometry and muscular architecture of the cardiac chambers and transmits forces produced during the cardiac cycle throughout the heart wall. The cardiac ECM is an active system that responds to the stresses to which it is exposed and in the normal heart is adapted to facilitate efficient mechanical function. There are marked differences in the short- and medium-term changes in ventricular geometry and cardiac ECM that occur as a result of volume overload, hypertension, and ischemic cardiomyopathy. Despite this, there is a widespread view that a common remodeling "phenotype" governs the final progression to end-stage heart failure in different forms of heart disease. In this review article, we make the case that this interpretation is not consistent with the clinical and experimental data on the topic. We argue that there is a need for new theoretical and experimental models that will enable stresses acting on the ECM and resultant deformations to be estimated more accurately and provide better spatial resolution of local signaling mechanisms that are activated as a result. These developments are necessary to link the effects of structural remodeling with altered cardiac mechanical function.

Electromechanical wave imaging for noninvasive mapping of the 3D electrical activation sequence in canines and humans in vivo

Cardiovascular diseases rank as America's primary killer, claiming the lives of over 41% of more than 2.4 million Americans. One of the main reasons for this high death toll is the severe lack of effective imaging techniques for screening, early detection and localization of an abnormality detected on the electrocardiogram (ECG). The two most widely used imaging techniques in the clinic are CT angiography and echocardiography with limitations in speed of application and reliability, respectively. It has been established that the mechanical and electrical properties of the myocardium change dramatically as a result of ischemia, infarction or arrhythmia; both at their onset and after survival. Despite these findings, no imaging technique currently exists that is routinely used in the clinic and can provide reliable, non-invasive, quantitative mapping of the regional, mechanical, and electrical function of the myocardium. Electromechanical Wave Imaging (EWI) is an ultrasound-based technique that utilizes the electromechanical coupling and its associated resulting strain to infer to the underlying electrical function of the myocardium. The methodology of EWI is first described and its fundamental performance is presented. Subsequent in vivo canine and human applications are provided that demonstrate the applicability of Electromechanical Wave Imaging in differentiating between sinus rhythm and induced pacing schemes as well as mapping arrhythmias. Preliminary validation with catheter mapping is also provided and transthoracic electromechanical mapping in all four chambers of the human heart is also presented demonstrating the potential of this novel methodology to noninvasively infer to both the normal and pathological electrical conduction of the heart.

The interaction of Ca2+ with sarcomeric proteins: role in function and dysfunction of the heart

The hallmarks of the normal heartbeat are both rapid onset of contraction and rapid relaxation as well as an inotropic response to both increased end-diastolic volume and increased heart rate. At the microscopic level, Ca(2+) plays a crucial role in normal cardiac contraction. This paper reviews the cycle of Ca(2+) fluxes during the normal heartbeat, which underlie the coupling between excitation and contraction and permit a highly synchronized action of cardiac sarcomeres. Length dependence of the response of the regulatory sarcomeric proteins mediates the Frank-Starling Law of the heart. However, Ca(2+) transport may go astray in heart disease such as in congestive heart failure, and both jeopardize systole and diastole and triggering arrhythmias. The interaction between weak and strong segments in nonuniform cardiac muscle allows partial preservation of force of contraction but may further lead to mechanoelectric feedback or reverse excitation-contraction coupling mediating an early diastolic Ca(2+) transient caused by the rapid force decrease during the relaxation phase. These rapid force changes in nonuniform muscle may cause arrhythmogenic Ca(2+) waves to propagate by the activation of neighboring sarcoplasmic reticulum by diffusing Ca(2+) ions.

