Applications of computational modeling in cardiac surgery

Long-term inhaling ultrafine zinc particles increases cardiac wall stresses elevated by myocardial infarction

The analysis of cardiac wall mechanics is of importance for understanding coronary heart diseases (CHD). The inhalation of ultrafine particles could deteriorate CHD. The aim of the study is to investigate the effects of cardiac wall mechanics on rats of myocardial infarction (MI) after long-term inhalation of ultrafine Zn particles. Cardiac wall stresses and strains were computed, based on echocardiographic and hemodynamic measurements. It was found that MI resulted in the significantly elevated stresses and the reduced strains. The short-term inhalation of ultrafine Zn particles decreased stresses and increased strains in MI rats, but the long-term inhalation had the opposite effects. Hence, the short-term inhalation of ultrafine Zn particles could alleviate the MI-induced LV dysfunction while the long-term inhalation impaired it.

Comparison of Left Ventricular Function Derived from Subject-Specific Inverse Finite Element Modeling Based on 3D ECHO and Magnetic Resonance Images

Three-dimensional echocardiography (3D ECHO) and magnetic resonance (MR) imaging are frequently used in patients and animals to evaluate heart functions. Inverse finite element (FE) modeling is increasingly applied to MR images to quantify left ventricular (LV) function and estimate myocardial contractility and other cardiac biomarkers. It remains unclear, however, as to whether myocardial contractility derived from the inverse FE model based on 3D ECHO images is comparable to that derived from MR images. To address this issue, we developed a subject-specific inverse FE model based on 3D ECHO and MR images acquired from seven healthy swine models to investigate if there are differences in myocardial contractility and LV geometrical features derived using these two imaging modalities. We showed that end-systolic and end-diastolic volumes derived from 3D ECHO images are comparable to those derived from MR images (R2=0.805 and 0.969, respectively). As a result, ejection fraction from 3D ECHO and MR images are linearly correlated (R2=0.977) with the limit of agreement (LOA) ranging from -17.95% to 45.89%. Using an inverse FE modeling to fit pressure and volume waveforms in subject-specific LV geometry reconstructed from 3D ECHO and MR images, we found that myocardial contractility derived from these two imaging modalities are linearly correlated with an R2 value of 0.989, a gradient of 0.895, and LOA ranging from -6.11% to 36.66%. This finding supports using 3D ECHO images in image-based inverse FE modeling to estimate myocardial contractility.

Review of cardiac-coronary interaction and insights from mathematical modeling

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

A Predictive Toxicokinetic Model for Nickel Leaching from Vascular Stents

In vitro testing methods offer valuable insights into the corrosion vulnerability of metal implants and enable prompt comparison between devices. However, they fall short in predicting the extent of leaching and the biodistribution of implant byproducts under in vivo conditions. Physiologically based toxicokinetic (PBTK) models are capable of quantitatively establishing such correlations and therefore provide a powerful tool in advancing nonclinical methods to test medical implants and assess patient exposure to implant debris. In this study, we present a multicompartment PBTK model and a simulation engine for toxicological risk assessment of vascular stents. The mathematical model consists of a detailed set of constitutive equations that describe the transfer of nickel ions from the device to peri-implant tissue and circulation and the nickel mass exchange between blood and the various tissues/organs and excreta. Model parameterization was performed using (1) in-house-produced data from immersion testing to compute the device-specific diffusion parameters and (2) full-scale animal in situ implantation studies to extract the mammalian-specific biokinetic functions that characterize the time-dependent biodistribution of the released ions. The PBTK model was put to the test using a simulation engine to estimate the concentration-time profiles, along with confidence intervals through probabilistic Monte Carlo, of nickel ions leaching from the implanted devices and determine if permissible exposure limits are exceeded. The model-derived output demonstrated prognostic conformity with reported experimental data, indicating that it may provide the basis for the broader use of modeling and simulation tools to guide the optimal design of implantable devices in compliance with exposure limits and other regulatory requirements.

