Quantification of Biventricular Strains in Heart Failure With Preserved Ejection Fraction Patient Using Hyperelastic Warping Method

Heart failure (HF) imposes a major global health care burden on society and suffering on the individual. About 50% of HF patients have preserved ejection fraction (HFpEF). More intricate and comprehensive measurement-focused imaging of multiple strain components may aid in the diagnosis and elucidation of this disease. Here, we describe the development of a semi-automated hyperelastic warping method for rapid comprehensive assessment of biventricular circumferential, longitudinal, and radial strains that is physiological meaningful and reproducible. We recruited and performed cardiac magnetic resonance (CMR) imaging on 30 subjects [10 HFpEF, 10 HF with reduced ejection fraction patients (HFrEF) and 10 healthy controls]. In each subject, a three-dimensional heart model including left ventricle (LV), right ventricle (RV), and septum was reconstructed from CMR images. The hyperelastic warping method was used to reference the segmented model with the target images and biventricular circumferential, longitudinal, and radial strain–time curves were obtained. The peak systolic strains are then measured and analyzed in this study. Intra- and inter-observer reproducibility of the biventricular peak systolic strains was excellent with all ICCs > 0.92. LV peak systolic circumferential, longitudinal, and radial strain, respectively, exhibited a progressive decrease in magnitude from healthy control→HFpEF→HFrEF: control (-15.5 ± 1.90, -15.6 ± 2.06, 41.4 ± 12.2%); HFpEF (-9.37 ± 3.23, -11.3 ± 1.76, 22.8 ± 13.1%); HFrEF (-4.75 ± 2.74, -7.55 ± 1.75, 10.8 ± 4.61%). A similar progressive decrease in magnitude was observed for RV peak systolic circumferential, longitudinal and radial strain: control (-9.91 ± 2.25, -14.5 ± 2.63, 26.8 ± 7.16%); HFpEF (-7.38 ± 3.17, -12.0 ± 2.45, 21.5 ± 10.0%); HFrEF (-5.92 ± 3.13, -8.63 ± 2.79, 15.2 ± 6.33%). Furthermore, septum peak systolic circumferential, longitudinal, and radial strain magnitude decreased gradually from healthy control to HFrEF: control (-7.11 ± 1.81, 16.3 ± 3.23, 18.5 ± 8.64%); HFpEF (-6.11 ± 3.98, -13.4 ± 3.02, 12.5 ± 6.38%); HFrEF (-1.42 ± 1.36, -8.99 ± 2.96, 3.35 ± 2.95%). The ROC analysis indicated LV peak systolic circumferential strain to be the most sensitive marker for differentiating HFpEF from healthy controls. Our results suggest that the hyperelastic warping method with the CMR-derived strains may reveal subtle impairment in HF biventricular mechanics, in particular despite a “normal” ventricular ejection fraction in HFpEF

Doctor of Philosophy

dissertationImage-based biomechanics, particularly numerical modeling using subject-specific data obtained via imaging, has proven useful for elucidating several biomechanical processes, such as prediction of deformation due to external loads, applicable to both normal function and pathophysiology of various organs. As the field evolves towards applications that stretch the limits of imaging hardware and acquisition time, the information traditionally expected as input for numerical routines often becomes incomplete or ambiguous, and requires specific acquisition and processing strategies to ensure physical accuracy and compatibility with predictive mathematical modeling. These strategies, often derivatives or specializations of traditional mechanics, effectively extend the nominal capability of medical imaging hardware providing subject-specific information coupled with the option of using the results for predictive numerical simulations. This research deals with the development of tools for extracting mechanical measurements from a finite set of imaging data and finite element analysis in the context of constructing structural atlases of the heart, understanding the biomechanics of the venous vasculature, and right ventricular failure. The tools include: (1) application of Hyperelastic Warping image registration to displacement-encoded MRI for reconstructing absolute displacement fields, (2) combination of imaging and a material parameter identification approach to measure morphology, deformation, and mechanical properties of vascular tissue, and (3) extrapolation of diffusion tensor MRI acquired at a single time point for the prediction the structural changes across the cardiac cycle with mechanical simulations. Selected tools were then applied to evaluate structural changes in a reversible animal model for right ventricular failure due to pressure overload