OpenCMISS: a multi-physics & multi-scale computational infrastructure for the VPH/Physiome project

The VPH/Physiome Project is developing the model encoding standards CellML (cellml.org) and FieldML (fieldml.org) as well as web-accessible model repositories based on these standards (models.physiome.org). Freely available open source computational modelling software is also being developed to solve the partial differential equations described by the models and to visualise results. The OpenCMISS code (opencmiss.org), described here, has been developed by the authors over the last six years to replace the CMISS code that has supported a number of organ system Physiome projects. OpenCMISS is designed to encompass multiple sets of physical equations and to link subcellular and tissue-level biophysical processes into organ-level processes. In the Heart Physiome project, for example, the large deformation mechanics of the myocardial wall need to be coupled to both ventricular flow and embedded coronary flow, and the reaction-diffusion equations that govern the propagation of electrical waves through myocardial tissue need to be coupled with equations that describe the ion channel currents that flow through the cardiac cell membranes. In this paper we discuss the design principles and distributed memory architecture behind the OpenCMISS code. We also discuss the design of the interfaces that link the sets of physical equations across common boundaries (such as fluid-structure coupling), or between spatial fields over the same domain (such as coupled electromechanics), and the concepts behind CellML and FieldML that are embodied in the OpenCMISS data structures. We show how all of these provide a flexible infrastructure for combining models developed across the VPH/Physiome community.

Serial ultrasound evaluation of intramyocardial strain after reperfused myocardial infarction reveals that remote zone dyssynchrony develops in concert with left ventricular remodeling

This study noninvasively evaluated the development of left ventricular (LV) dyssynchrony following reperfused myocardial infarction (MI) in mice using an ultrasonic speckle-tracking method. Eight C57BL/6J mice were assessed by high-resolution echocardiography at baseline and at eight time-points following MI. Images were acquired at 1mm elevational intervals encompassing the entire LV to determine chamber volumes and radial strain. Receiver-operating characteristic (ROC) analysis of regional radial strain was used to segment the three-dimensional (3-D) LV into infarct, adjacent and remote zones. This in vivo segmentation was correlated to histologic infarct size (R = 0.89, p < 0.01) in a short-axis, slice-by-slice comparison. The onset of dyssynchrony during LV remodeling was assessed by standard deviation of time to peak radial strain in the infarct, adjacent and remote zones. It was discovered that the form of LV dyssynchrony that develops in the remote zone late after MI does so in concert with the progression of LV remodeling (R = 0.70, p < 0.05).

Electromechanical coupling in the cardiac myocyte; stretch-arrhythmia feedback

The macroscopic hallmarks of the normal heartbeat are rapid onset of contraction and rapid relaxation and an inotropic response to both increased end diastolic volume and increased heart rate. At the microscopic level, the calcium ion (Ca(2+)) plays a crucial role in normal cardiac contraction. This paper reviews the cycle of Ca(2+) fluxes during the normal heartbeat, which underlie the coupling between excitation and contraction (ECC) and permit a highly synchronized action of cardiac sarcomeres. Length dependence of the response of the regulatory sarcomeric proteins mediates the Frank-Starling Law of the heart. However, Ca(2+) transport may go astray in heart disease and both jeopardize the exquisite mechanism of systole and diastole and triggering arrhythmias. The interplay between weakened and strong segments in nonuniform cardiac muscle may further lead to mechanoelectric feedback-or reverse excitation contraction coupling (RECC) mediating an early diastolic Ca(2+) transient caused by the rapid force decrease during the relaxation phase. These rapid force changes in nonuniform muscle may cause arrhythmogenic Ca(2+) waves to propagate by activation of neighbouring SR by diffusing Ca(2+) ions.

A computational method for developing hierarchical large deformation viscoelastic models of the contracting heart

In this study, a new computational method for modelling the contracting heart is described. Using this method, the cardiac wall is constructed from basic, repeating contractile units that represent individual myocardial units and collagen, each with its own set of parameters, including orientation, passive and active behaviour and stimulation propagation. The method allows individual control of each structural unit (e.g. at the level of a single myocardial unit). Feasibility of modelling dynamic heart contraction using this method is demonstrated using 2D cross-sections and simplified 3D geometries. Effects of non-contractile scar and myopathic tissue were also tested in these geometrical configurations. Results from the 2D and 3D simulations were, overall, in agreement with well-established physiological data. The present method holds promise for modelling complex heart pathologies, abnormal mechanical properties (e.g. myocardial infarcts) and electrical conduction properties (branch blocks), and their spatial distributions across the myocardial tissues.