Reduced left ventricular dynamics modeling based on a cylindrical assumption

Biomechanical modeling and simulation is expected to play a significant role in the development of the next generation tools in many fields of medicine. However, full-order finite element models of complex organs such as the heart can be computationally very expensive, thus limiting their practical usability. Therefore, reduced models are much valuable to be used, for example, for pre-calibration of full-order models, fast predictions, real-time applications, and so forth. In this work, focused on the left ventricle, we develop a reduced model by defining reduced geometry & kinematics while keeping general motion and behavior laws, allowing to derive a reduced model where all variables & parameters have a strong physical meaning. More specifically, we propose a reduced ventricular model based on cylindrical geometry & kinematics, which allows to describe the myofiber orientation through the ventricular wall and to represent contraction patterns such as ventricular twist, two important features of ventricular mechanics. Our model is based on the original cylindrical model of Guccione, McCulloch, & Waldman (1991); Guccione, Waldman, & McCulloch (1993), albeit with multiple differences: we propose a fully dynamical formulation, integrated into an open-loop lumped circulation model, and based on a material behavior that incorporates a fine description of contraction mechanisms; moreover, the issue of the cylinder closure has been completely reformulated; our numerical approach is novel aswell, with consistent spatial (finite element) and time discretizations. Finally, we analyze the sensitivity of the model response to various numerical and physical parameters, and study its physiological response.

Comparison of interpolation methods of predominant cardiomyocyte orientation from in vivo and ex vivo cardiac diffusion tensor imaging data

Cardiac electrophysiology and cardiac mechanics both depend on the average cardiomyocyte long-axis orientation. In the realm of personalized medicine, knowledge of the patient-specific changes in cardiac microstructure plays a crucial role. Patient-specific computational modelling has emerged as a tool to better understand disease progression. In vivo cardiac diffusion tensor imaging (cDTI) is a vital tool to non-destructively measure the average cardiomyocyte long-axis orientation in the heart. However, cDTI suffers from long scan times, rendering volumetric, high-resolution acquisitions challenging. Consequently, interpolation techniques are needed to populate bio-mechanical models with patient-specific average cardiomyocyte long-axis orientations. In this work, we compare five interpolation techniques applied to in vivo and ex vivo porcine input data. We compare two tensor interpolation approaches, one rule-based approximation, and two data-driven, low-rank models. We demonstrate the advantage of tensor interpolation techniques, resulting in lower interpolation errors than do low-rank models and rule-based methods adapted to cDTI data. In an ex vivo comparison, we study the influence of three imaging parameters that can be traded off against acquisition time: in-plane resolution, signal to noise ratio, and number of acquired short-axis imaging slices.

Estimation of Regional Pulmonary Compliance in Idiopathic Pulmonary Fibrosis Based On Personalized Lung Poromechanical Modeling

Pulmonary function is tightly linked to the lung mechanical behavior, especially large deformation during breathing. Interstitial lung diseases, such as Idiopathic Pulmonary Fibrosis (IPF), have an impact on the pulmonary mechanics and consequently alter lung function. However, IPF remains poorly understood, poorly diagnosed and poorly treated. Currently, the mechanical impact of such diseases is assessed by pressure-volume curves, giving only global information. We developed a poromechanical model of the lung that can be personalized to a patient based on routine clinical data. The personalization pipeline uses clinical data, mainly CT-images at two time steps and involves the formulation of an inverse problem to estimate regional compliances. The estimation problem can be formulated both in terms of "effective", i.e., without considering the mixture porosity, or "rescaled", i.e., where the first-order effect of the porosity has been taken into account, compliances. Regional compliances are estimated for one control subject and three IPF patients, allowing to quantify the IPF-induced tissue stiffening. This personalized model could be used in the clinic as an objective and quantitative tool for IPF diagnosis.

Creation of Anatomically Correct and Optimized for 3D Printing Human Bones Models

Educational institutions in several countries state that the education sector should be modernized to ensure a contemporary, individualized, and more open learning process by introducing and developing advance digital solutions and learning tools. Visualization along with 3D printing have already found their implementation in different medical fields in Pauls Stradiņš Clinical University Hospital, and Rīga Stradiņš University, where models are being used for prosthetic manufacturing, surgery planning, simulation of procedures, and student education. The study aimed to develop a detailed methodology for the creation of anatomically correct and optimized models for 3D printing from radiological data using only free and widely available software. In this study, only free and cross-platform software from widely available internet sources has been used—“Meshmixer”, “3D Slicer”, and “Meshlab”. For 3D printing, the Ultimaker 5S 3D printer along with PLA material was used. In its turn, radiological data have been obtained from the “New Mexico Decedent Image Database”. In total, 28 models have been optimized and printed. The developed methodology can be used to create new models from scratch, which can be used will find implementation in different medical and scientific fields—simulation processes, anthropology, 3D printing, bioprinting, and education.