Mathematical modelling of myocardial perfusion: coronary flow and myocardial mechanics

Coronary artery disease (CAD) is a condition characterised by the narrowing or blockage of the major blood vessels that supply blood to the heart muscle. This can cause insufficient myocardial perfusion to the heart and deficient cardiac outputs, leading to the possibility of heart failure. CAD is one of the leading causes of morbidity and mortality worldwide. Early and accurate diagnosis and treatment of CAD are essential to minimise the risk of complications, including heart attack or heart failure. In cardiovascular research, computational modelling of coronary circulation is proving to be a valuable tool for gaining insights and information. It enables researchers to isolate the effects of various physiological and pathological conditions on the coronary circulation. Thus, this thesis aimed to develop computational models of one dimensional (1D) coronary flow and three-dimensional (3D) heart. Both models included detailed geometric information tosimulate and predict physiologically realistic results. A one- way coupling of the coronary flow model and the heart model was achieved and produced physiologically accurate myocardial perfusion. Specifically, we first investigated the effect of intramyocardial pressure (IMP) on coronary flow and developed a 1D finite difference coronary flow model. A coronary network based on experimental data was constructed to simulate coronary flow along the complete path of the coronary vasculature. Utilising an assumed aortic pressure, right atrial pressure, and IMP, our simulated coronary pressure and flow rates were in good agreement with published experimental data. It was observed that the majority of the coronary arterial flow on the left side occurs during diastole, while the flow slows down or even reverses during systole. Secondly, we developed a 3D finite element model of the left ventricle (LV) to obtain a more realistic IMP. The LV model was constructed from a patient-specific geometry. The simulated pressure and volume of the LV cavity in repeated cardiac cycles, as well as the ejection fraction, were all within published physiological ranges. We further analysed the stress distributions within the LV wall. Thirdly, a brief review of experimental IMP, as well as calculations of IMP from lumped parameter models and 3D heart models, were presented. Through analysis, we determined a formula for calculating IMP from our 3D LV model. Additionally, we proposed an assignment scheme of the epicardial coronary arteries to the 17 segments of the LV wall recommended by the American Heart Association. Based on the assignment, we devised the one-way coupling framework between the coronary flow model and the LV model to investigate myocardial perfusion. We further developed a bi-ventricular model to investigate the effect of pulmonary regurgitation (PR) on cardiac function. The model provided a computational approach for exploring the influence of PR on right ventricle (RV) dilation and the interaction between LV and RV. Our simulated RV end-diastolic volumes under varying degrees ofPR were comparable with published magnetic resonance imaging data. Moreover, from the long-axis and short-axis views of the bi-ventricular geometry, we observed clearly the motion of the interventricular septum from the baseline case to the severe PR case. This bi-ventricular model was intended to further couple with the coronary flow model to investigate the interaction of right coronary arterial flow and left coronary arterial flow. However, due to time constraints, this has not yet been undertaken. The computational models of the coronary flow and heart developed in this thesis exhibit promising capabilities for providing physiologically accurate predictions of coronary flow and myocardial mechanics. Further application of these models has the potential to deepen our understanding of the underlying mechanisms in physiological coronary flow and various CAD

Mathematical modelling of cardiac function: constitutive law, fibre dispersion, growth and remodelling