Real-time segmentation by Active Geometric Functions

Recent advances in 4D imaging and real-time imaging provide image data with clinically important cardiac dynamic information at high spatial or temporal resolution. However, the enormous amount of information contained in these data has also raised a challenge for traditional image analysis algorithms in terms of efficiency. In this paper, a novel deformable model framework, Active Geometric Functions (AGF), is introduced to tackle the real-time segmentation problem. As an implicit framework paralleling to level-set, AGF has mathematical advantages in efficiency and computational complexity as well as several flexible feature similar to level-set framework. AGF is demonstrated in two cardiac applications: endocardial segmentation in 4D ultrasound and myocardial segmentation in MRI with super high temporal resolution. In both applications, AGF can perform real-time segmentation in several milliseconds per frame, which was less than the acquisition time per frame. Segmentation results are compared to manual tracing with comparable performance with inter-observer variability. The ability of such real-time segmentation will not only facilitate the diagnoses and workflow, but also enables novel applications such as interventional guidance and interactive image acquisition with online segmentation.

Quantitative three-dimensional wall motion analysis predicts ischemic region size and location

Stress echocardiography is an important screening test for coronary artery disease. Currently, cardiologists rely on visual analysis of left ventricular (LV) wall motion abnormalities, which is subjective and qualitative. We previously used finite-element models of the regionally ischemic left ventricle to develop a wall motion measure, 3DFS, for predicting ischemic region size and location from real-time 3D echocardiography (RT3DE). The purpose of this study was to validate these methods against regional blood flow measurements during regional ischemia and to compare the accuracy of our methods to the current state of the art, visual scoring by trained cardiologists. We acquired RT3DE images during 20 brief (<2 min) coronary occlusions in dogs and determined ischemic region size and location by microsphere-based measurement of regional perfusion. We identified regions of abnormal wall motion using 3DFS and by blinded visual scoring. 3DFS predicted ischemic region size well (correlation r (2) = 0.64 against microspheres, p < 0.0001), reducing error by more than half compared to visual scoring (8 +/- 9% vs. 19 +/- 14%, p < 0.05), while localizing the ischemic region with equal accuracy. We conclude that 3DFS is an objective, quantitative measure of wall motion that localizes acutely ischemic regions as accurately as wall motion scoring while providing superior quantification of ischemic region size.

Generation of histo-anatomically representative models of the individual heart: tools and application

This paper presents methods to build histo-anatomically detailed individualized cardiac models. The models are based on high-resolution three-dimensional anatomical and/or diffusion tensor magnetic resonance images, combined with serial histological sectioning data, and are used to investigate individualized cardiac function. The current state of the art is reviewed, and its limitations are discussed. We assess the challenges associated with the generation of histo-anatomically representative individualized in silico models of the heart. The entire processing pipeline including image acquisition, image processing, mesh generation, model set-up and execution of computer simulations, and the underlying methods are described. The multifaceted challenges associated with these goals are highlighted, suitable solutions are proposed, and an important application of developed high-resolution structure-function models in elucidating the effect of individual structural heterogeneity upon wavefront dynamics is demonstrated.

Wall thickness of coronary vessels varies transmurally in the LV but not the RV: implications for local stress distribution

Since the right and left ventricles (RV and LV) function under different loading conditions, it is not surprising that they differ in their mechanics (intramyocardial pressure), structure, and metabolism; such differences may also contribute to differences in the coronary vessel wall. Our hypothesis is that intima-media thickness (IMT), IMT-to-radius (IMT-to-R) ratio, and vessel wall stress vary transmurally in the LV, much more than in the RV. Five normal Yorkshire swine were used in this study. The major coronary arteries were cannulated through the aorta and perfusion fixed with 6.25% glutaraldehyde and casted with a catalyzed silicone-elastomer solution. Arterial and venous vessels were obtained from different transmural locations of the RV and LV, processed for histological analysis, and measured with an imaging software. A larger transmural gradient was found for IMT, IMT-to-R ratio, and diastolic circumferential stress in vessels from the LV than the nearly zero transmural slope in the RV. The IMT of arterial vessels in the LV showed a slope of 0.7 +/- 0.5 compared with 0.3 +/- 0.3 of arterial vessels in the RV (P <or= 0.05). The slope for venous vessels in the LV was 0.14 +/- 0.14 vs. 0.06 +/- 0.05 in the RV. The present data reflect the local structure-function relation, where the significant gradient in intramyocardial pressure in the LV is associated with a significant gradient of IMT and IMT-to-R ratio, unlike the RV. This has important implications for local adaptation of transmural loading on the vessel wall and vascular remodeling when the loading is perturbed in cardiac hypertrophy or heart failure.