Mechanical and Structural Remodeling of Cardiac Muscle after Aerobic and Resistance Exercise Training in Rats

INTRODUCTION

Aerobic and resistance exercise training results in distinct structural changes of the heart. The mechanics of how cardiac cells adapt to resistance training and the benefits to cells when combining aerobic and resistance exercise remains largely unknown. The purpose of this study was to compare mechanical adaptations of skinned cardiac fiber bundles after chronic resistance, aerobic and combined exercise training in rats. We hypothesized that differences in mechanical function on the fiber bundle level coincide with differences previously reported in the structure of the heart.

METHOD

Twelve-week-old rats were assigned to (i) an aerobic running group (n = 6), (ii) a ladder climbing resistance group (n = 6), (iii) a combination group subjected to aerobic and resistance training (n = 6), or (iv) a sedentary (control) group (n = 5). Echocardiography was used to measure cardiac structural remodeling. Skinned cardiac fiber bundles were used to determine active and passive force properties, maximal shortening velocity, and calcium sensitivity.

RESULTS

Aerobically trained animals had 43%-49% greater ventricular volume and myocardial thickness, and a 4%-17% greater shortening velocity and calcium sensitivity compared with control group rats. Resistance-trained rats had 37%-71% thicker ventricular walls, a 56% greater isometric force production, a 9% greater shortening velocity, and a 4% greater calcium sensitivity compared with control group rats. The combination exercise-trained rats had 25%-43% greater ventricular volume and myocardial wall thickness, a 55% greater active force production, a 7% greater shortening velocity, and a 60% greater cross-bridge cooperativity compared with control group rats.

CONCLUSIONS

The heart adapts differently to each exercise modality, and a combination of aerobic and resistance training may have the greatest benefit for cardiac health and performance.

Digital Health Primer for Cardiothoracic Surgeons

The burgeoning demands for quality, safety, and value in cardiothoracic surgery, in combination with the advancement and acceleration of digital health solutions and information technology, provide a unique opportunity to improve efficiency and effectiveness simultaneously in cardiothoracic surgery. This primer on digital health explores and reviews data integration, data processing, complex modeling, telehealth with remote monitoring, and cybersecurity as they shape the future of cardiothoracic surgery.

Simulating the effect of sodium channel blockage on cardiac electromechanics

There is growing interest to better understand drug-induced cardiovascular complications and to predict undesirable side effects at as early a stage in the drug development process as possible. The purpose of this paper is to investigate computationally the influence of sodium ion channel blockage on cardiac electromechanics. To do so, we implement a myofiber orientation dependent passive stress model (Holzapfel-Ogden) in the multiphysics solver Chaste to simulate an imaged physiological model of the human ventricles. A dosage of a sodium channel blocker was then applied and its inhibitory effects on the electrical propagation across ventricles were modeled. We employ the Kerckhoffs active stress model to generate electrically excited contractile behavior of myofibers. Our predictions indicate that a delay in the electrical activation of ventricular tissue caused by the sodium channel blockage translates to a delay in the mechanical biomarkers that were investigated. Moreover, sodium channel blockage was found to increase left ventricular twist. A multiphysics computational framework from the cell level to the organ level was thus used to predict the effect of sodium channel blocking drugs on cardiac electromechanics.