The heart is an immensely complex living organ. Myocardium has continually been undergoing adaptive or maladaptive response to surrounding environments, in which the significant importance of growth and remodelling (G&R) has been valued. This PhD project intends to study mechanics modelling of myocardium towards predictive stress/strain-driven growth. Constitutive laws and fibre structures in myocardium work together to determine the mechanical clues which trigger the growth mechanically. Therefore, this project includes two parts: (1) constitutive characterization of myocardium, and (2) myocardial G&R. Constitutive laws and myofibre architectures hold the key to accurately model the biomechanical behaviours of the heart. In the first part of this thesis, we firstly perform an analysis using combinations of uniaxial tension, biaxial tension and simple shear from three different sets of myocardial experimental tissue studies to investigate the descriptive and predictive capabilities of a general invariant-based model that is developed by Holzapfel and Ogden, denoted the HO model. We aim to reduce the constitutive law using the Akaike information criterion to maintain its mechanical integrity whilst achieve minimal computational cost. Our study shows that single-mode tests are insufficient to determine the myocardium responses. It is also essential to consider the transmural fibre rotation within the myocardial samples. We conclude that a competent myocardial material model can be obtained from the general HO model using Akaike information criterion analysis and a suitable combination of tissue tests. Secondly, we develop a neonatal porcine bi-ventricle model with three different myofibre architectures for the left side of the heart. The most realistic one is derived from ex vivo diffusion tensor magnetic resonance image, and the other two simplifications are based on the rule-based methods. We show that the most realistic myofibre architecture model can achieve better cardiac pump functions compared to those of the rule-based models under the same pre/after loads. Our results also reveal that when the cross-fibre contraction is included, the active stress seems to play a dual role: the sheet-normal component enhances the ventricular contraction while the sheet component does the opposite. This study highlights the importance of including myofibre dispersion in cardiac modelling if rule-based methods are used, especially in personalized model. To further describe the detailed fibre distribution, discrete fibre dispersion method is employed to compute passive response because of its advantages in excluding compressed fibres. An additive active stress method that includes cross-fibre active stress is proposed according to the generalised structure tensor method. We find that end-systolic volumes of simulated heart models are much more sensitive to dispersion parameter than end-diastolic volumes. G&R is the focus in the second part of this thesis. An updated reference approach is employed to track the evolution of the reference configuration during G&R, in which the nodal positions and the fibre structure are updated at the beginning of each new growth cycle. Moreover, the homogenised constrained mixture theory is used to describe the G&R process of each constituent within myocardium, which are the ground matrix, collagen network and myofibres. Our models can reproduce the eccentric growth driven by fibre stretch at the diastole, concentric growth driven by fibre stress at the systole, and heterogeneous growth after acute myocardium infarction. Ventricular wall G&R mainly occurs in endocardium, in which the myocyte is the primary responder for the G&R process. G&R laws of collagen fibre have significant impacts on G&R of heart. For example, purely remodeled collagen network without new deposition causes increasingly softer heart wall, leading to excessive heart dilation. Finally, the effects of fibre dispersion on G&R is investigated by including fibre dispersion model in the G&R of infarction model. Highly dispersed fibre structure in the infarcted zone significantly reduces the pump function. This thesis has been focusing on mathematical modelling of biomechanical behaviours of myocardium, firstly on the nonlinear cardiac mechanics including constitutive laws and fibre structures, and then on the G&R process of heart under different pathological conditions. These studies support to choose suitable constitutive laws and fibre architectures in G&R model and illustrate the underlying mechanism of mechanical triggers in G&R. It presents the potential for understanding the mechanics of heart failure and reveal hidden roles of different constituents in myocardium

An image segmentation and registration approach to cardiac function analysis using MRI