Region-based endocardium tracking on real-time three-dimensional ultrasound

Matrix-phased array transducers for real-time 3-D ultrasound enable fast, noninvasive visualization of cardiac ventricles. Typically, 3-D ultrasound images are semiautomatically segmented to extract the left ventricular endocardial surface at end-diastole and end-systole. Automatic segmentation and propagation of this surface throughout the entire cardiac cycle is a challenging and cumbersome task. If the position of the endocardial surface is provided at one or two time frames during the cardiac cycle, automated tracking of the surface over the remaining time frames could reduce the workload of cardiologists and optimize analysis of 3-D ultrasound data. In this paper, we applied a region-based tracking algorithm to track the endocardial surface between two reference frames that were manually segmented. To evaluate the tracking of the endocardium, the method was applied to 40 open-chest dog datasets with 484 frames in total. Ventricular geometry and volumes derived from region-based endocardial surfaces and manual tracing were quantitatively compared, showing strong correlation between the two approaches. Statistical analysis showed that the errors from tracking were within the range of interobserver variability of manual tracing. Moreover, our algorithm performed well on ischemia datasets, suggesting that the method is robust-to-abnormal wall motion. In conclusion, the proposed optical flow-based surface tracking method is very efficient and accurate, providing dynamic "interpolation" of segmented endocardial surfaces.

Computational cardiac atlases: from patient to population and back

Integrative models of cardiac physiology are important for understanding disease and planning intervention. Multimodal cardiovascular imaging plays an important role in defining the computational domain, the boundary/initial conditions, and tissue function and properties. Computational models can then be personalized through information derived from in vivo and, when possible, non-invasive images. Efforts are now established to provide Web-accessible structural and functional atlases of the normal and pathological heart for clinical, research and educational purposes. Efficient and robust statistical representations of cardiac morphology and morphodynamics can thereby be obtained, enabling quantitative analysis of images based on such representations. Statistical models of shape and appearance can be built automatically from large populations of image datasets by minimizing manual intervention and data collection. These methods facilitate statistical analysis of regional heart shape and wall motion characteristics across population groups, via the application of parametric mathematical modelling tools. These parametric modelling tools and associated ontological schema also facilitate data fusion between different imaging protocols and modalities as well as other data sources. Statistical priors can also be used to support cardiac image analysis with applications to advanced quantification and subject-specific simulations of computational physiology.

Toward patient-specific myocardial models of the heart

This article presents a framework for building patient-specific models of the myocardium, to help diagnosis, therapy planning, and procedure guidance. The aim is to be able to introduce such models in clinical applications. Thus, there is a need to design models that can be adjusted from clinical data, images, or signals, which are sparse and noisy. The authors describe the three main components of a myocardial model: the anatomy, the electrophysiology, and the biomechanics. For each of these components, the authors try to obtain the best balance between prior knowledge and observable parameters to be able to adjust these models to patient data. To achieve this, there is a need to design models with the right level of complexity and a computational cost compatible with clinical constraints.