An investigation of layer-specific tissue biomechanics of porcine atrioventricular valve anterior leaflets

Atrioventricular heart valves (AHVs) are composed of structurally complex and morphologically heterogeneous leaflets. The coaptation of these leaflets during the cardiac cycle facilitates unidirectional blood flow. Valve regurgitation is treated preferably by surgical repair if possible or replacement based on the disease state of the valve tissue. A comprehensive understanding of valvular morphology and mechanical properties is crucial to refining computational models, serving as a patient-specific diagnostic and surgical tool for preoperative planning. Previous studies have modeled the stress distribution throughout the leaflet's thickness, but validations with layer-specific biaxial mechanical experiments are missing. In this study, we sought to fill this gap in literature by investigating the impact of microstructure constituents on mechanical behavior throughout the thickness of the AHVs' anterior leaflets. Porcine mitral valve anterior leaflets (MVAL) and tricuspid valve anterior leaflets (TVAL) were micro-dissected into three layers (atrialis/spongiosa, fibrosa, and ventricular) and two layers (atrialis/spongiosa and fibrosa/ventricularis), respectively, based on their relative distributions of extracellular matrix components as quantified by histological analyses: collagen, elastin, and glycosaminoglycans. Our results suggest that (i) for both valves, the atrialis/spongiosa layer is the most extensible and anisotropic layer, possibly due to its relatively low collagen content as compared to other layers, (ii) the intact TVAL response is stiffer than the atrialis/spongiosa layer but more compliant than the fibrosa/ventricularis layer, and (iii) the MVAL fibrosa and ventricularis layers behave nearly isotropic. These novel findings emphasize the biomechanical variances throughout the AHV leaflets, and our results could better inform future AHV computational model developments. STATEMENT OF SIGNIFICANCE: This study, which is the first of its kind for atrioventricular heart valve (AHV) leaflet tissue layers, rendered a mechanical characterization of the biaxial mechanical properties and distributions of extracellular matrix components (collagen, elastin, and glycosaminoglycans) of the mitral and tricuspid valve anterior leaflet layers. The novel findings from the present study emphasize the biomechanical variances throughout the thickness of AHV leaflets, and our results indicate that the previously-adopted homogenous leaflet in the AHV biomechanical modeling may be an oversimplification of the complex leaflet anatomy. Such improvement in the understanding of valvular morphology and tissue mechanics is crucial to future refinement of AHV computational models, serving as a patient-specific diagnostic and surgical tool, at the preoperative stage, for treating valvular heart diseases.

Kinematic boundary conditions substantially impact in silico ventricular function

Computational cardiac mechanical models, individualized to the patient, have the potential to elucidate the fundamentals of cardiac (patho-)physiology, enable non-invasive quantification of clinically significant metrics (eg, stiffness, active contraction, work), and anticipate the potential efficacy of therapeutic cardiovascular intervention. In a clinical setting, however, the available imaging resolution is often limited, which limits cardiac models to focus on the ventricles, without including the atria, valves, and proximal arteries and veins. In such models, the absence of surrounding structures needs to be accounted for by imposing realistic kinematic boundary conditions, which, for prognostic purposes, are preferably generic and thus non-image derived. Unfortunately, the literature on cardiac models shows no consistent approach to kinematically constrain the myocardium. The impact of different approaches (eg, fully constrained base, constrained epi-ring) on the predictive capacity of cardiac mechanical models has not been thoroughly studied. For that reason, this study first gives an overview of current approaches to kinematically constrain (bi) ventricular models. Next, we developed a patient-specific in silico biventricular model that compares well with literature and in vivo recorded strains. Alternative constraints were introduced to assess the influence of commonly used mechanical boundary conditions on both the predicted global functional behavior of the in-silico heart (cavity volumes, stroke volume, ejection fraction) and local strain distributions. Meaningful differences in global functioning were found between different kinematic anchoring strategies, which brought forward the importance of selecting appropriate boundary conditions for biventricular models that, in the near future, may inform clinical intervention. However, whilst statistically significant differences were also found in local strain distributions, these differences were minor and mostly confined to the region close to the applied boundary conditions.

Equilibrated warping: Finite element image registration with finite strain equilibrium gap regularization

In this paper, we propose a novel continuum finite strain formulation of the equilibrium gap regularization for image registration. The equilibrium gap regularization essentially penalizes any deviation from the solution of a hyperelastic body in equilibrium with arbitrary loads prescribed at the boundary. It thus represents a regularization with strong mechanical basis, especially suited for cardiac image analysis. We describe the consistent linearization and discretization of the regularized image registration problem, in the framework of the finite elements method. The method is implemented using FEniCS & VTK, and distributed as a freely available python library. We show that the equilibrated warping method is effective and robust: regularization strength and image noise have minimal impact on motion tracking, especially when compared to strain-based regularization methods such as hyperelastic warping. We also show that equilibrated warping is able to extract main deformation features on both tagged and untagged cardiac magnetic resonance images.