Cardiovascular diseases (CVDs) are one of the major causes of death in the world. In recent years, significant progress has been made in the care and treatment of patients with such diseases. A crucial factor for this progress has been the development of magnetic resonance (MR) imaging which makes it possible to diagnose and assess the cardiovascular function of the patient. The ability to obtain high-resolution, cine volume images easily and safely has made it the preferred method for diagnosis of CVDs. MRI is also unique in its ability to introduce noninvasive markers directly into the tissue being imaged(MR tagging) during the image acquisition process. With the development of advanced MR imaging acquisition technologies, 3D MR imaging is more and more clinically feasible. This recent development has allowed new potentially 3D image analysis technologies to be deployed. However, quantitative analysis of cardiovascular system from the images remains a challenging topic. The work presented in this thesis describes the development of segmentation and motion analysis techniques for the study of the cardiac anatomy and function in cardiac magnetic resonance (CMR) images. The first main contribution of the thesis is the development of a fully automatic cardiac segmentation technique that integrates and combines a series of state-of-the-art techniques. The proposed segmentation technique is capable of generating an accurate 3D segmentation from multiple image sequences. The proposed segmentation technique is robust even in the presence of pathological changes, large anatomical shape variations and locally varying contrast in the images. Another main contribution of this thesis is the development of motion tracking techniques that can integrate motion information from different sources. For example, the radial motion of the myocardium can be tracked easily in untagged MR imaging since the epi- and endocardial surfaces are clearly visible. On the other hand, tagged MR imaging allows easy tracking of both longitudinal and circumferential motion. We propose a novel technique based on non-rigid image registration for the myocardial motion estimation using both untagged and 3D tagged MR images. The novel aspect of our technique is its simultaneous use of complementary information from both untagged and 3D tagged MR imaging. The similarity measure is spatially weighted to maximise the utility of information from both images. The thesis also proposes a sparse representation for free-form deformations (FFDs) using the principles of compressed sensing. The sparse free-form deformation (SFFD) model can capture fine local details such as motion discontinuities without sacrificing robustness. We demonstrate the capabilities of the proposed framework to accurately estimate smooth as well as discontinuous deformations in 2D and 3D CMR image sequences. Compared to the standard FFD approach, a significant increase in registration accuracy can be observed in datasets with discontinuous motion patterns. Both the segmentation and motion tracking techniques presented in this thesis have been applied to clinical studies. We focus on two important clinical applications that can be addressed by the techniques proposed in this thesis. The first clinical application aims at measuring longitudinal changes in cardiac morphology and function during the cardiac remodelling process. The second clinical application aims at selecting patients that positively respond to cardiac resynchronization therapy (CRT). The final chapter of this thesis summarises the main conclusions that can be drawn from the work presented here and also discusses possible avenues for future research

When Cardiac Biophysics Meets Groupwise Statistics: Complementary Modelling Approaches for Patient-Specific Medicine

This habilitation manuscript contains research on biophysical and statistical modeling of the heart, as well as interactions between these two approaches

When Cardiac Biophysics Meets Groupwise Statistics: Complementary Modelling Approaches for Patient-Specific Medicine

This habilitation manuscript contains research on biophysical and statistical modeling of the heart, as well as interactions between these two approaches

Three-dimensional biventricular strains in pulmonary arterial hypertension patients using hyperelastic warping

International audienceBackground and Objective: Evaluation of biventricular function is an essential component of clinical management in pulmonary arterial hypertension (PAH). This study aims to examine the utility of biventricular strains derived from a model-to-image registration technique in PAH patients in comparison to age-and gender-matched normal controls. Methods: A three-dimensional (3D) model was reconstructed from cine short-and long-axis cardiac magnetic resonance (CMR) images and subsequently partitioned into right ventricle (RV), left ventricle (LV) and septum. The hyperelastic warping method was used to register the meshed biventricular finite element model throughout the cardiac cycle and obtain the corresponding biventricular circumferential, longitudinal and radial strains. Results: Intra-and inter-observer reproducibility of biventricular strains was excellent with all intra-class correlation coefficients > 0.84. 3D biventricular longitudinal, circumferential and radial strains for RV, LV and septum were significantly decreased in PAH patients compared with controls. Receiver operating characteristic (ROC) analysis showed that the 3D biventricular strains were better early markers (Area under the ROC curve = 0.96 for RV longitudinal strain) of ventricular dysfunction than conventional parameters such as two-dimensional strains and ejection fraction. Conclusions: Our highly reproducible methodology holds potential for extending CMR imaging to characterize 3D biventricular strains, eventually leading to deeper understanding of biventricular mechanics in PAH