Personalized Computer Simulation of Diastolic Function in Heart Failure

Abstract

The search for a parameter representing left ventricular relaxation from non-invasive and invasive diagnostic tools has been extensive, since heart failure (HF) with preserved ejection fraction (HF-pEF) is a global health problem. We explore here the feasibility using patient-specific cardiac computer modeling to capture diastolic parameters in patients suffering from different degrees of systolic HF. Fifty eight patients with idiopathic dilated cardiomyopathy have undergone thorough clinical evaluation, including cardiac magnetic resonance imaging (MRI), heart catheterization, echocardiography, and cardiac biomarker assessment. A previously-introduced framework for creating multi-scale patient-specific cardiac models has been applied on all these patients. Novel parameters, such as global stiffness factor and maximum left ventricular active stress, representing cardiac active and passive tissue properties have been computed for all patients. Invasive pressure measurements from heart catheterization were then used to evaluate ventricular relaxation using the time constant of isovolumic relaxation Tau (τ). Parameters from heart catheterization and the multi-scale model have been evaluated and compared to patient clinical presentation. The model parameter global stiffness factor, representing diastolic passive tissue properties, is correlated significantly across the patient population with τ. This study shows that multi-modal cardiac models can successfully capture diastolic (dys) function, a prerequisite for future clinical trials on HF-pEF.

Keywords: Computer-based 3D model; Diastolic function; Dilated cardiomyopathy; Myocardial stiffness; Personalized medicine; Tau.

Figure 1

Distribution of the examined variables Distribution of the calculated time constant Tau (τ; A), global stiffness factor (B), and LV maximum active stress (C) across the study population is plotted. The brown bars represent the frequency density and the red lines represent the distribution curve overlay for each variable. LV, left ventricle.

Figure 2

Map of the computed myocardium contraction strength in a patient-specific cardiac model The contraction strength is shown in the front view (A) and upper view (B) using color gradient with low intensity in blue and high intensity in red, non-contractile connective tissue is colored in gray.

Figure 3

Correlation between the global stiffness factor and τ Scatter plots represent the correlation between global stiffness factor and τ across the study population for all patients (A) and in the subgroup for patients with elevated NT-proBNP levels (NT-proBNP levels >125 ng/l) (B). The blue clouds represent the frequency density. The red line represents the best-fit line for the correlation, which is generated using R. NT-proBNP, N-terminal pro-brain natriuretic peptide.

Figure 4

Schematic representation of the classical Hill’s muscle model The model has two parallel components: an active (AE) and a passive (PE) component. The total stress produced by the tissue is indicated by T.