Efficient estimation of personalized biventricular mechanical function employing gradient-based optimization

Individually personalized computational models of heart mechanics can be used to estimate important physiological and clinically-relevant quantities that are difficult, if not impossible, to directly measure in the beating heart. Here, we present a novel and efficient framework for creating patient-specific biventricular models using a gradient-based data assimilation method for evaluating regional myocardial contractility and estimating myofiber stress. These simulations can be performed on a regular laptop in less than 2 h and produce excellent fit between measured and simulated volume and strain data through the entire cardiac cycle. By applying the framework using data obtained from 3 healthy human biventricles, we extracted clinically important quantities as well as explored the role of fiber angles on heart function. Our results show that steep fiber angles at the endocardium and epicardium are required to produce simulated motion compatible with measured strain and volume data. We also find that the contraction and subsequent systolic stresses in the right ventricle are significantly lower than that in the left ventricle. Variability of the estimated quantities with respect to both patient data and modeling choices are also found to be low. Because of its high efficiency, this framework may be applicable to modeling of patient specific cardiac mechanics for diagnostic purposes.

Modeling Right Ventricle Failure After Continuous Flow Left Ventricular Assist Device: A Biventricular Finite-Element and Lumped-Parameter Analysis

The risk of right ventricle (RV) failure remains a major contraindication for continuous-flow left ventricular assist device (CF-LVAD) implantation in patients with heart failure. It is therefore critical to identify the patients who will benefit from early intervention to avoid adverse outcomes. We sought to advance the computational modeling description of the mechanisms underlying RV failure in LVAD-supported patients. RV failure was studied by computational modeling of hemodynamic and cardiac mechanics using lumped-parameter and biventricular finite element (FE) analysis. Findings were validated by comparison of bi-dimensional speckle-tracking echocardiographic strain assessment of the RV free wall vs. patient-specific computational strain estimations, and by non-invasive lumped-based hemodynamic predictions vs. invasive right heart catheterization data. Correlation analysis revealed that lumped-derived RV cardiac output (R = 0.94) and RV stroke work index (R = 0.85) were in good agreement with catheterization data collected from 7 patients with CF-LVAD. Biventricular FE analysis showed abnormal motion of the interventricular septum towards the left ventricular free wall, suggesting impaired right heart mechanics. Good agreement between computationally predicted and echocardiographic measured longitudinal strains was found at basal (- 19.1 ± 3.0% for ECHO, and - 16.4 ± 3.2% for FEM), apical (- 20.0 ± 3.7% for ECHO, and - 17.4 ± 2.7% for FEM), and mid-level of the RV free wall (- 20.1 ± 5.9% for echo, and - 18.0 ± 5.4% for FEM). Simulation approach here presented could serve as a tool for less invasive and early diagnosis of the severity of RV failure in patients with LVAD, although future studies are needed to validate our findings against clinical outcomes.

The importance of mechano-electrical feedback and inertia in cardiac electromechanics

In the past years, a number cardiac electromechanics models have been developed to better understand the excitation-contraction behavior of the heart. However, there is no agreement on whether inertial forces play a role in this system. In this study, we assess the influence of mass in electromechanical simulations, using a fully coupled finite element model. We include the effect of mechano-electrical feedback via stretch activated currents. We compare five different models: electrophysiology, electromechanics, electromechanics with mechano-electrical feedback, electromechanics with mass, and electromechanics with mass and mechano-electrical feedback. We simulate normal conduction to study conduction velocity and spiral waves to study fibrillation. During normal conduction, mass in conjunction with mechano-electrical feedback increased the conduction velocity by 8.12% in comparison to the plain electrophysiology case. During the generation of a spiral wave, mass and mechano-electrical feedback generated secondary wavefronts, which were not present in any other model. These secondary wavefronts were initiated in tensile stretch regions that induced electrical currents. We expect that this study will help the research community to better understand the importance of mechanoelectrical feedback and inertia in cardiac electromechanics.

