In Vivo Human Right Ventricle Shape and Kinematic Analysis with and without Pulmonary Hypertension

Pulmonary hypertension (PH) is a severe cardio-pulmonary illness which has been commonly observed to induce substantial and ultimately deleterious changes to the human right ventricle (RV) shape and function. As such, the functional state of the RV is thought to be a major determinant of symptoms and survival rates for PH. However, there has been little success to-date to identify clinically obtainable metrics of RV shape and deformation as a means to detect the onset and progression of PH. This difficulty is largely the result of the absence of a proven approach that is generally applicable for consistent and reliable quantitative analysis of anatomical shapes, particularly the RV, between patients and over time. Therefore, a computational framework which can quantitatively analyze RV shape and deformation could be a key to assist in clinically detecting the onset and progression of PH. Statistical shape analysis techniques were developed, implemented, and assessed to analyze variations in human RV endocardial surface (RVES) shapes and kinematics from noninvasive clinical medical imaging data with respect to a spectrum of hemodynamic states. A computational framework for the quantitative analysis and statistical decomposition of sets of 3D genus-0 shapes that combines a modified harmonic mapping approach directly with proper orthogonal decomposition (DM-POD) is presented. The DM-POD approach is shown to be a robust technique for recovering inherent shape-related features through the analysis of sets of artificially generated shapes. The DM-POD approach is then applied to obtain kinematic features of the human RV based on the relative change in shape of the endocardial surface using cardiac computed tomography images. In addition, the kinematic features of the RVES obtained by the DM-POD approach are shown to be consistent and associated with intrinsically physiological components of the heart, and thus may potentially provide a more accurate means for classifying the progressive change in RV function caused by PH, in comparison to traditional clinical hemodynamic and volume-based metrics. Statistical shape analysis for the human RV is further evaluated through analysis of alternate components of the DM-POD approach, as well as through comparison of the DM-POD workflow with an alternate spherical harmonic function-based workflow (SPHARM), with respect to the aspects of surface representation, alignment, and decomposition. Additionally, different ways of utilizing the available imaging data with respect to the classification potential are investigated by considering analysis results when applying both the various DM-POD and SPHARM approaches with several different combinations of the phases captured throughout a single cardiac cycle for the patient set. Lastly, a novel statistical decomposition technique known as independent component analysis (ICA) was incorporated into the statistical shape analysis framework (i.e., DM-POD) to produce an alternative workflow (DM-ICA). Both the DM-POD and DM-ICA approaches are applied to analyze sets of artificially generated data and the human RVES datasets, and the respective results are compared. The DM-POD and DM-ICA workflows are shown to produce consistent, but substantially different results due to the various principles and views of each of the two statistical decomposition algorithms (i.e., POD and ICA). Most importantly, the results from the DM-POD and DM-ICA workflows appear to relate to RV function in unique ways, with respect to both traditional clinical metrics and each other, and have the potential to provide new metrics for better understanding of the human RV and its relationship to PH

A mathematical model that integrates cardiac electrophysiology, mechanics, and fluid dynamics: Application to the human left heart

: We propose a mathematical and numerical model for the simulation of the heart function that couples cardiac electrophysiology, active and passive mechanics and hemodynamics, and includes reduced models for cardiac valves and the circulatory system. Our model accounts for the major feedback effects among the different processes that characterize the heart function, including electro-mechanical and mechano-electrical feedback as well as force-strain and force-velocity relationships. Moreover, it provides a three-dimensional representation of both the cardiac muscle and the hemodynamics, coupled in a fluid-structure interaction (FSI) model. By leveraging the multiphysics nature of the problem, we discretize it in time with a segregated electrophysiology-force generation-FSI approach, allowing for efficiency and flexibility in the numerical solution. We employ a monolithic approach for the numerical discretization of the FSI problem. We use finite elements for the spatial discretization of partial differential equations. We carry out a numerical simulation on a realistic human left heart model, obtaining results that are qualitatively and quantitatively in agreement with physiological ranges and medical images

Three-dimensional myocardial strain estimation from volumetric ultrasound: experimental validation in an animal model

Although real-time three-dimensional echocardiography has the potential to allow for more accurate assessment of global and regional ventricular dynamics compared to the more traditional two-dimensional ultrasound examinations, it still requires rigorous testing and validation against other accepted techniques should it breakthrough as a standard examination in routine clinical practice. Very few studies have looked at a validation of regional functional indices in an in-vivo context. The aim of the present study therefore was to validate a previously proposed 3D strain estimation-method based on elastic registration of subsequent volumes on a segmental level in an animal model. Volumetric images were acquired with a GE Vivid7 ultrasound system in five open-chest sheep instrumented with ultrasonic microcrystals. Radial (epsilon(RR)), longitudinal (epsilon(LL)) and circumferential strain (epsilon(CC)) were estimated during four stages: at rest, during esmolol and dobutamine infusion, and during acute ischemia. Moderate correlations for epsilon(LL) (r=0.63; p<0.01) and epsilon(CC) (r=0.60; p=0.01) were obtained, whereas no significant radial correlation was found. These findings are comparable to the performance of the current state-of-the-art commercial 3D speckle tracking methods