Maximum a posteriori strategy for the simultaneous motion and material property estimation of the heart

In addition to its technical merits as a challenging nonrigid motion and structural integrity analysis problem, quantitative estimation of cardiac regional functions and material characteristics has significant physiological and clinical value. We developed a stochastic finite-element framework for the simultaneous recovery of myocardial motion and material parameters from medical image sequences with an extended Kalman filter approach, and we have shown that this simultaneous estimation strategy achieves more accurate and robust results than separated motion and material estimation efforts. In this paper, we present a new computational strategy for the framework based upon the maximum a posteriori estimation principles, realized through the extended Kalman smoother, that produces a sequence of kinematics state and material parameter estimation of the entire myocardium, including the endocardial, epicardial, and midwall tissues. The system dynamics equations of the heart are constructed using a biomechanical model with stochastic parameters, and the tissue material and deformation parameters are jointly estimated from the periodic imaging data. Noise-corrupted synthetic image sequences with known kinematics and material parameters are used to assess the accuracy and robustness of the framework. Experiments with canine magnetic resonance tagging and phase-contrast image sequences have been conducted with very promising results, as validated through comparison to the histological staining of postmortem myocardium.

Physiome-model-based state-space framework for cardiac deformation recovery

RATIONALE AND OBJECTIVES

To more reliably recover cardiac information from noise-corrupted, patient-specific measurements, it is essential to employ meaningful constraining models and adopt appropriate optimization criteria to couple the models with the measurements. Although biomechanical models have been extensively used for myocardial motion recovery with encouraging results, the passive nature of such constraints limits their ability to fully count for the deformation caused by active forces of the myocytes. To overcome such limitations, we propose to adopt a cardiac physiome model as the prior constraint for cardiac motion analysis.

MATERIALS AND METHODS

The cardiac physiome model comprises an electric wave propagation model, an electromechanical coupling model, and a biomechanical model, which are connected through a cardiac system dynamics for a more complete description of the macroscopic cardiac physiology. Embedded within a multiframe state-space framework, the uncertainties of the model and the patient's measurements are systematically dealt with to arrive at optimal cardiac kinematic estimates and possibly beyond.

RESULTS

Experiments have been conducted to compare our proposed cardiac-physiome-model-based framework with the solely biomechanical model-based framework. The results show that our proposed framework recovers more accurate cardiac deformation from synthetic data and obtains more sensible estimates from real magnetic resonance image sequences.

CONCLUSION

With the active components introduced by the cardiac physiome model, cardiac deformations recovered from patient's medical images are more physiologically plausible.

Theoretical quality assessment of myocardial elastography with in vivo validation

Myocardial elastography (ME), a radio frequency (RF)-based speckle tracking technique with one-dimensional (1-D) cross correlation and novel recorrelation methods in a 2-D search was proposed to estimate and fully image 2-D transmural deformation field and to detect abnormal cardiac function. A theoretical framework was first developed in order to evaluate the performance of 2-D myocardial elastography based on a previously developed 3-D finite-element model of the canine left ventricle. A normal (control) and an ischemic (left-circumflex, LCx) model, which more completely represented myocardial deformation than a kinematic model, were considered. A 2-D convolutional image formation model was first used to generate RF signals for quality assessment of ME in the normal and ischemic cases. A 3-D image formation model was further developed to investigate the effect of the out-of-plane motion on the 2-D, in-plane motion estimation. Both orthogonal, in-plane displacement components (i.e., lateral and axial) between consecutive RF frames were iteratively estimated. All the estimated incremental 2-D displacements from end-diastole (ED) to end-systole (ES) were then accumulated to acquire the cumulative 2-D displacements, which were further used to calculate the cumulative 2-D systolic finite strains. Furthermore, the cumulative systolic radial and circumferential strains, which were angle- and frame-rate independent, were obtained from the 2-D finite-strain components and imaged in full view to detect the ischemic region. We also explored the theoretical understanding of the limitations of our technique for the accurate depiction of disease and validated it in vivo against tagged magnetic resonance imaging (tMRI) in the case of a normal human myocardium in a 2-D short-axis (SA) echocardiographic view. The theoretical framework succeeded in demonstrating that the 2-D myocardial elastography technique was a reliable tool for the complete estimation and depiction of the in-plane myocardial deformation field as well as for accurate identification of pathological mechanical function using established finite-element, left-ventricular canine models. In a preliminary study, the 2-D myocardial elastography was shown capable of imaging myocardial deformation comparable to equivalent tMRI estimates in a clinical setting.