Utility of cardiac magnetic resonance for evaluation of mitral regurgitation prior to mitral valve surgery

Mitral regurgitation (MR) is a common cause of morbidity worldwide and an accepted indication for interventional therapies which aim to reduce or resolve adverse clinical outcomes associated with MR. Cardiac magnetic resonance (CMR) provides highly accurate means of assessing MR, including a variety of approaches that can measure MR based on quantitative flow. Additionally, CMR is widely accepted as a reference standard for cardiac chamber quantification, enabling reliable detection of subtle changes in cardiac chamber size and function so as to guide decision-making regarding timing of mitral valve directed therapies. Beyond geometric imaging, CMR enables tissue characterization of ischemia and infarction in the left ventricular (LV) myocardium as well as within the mitral valve apparatus, thus enabling identification of structural substrates for MR. This review provides an overview of established and emerging CMR approaches to measure valvular regurgitation, including relative utility of different approaches for patients with primary or secondary MR. Clinical outcomes studies are discussed with focus on data demonstrating advantages of CMR for guiding diagnosis, risk stratification, and management of patients with known or suspected MR. Comparative data is reviewed with focus on diagnostic performance of CMR in comparison to conventional assessment via echocardiography (echo). Emerging literature is reviewed concerning potential new approaches that utilize CMR tissue characterization to guide clinical decision-making in order to improve therapeutic outcomes and clinical prognosis for patients with MR.

Characterization of patient-specific biventricular mechanics in heart failure with preserved ejection fraction: Hyperelastic warping

Heart failure with preserved ejection fraction (HFPEF) is considered as a major public health problem. Traditionally, HFPEF is diagnosed based on a "normal" EF, but the studies have explored the potential role of left ventricular mechanics. Furthermore, right ventricular mechanics and bi-ventricular interaction in HFPEF is currently not well understood. In this study, we aim to develop a framework using a hyperelastic warping approach to quantify bi-ventricular and septum strains from cardiac magnetic resonance (CMR) images. Whole heart models were reconstructed in HFPEF, HF with reduced EF (HFREF) and normal control patients, and a Laplace-Dirichlet Rule-Based (LDRB) algorithm was employed to assign circumferential orientation. The LV circumferential strain was 10.56% in normal control, and decreased to 5.90% in HFPEF and 1.66% in HFREF. Interestingly, the RV circumferential strain was 7.29% in normal control, but increased to 8.93% in HFPEF, and decreased to 2.16% in HFREF. The septum circumferential strain was comparable between HFPEF and normal control. Heart failure with preserved ejection fraction demonstrated augmented right ventricular strain and comparable septum strain to maintain its "normal" ejection fraction. This might unveil a new mechanism of bi-ventricular interaction and compensation in heart failure with preserved ejection fraction.

Multi-scale Modeling of the Cardiovascular System: Disease Development, Progression, and Clinical Intervention

Cardiovascular diseases (CVDs) are the leading cause of death in the western world. With the current development of clinical diagnostics to more accurately measure the extent and specifics of CVDs, a laudable goal is a better understanding of the structure-function relation in the cardiovascular system. Much of this fundamental understanding comes from the development and study of models that integrate biology, medicine, imaging, and biomechanics. Information from these models provides guidance for developing diagnostics, and implementation of these diagnostics to the clinical setting, in turn, provides data for refining the models. In this review, we introduce multi-scale and multi-physical models for understanding disease development, progression, and designing clinical interventions. We begin with multi-scale models of cardiac electrophysiology and mechanics for diagnosis, clinical decision support, personalized and precision medicine in cardiology with examples in arrhythmia and heart failure. We then introduce computational models of vasculature mechanics and associated mechanical forces for understanding vascular disease progression, designing clinical interventions, and elucidating mechanisms that underlie diverse vascular conditions. We conclude with a discussion of barriers that must be overcome to provide enhanced insights, predictions, and decisions in pre-clinical and clinical applications.

Computational modeling of acute myocardial infarction

Myocardial infarction, commonly known as heart attack, is caused by reduced blood supply and damages the heart muscle because of a lack of oxygen. Myocardial infarction initiates a cascade of biochemical and mechanical events. In the early stages, cardiomyocytes death, wall thinning, collagen degradation, and ventricular dilation are the immediate consequences of myocardial infarction. In the later stages, collagenous scar formation in the infarcted zone and hypertrophy of the non-infarcted zone are auto-regulatory mechanisms to partly correct for these events. Here we propose a computational model for the short-term adaptation after myocardial infarction using the continuum theory of multiplicative growth. Our model captures the effects of cell death initiating wall thinning, and collagen degradation initiating ventricular dilation. Our simulations agree well with clinical observations in early myocardial infarction. They represent a first step toward simulating the progression of myocardial infarction with the ultimate goal to predict the propensity toward heart failure as a function of infarct intensity, location, and size.

Spin echo versus stimulated echo diffusion tensor imaging of the in vivo human heart

Purpose

To compare signal‐to‐noise ratio (SNR) efficiency and diffusion tensor metrics of cardiac diffusion tensor mapping using acceleration‐compensated spin‐echo (SE) and stimulated echo acquisition mode (STEAM) imaging.

Methods

Diffusion weighted SE and STEAM sequences were implemented on a clinical 1.5 Tesla MR system. The SNR efficiency of SE and STEAM was measured (b = 50–450 s/mm²) in isotropic agar, anisotropic diffusion phantoms and the in vivo human heart. Diffusion tensor analysis was performed on mean diffusivity, fractional anisotropy, helix and transverse angles.

Results

In the isotropic phantom, the ratio of SNR efficiency for SE versus STEAM, SNR_t(SE/STEAM), was 2.84 ± 0.08 for all tested b‐values. In the anisotropic diffusion phantom the ratio decreased from 2.75 ± 0.05 to 2.20 ± 0.13 with increasing b‐value, similar to the in vivo decrease from 2.91 ± 0.43 to 2.30 ± 0.30. Diffusion tensor analysis revealed reduced deviation of helix angles from a linear transmural model and reduced transverse angle standard deviation for SE compared with STEAM. Mean diffusivity and fractional anisotropy were measured to be statistically different (P < 0.001) between SE and STEAM.

Conclusion

Cardiac DTI using motion‐compensated SE yields a 2.3–2.9× increase in SNR efficiency relative to STEAM and improved accuracy of tensor metrics. The SE method hence presents an attractive alternative to STEAM based approaches. Magn Reson Med 76:862–872, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

An integrated electromechanical-growth heart model for simulating cardiac therapies

An emerging class of models has been developed in recent years to predict cardiac growth and remodeling (G&R). We recently developed a cardiac G&R constitutive model that predicts remodeling in response to elevated hemodynamics loading, and a subsequent reversal of the remodeling process when the loading is reduced. Here, we describe the integration of this G&R model to an existing strongly coupled electromechanical model of the heart. A separation of timescale between growth deformation and elastic deformation was invoked in this integrated electromechanical-growth heart model. To test our model, we applied the G&R scheme to simulate the effects of myocardial infarction in a realistic left ventricular (LV) geometry using the finite element method. We also simulate the effects of a novel therapy that is based on alteration of the infarct mechanical properties. We show that our proposed model is able to predict key features that are consistent with experiments. Specifically, we show that the presence of a non-contractile infarct leads to a dilation of the left ventricle that results in a rightward shift of the pressure volume loop. Our model also predicts that G&R is attenuated by a reduction in LV dilation when the infarct stiffness is increased.

Second-order motion-compensated spin echo diffusion tensor imaging of the human heart

PURPOSE

Myocardial microstructure has been challenging to probe in vivo. Spin echo-based diffusion-weighted sequences allow for single-shot acquisitions but are highly sensitive to cardiac motion. In this study, the use of second-order motion-compensated diffusion encoding was compared with first-order motion-compensated diffusion-weighted imaging during systolic contraction of the heart.

METHODS

First- and second-order motion-compensated diffusion encoding gradients were incorporated into a triggered single-shot spin echo sequence. The effect of contractile motion on the apparent diffusion coefficients and tensor orientations was investigated in vivo from basal to apical level of the heart.

RESULTS

Second-order motion compensation was found to increase the range of systolic trigger delays from 30%-55% to 15%-77% peak systole at the apex and from 25%-50% to 15%-79% peak systole at the base. Diffusion tensor analysis yielded more physiological transmural distributions when using second-order motion-compensated diffusion tensor imaging.