Modeling of skeletal muscle: the influence of tendon and aponeuroses compliance on the force-length relationship

The aim of this study was to investigate the influence of changing elastic properties of tendon and aponeuroses on force production and muscle geometry. A three-dimensional, structural, continuum mechanics model of the cat medial gastrocnemius was used for this purpose. Increasing compliance in tendon and aponeuroses caused a decrease in the peak isometric force and a shift of the force-length relationship to the right of the length axis (i.e. toward greater muscle lengths). This result can be explained with the stability condition of the force-length relationship which produced a history dependence of force production that is conceptually in agreement with experimental observations.

ECG-gated, mechanical and electromechanical wave imaging of cardiovascular tissues in vivo

In simplistic terms, the motion of the heart can be summarized as an active contraction and passive relaxation of the myocardium. However, the local motion of cardiovascular tissues over the course of an entire cardiac cycle results from various transient events such as the valves closing/opening, sudden changes in blood pressure and electrical conduction of the myocardium. The transient motion generated by most of these events occurs within a very short time (on the order of 1 ms) and cannot be imaged correctly with conventional imaging systems, due to their limited temporal resolution. In this paper, we propose a method for imaging this rapid transient motion of tissues in cardiovascular applications. Our method is based on imaging tissues with ultrasound at high frame rates (up to 8000 fps) by synchronizing the two-dimensional (2D) image acquisition on the electrocardiogram (ECG) signals. In vivo feasibility is demonstrated in anesthetized mice. The propagation of several transient mechanical waves was imaged in different regions of the myocardium and the wave phase velocities were found to be between 0.44 m/s and 5 m/s. These waves may be generated by either a purely mechanical effects or through electromechanical coupling in the myocardium depending on the phase of the cardiac cycle, in which they occur. The abdominal aorta was also imaged using the same technique and the propagation of a mechanical pulse wave was imaged. The pulse wave velocity was measured and the Young's modulus of the vessel wall was derived based on the Moens-Korteweg equation. This method could potentially be used for mapping the stiffness of the myocardium and the artery walls and may lead to the early diagnosis of cardiovascular diseases.

Left ventricular form and function revisited: applied translational science to cardiovascular ultrasound imaging

Doppler tissue imaging (DTI) and DTI-derived strain imaging are robust physiologic tools used for the noninvasive assessment of regional myocardial function. As a result of high temporal and spatial resolution, regional function can be assessed for each phase of the cardiac cycle and within the transmural layers of the myocardial wall. Newer techniques that measure myocardial motion by speckle tracking in gray-scale images have overcome the angle dependence of DTI strain, allowing for measurement of 2-dimensional strain and cardiac rotation. DTI, DTI strain, and speckle tracking may provide unique information that deciphers the deformation sequence of complexly oriented myofibers in the left ventricular wall. The data are, however, limited. This review examines the structure and function of the left ventricle relative to the potential clinical application of DTI and speckle tracking in assessing the global mechanical sequence of the left ventricle in vivo.

The challenge of cardiac modeling--interaction and integration

The goal of clinical cardiology is to obtain an integrated picture of the interacting parameters of muscle and vessel mechanics, blood circulation and myocardial perfusion, oxygen consumption and energy metabolism, and electrical activation and heart rate, thus relating to the true physiological and pathophysiological characteristics of the heart. Scientific insight into the cardiac physiology and performance is achieved by utilizing life sciences, for example, molecular biology, genetics and related intra- and intercellular phenomena, as well as the exact sciences, for example, mathematics, computer science, and related imaging and visualization techniques. The tools to achieve these goals are based on the intimate interactions between engineering science and medicine and the developments of modern, medically oriented technology. Most significant is the beneficiary effect of the globalization of science, the Internet, and the unprecedented international interaction and scientific cooperation in facing difficult multidisciplined challenges. This meeting aims to explore some important interactions in the cardiac system and relate to the integration of spatial and temporal interacting system parameters, so as to gain better insight into the structure and function of the cardiac system, thus leading to better therapeutic modalities.