CONCLUSION

Higher-order motion-compensated diffusion encoding decreases the sensitivity to cardiac motion, thereby enabling cardiac DTI over a wider range of time points during systolic contraction of the heart.

Heterogeneous growth-induced prestrain in the heart

Even when entirely unloaded, biological structures are not stress-free, as shown by Y.C. Fung׳s seminal opening angle experiment on arteries and the left ventricle. As a result of this prestrain, subject-specific geometries extracted from medical imaging do not represent an unloaded reference configuration necessary for mechanical analysis, even if the structure is externally unloaded. Here we propose a new computational method to create physiological residual stress fields in subject-specific left ventricular geometries using the continuum theory of fictitious configurations combined with a fixed-point iteration. We also reproduced the opening angle experiment on four swine models, to characterize the range of normal opening angle values. The proposed method generates residual stress fields which can reliably reproduce the range of opening angles between 8.7±1.8 and 16.6±13.7 as measured experimentally. We demonstrate that including the effects of prestrain reduces the left ventricular stiffness by up to 40%, thus facilitating the ventricular filling, which has a significant impact on cardiac function. This method can improve the fidelity of subject-specific models to improve our understanding of cardiac diseases and to optimize treatment options.

Human Cardiac Function Simulator for the Optimal Design of a Novel Annuloplasty Ring with a Sub-valvular Element for Correction of Ischemic Mitral Regurgitation

Ischemic mitral regurgitation is associated with substantial risk of death. We sought to: (1) detail significant recent improvements to the Dassault Systèmes human cardiac function simulator (HCFS); (2) use the HCFS to simulate normal cardiac function as well as pathologic function in the setting of posterior left ventricular (LV) papillary muscle infarction; and (3) debut our novel device for correction of ischemic mitral regurgitation. We synthesized two recent studies of human myocardial mechanics. The first study presented the robust and integrative finite element HCFS. Its primary limitation was its poor diastolic performance with an LV ejection fraction below 20% caused by overly stiff ex vivo porcine tissue parameters. The second study derived improved diastolic myocardial material parameters using in vivo MRI data from five normal human subjects. We combined these models to simulate ischemic mitral regurgitation by computationally infarcting an LV region including the posterior papillary muscle. Contact between our novel device and the mitral valve apparatus was simulated using Dassault Systèmes SIMULIA software. Incorporating improved cardiac geometry and diastolic myocardial material properties in the HCFS resulted in a realistic LV ejection fraction of 55%. Simulating infarction of posterior papillary muscle caused regurgitant mitral valve mechanics. Implementation of our novel device corrected valve dysfunction. Improvements in the current study to the HCFS permit increasingly accurate study of myocardial mechanics. The first application of this simulator to abnormal human cardiac function suggests that our novel annuloplasty ring with a sub-valvular element will correct ischemic mitral regurgitation.

Distribution of normal human left ventricular myofiber stress at end diastole and end systole: a target for in silico design of heart failure treatments

Ventricular wall stress is believed to be responsible for many physical mechanisms taking place in the human heart, including ventricular remodeling, which is frequently associated with heart failure. Therefore, normalization of ventricular wall stress is the cornerstone of many existing and new treatments for heart failure. In this paper, we sought to construct reference maps of normal ventricular wall stress in humans that could be used as a target for in silico optimization studies of existing and potential new treatments for heart failure. To do so, we constructed personalized computational models of the left ventricles of five normal human subjects using magnetic resonance images and the finite-element method. These models were calibrated using left ventricular volume data extracted from magnetic resonance imaging (MRI) and validated through comparison with strain measurements from tagged MRI (950 ± 170 strain comparisons/subject). The calibrated passive material parameter values were C0 = 0.115 ± 0.008 kPa and B0 = 14.4 ± 3.18; the active material parameter value was Tmax = 143 ± 11.1 kPa. These values could serve as a reference for future construction of normal human left ventricular computational models. The differences between the predicted and the measured circumferential and longitudinal strains in each subject were 3.4 ± 6.3 and 0.5 ± 5.9%, respectively. The predicted end-diastolic and end-systolic myofiber stress fields for the five subjects were 2.21 ± 0.58 and 16.54 ± 4.73 kPa, respectively. Thus these stresses could serve as targets for in silico design of heart failure treatments.