An electromechanical model of the heart for image analysis and simulation

This paper presents a new three-dimensional electromechanical model of the two cardiac ventricles designed both for the simulation of their electrical and mechanical activity, and for the segmentation of time series of medical images. First, we present the volumetric biomechanical models built. Then the transmembrane potential propagation is simulated, based on FitzHugh-Nagumo reaction-diffusion equations. The myocardium contraction is modeled through a constitutive law including an electromechanical coupling. Simulation of a cardiac cycle, with boundary conditions representing blood pressure and volume constraints, leads to the correct estimation of global and local parameters of the cardiac function. This model enables the introduction of pathologies and the simulation of electrophysiology interventions. Moreover, it can be used for cardiac image analysis. A new proactive deformable model of the heart is introduced to segment the two ventricles in time series of cardiac images. Preliminary results indicate that this proactive model, which integrates a priori knowledge on the cardiac anatomy and on its dynamical behavior, can improve the accuracy and robustness of the extraction of functional parameters from cardiac images even in the presence of noisy or sparse data. Such a model also allows the simulation of cardiovascular pathologies in order to test therapy strategies and to plan interventions.

Effect of fiber orientation on propagation: electrical mapping of genetically altered mouse hearts

BACKGROUND

Epicardial potentials reveal the strong effects of fiber anisotropy, rotation, imbrication, and coupling on propagation in the intact heart. From the patterns of the surface potentials, we can obtain information about the local fiber orientation, anisotropy, the transmural fiber rotation, and which direction the wave front is traveling through the wall. In this study, lessons learned from epicardial potential mapping of large hearts were applied to studies conducted in genetically altered mouse hearts.

METHODS

An inducible model of the overexpression of a gain-of-function alpha5 integrin (cytoplasmic domain truncation) was created in mouse. After 3 days of administration of doxycycline, the animals exhibited an altered electrical phenotype of markedly reduced amplitude of the QRS complex on the surface electrocardiogram. Epicardial potentials were recorded from Langendorff-perfused mouse hearts with alpha5 integrin gain-of-function mutations and from wild-type (WT) control hearts. A cylindrical electrode array consisting of 184 sites with 1-mm uniform interelectrode spacing was placed around the heart, and unipolar electrograms were recorded during atrial and ventricular stimulation at different basic cycle lengths.

RESULTS

The total ventricular activation time for the transgenic animals was greater than that of the WT hearts for atrial and ventricular pacing locations. The isopotential maps from the mutated hearts showed a loss of anisotropy, as revealed by the more rounded and less elliptically shaped wave fronts seen immediately after epicardial point stimulation when compared with WT hearts. The weaker potential maxima in the mutated hearts did not exhibit the normal expansion and rotation associated with an advancing wave front in a normal heart, suggesting abnormalities in myocyte coupling in these hearts. Isopotential maps provided additional information about fiber architecture from the electric field that was not obtained from optical recordings alone. These findings provided a phenotypic characterization and specific insights into the mechanisms of the electrical abnormalities associated with altered integrin signaling in cardiac myocytes.

Parameterization of Left Ventricular Wall Motion for Detection of Regional Ischemia

While qualitative wall motion analysis has proven valuable in clinical cardiology practice, quantitative analyses remain too time-consuming for routine clinical use. Our long-term goal is therefore to develop automated methods for quantitative wall motion analysis. In this paper, we utilize a finite element model of the regionally ischemic canine left ventricle to demonstrate a new approach based on parameterization of the left ventricular endocardial surface in prolate spheroidal coordinates. The parameterization provided a substantial data reduction and enabled simple definition, calculation, and display of three-dimensional fractional shortening (3DFS), a quantitative measure of wall motion analogous to the fractional shortening measure used in 2D analysis. The endocardial surface area displaying akinesis or dyskinesis by 3DFS corresponded closely to simulated ischemic region size and 3DFS identified appropriate wall motion abnormalities during experimental coronary occlusion in a canine pilot study. 3DFS therefore appears to be a reasonable candidate for clinical tests to determine its utility in identifying and quantifying acute regional ischemia in patients. By linking state of the art finite element models to the clinically relevant framework of wall motion analysis, the methods presented here will facilitate formulation, in silico prescreening, and clinical testing of additional candidate measures of wall motion.