Estimating Left Ventricular Elastance from Aortic Flow Waveform, Ventricular Ejection Fraction, and Brachial Pressure: An In Silico Study

Noninvasive Left Ventricle Pressure-Volume Loop Determination Method With Cardiac Magnetic Resonance Imaging and Carotid Tonometry Using a Physics-Informed Approach

Left ventricular (LV) pressure-volume loop (PV-loop) is an important tool to quantify intrinsic left ventricular properties and ventricular-arterial coupling. A significant drawback of conventional PV-loop assessment is the need of invasive measurements which limits its widespread application. To tackle this issue, we developed a PV-loop determination method by using non-invasive measurements from arterial tonometry and cardiac magnetic resonance imaging. A physics-based optimization strategy was designed that adaptively identifies the optimal parameters to construct the PV-loop. We conducted comparative analysis in a convenience sample (N = 77) with heart failure (HF) (N = 23) patients and a control (N = 54) group to evaluate the sensitivity our PV-loop estimation algorithm. Significant and coherent differences between cohorts for the parameters derived using the PV-loop were observed. Our method captures the significant elevation of LV end diastolic pressure (p<0.001), and the decrease of the ventricular efficiency (p<0.0001) of the HF patients compared to the Control group. This method further captures the mechanistic changes of the LV by highlighting the significant differences of the smaller stroke work (p<0.0001), mean external power (p<0.05), and contractility (p<0.001) between these groups. The LV performance metrics align well with the previous clinical PV-loop observations of HF patients and our results demonstrate that the proposed PV-loop reconstruction method can be used to assess the ventricular functional changes associated with HF. Using this noninvasive method may significantly impact and facilitate the diagnosis and therapeutic management of HF.

In vivo application and validation of a novel noninvasive method to estimate the end-systolic elastance

Accurate assessment of the left ventricular (LV) systolic function is indispensable in the clinic. However, estimation of a precise index of cardiac contractility, i.e., the end-systolic elastance (E_es), is invasive and cannot be established as clinical routine. The aim of this work was to present and validate a methodology that allows for the estimation of E_es from simple and readily available noninvasive measurements. The method is based on a validated model of the cardiovascular system and noninvasive data from arm-cuff pressure and routine echocardiography to render the model patient-specific. Briefly, the algorithm first uses the measured aortic flow as model input and optimizes the properties of the arterial system model to achieve correct prediction of the patient's peripheral pressure. In a second step, the personalized arterial system is coupled with the cardiac model (time-varying elastance model) and the LV systolic properties, including E_es, are tuned to predict accurately the aortic flow waveform. The algorithm was validated against invasive measurements of E_es (multiple pressure-volume loop analysis) taken from n = 10 patients with heart failure with preserved ejection fraction and n = 9 patients without heart failure. Invasive measurements of E_es (median = 2.4 mmHg/mL, range = [1.0, 5.0] mmHg/mL) agreed well with method predictions (normalized root mean square error = 9%, ρ = 0.89, bias = -0.1 mmHg/mL, and limits of agreement = [-0.9, 0.6] mmHg/mL). This is a promising first step toward the development of a valuable tool that can be used by clinicians to assess systolic performance of the LV in the critically ill.NEW & NOTEWORTHY In this study, we present a novel model-based method to estimate the left ventricular (LV) end-systolic elastance (E_es) according to measurement of the patient's arm-cuff pressure and a routine echocardiography examination. The proposed method was validated in vivo against invasive multiple-loop measurements of E_es, achieving high correlation and low bias. This tool could be most valuable for clinicians to assess the cardiovascular health of critically ill patients.

Biomechanics of diastolic dysfunction: a one-dimensional computational modeling approach

Diastolic dysfunction (DD) is a major component of heart failure with preserved ejection fraction (HFpEF). Accordingly, a profound understanding of the underlying biomechanical mechanisms involved in DD is needed to elucidate all aspects of HFpEF. In this study, we have developed a computational model of DD by leveraging the power of an advanced one-dimensional arterial network coupled to a four-chambered zero-dimensional cardiac model. The two main pathologies investigated were linked to the active relaxation of the myocardium and the passive stiffness of the left ventricular wall. These pathologies were quantified through two parameters for the biphasic delay of active relaxation, which simulate the early and late-phase relaxation delay, and one parameter for passive stiffness, which simulates the increased nonlinear stiffness of the ventricular wall. A parameter sensitivity analysis was conducted on each of the three parameters to investigate their effect in isolation. The three parameters were then concurrently adjusted to produce the three main phenotypes of DD. It was found that the impaired relaxation phenotype can be replicated by mainly manipulating the active relaxation, the pseudo-normal phenotype was replicated by manipulating both the active relaxation and passive stiffness, and, finally, the restricted phenotype was replicated by mainly changing the passive stiffness. This article presents a simple model producing a holistic and comprehensive replication of the main DD phenotypes and presents novel biomechanical insights on how key parameters defining the relaxation and stiffness properties of the myocardium affect the development and manifestation of DD.NEW & NOTEWORTHY This study uses a complete and validated computational model of the cardiovascular system to simulate the two main pathologies involved in diastolic dysfunction (DD), i.e., abnormal active relaxation and increased ventricular diastolic stiffness. The three phenotypes of DD were successfully replicated according to literature data. We elucidate the biomechanical effect of the relaxation pathologies involved and how these pathologies interact to create the various phenotypes of DD.

Understanding ventriculo-arterial coupling

In the late 19th century, Otto Frank published the first description of a ventricular pressure-volume diagram, thus laid the foundation for modern cardiovascular physiology. Since then, the analysis of the pressure-volume loops became a reference tool for the study of the ventricular pump properties. However, understanding cardiovascular performance requires both the evaluation of ventricular properties and the modulating effects of the arterial system, since the heart and the arterial tree are anatomically and functionally related structures. The study of the coupling between the cardiac function and the properties of the arterial system, or ventriculo-arterial (VA) coupling, provides then a comprehensive characterization of the performance of the cardiovascular system in both health and disease. The assessment of cardiovascular function is an essential element of the hemodynamic evaluation of critically ill patients. Both left and right ventricular dysfunction and arterial system disturbances are frequent in these patients. Since VA coupling ultimately defines de performance and efficiency of the cardiovascular system, the analysis of the interaction between the heart and the arterial system could offer a broader perspective of the hemodynamic disorders associated with common conditions, such as septic shock, heart failure, or right ventricular dysfunction. Moreover, this analysis could also provide valuable information about their pathophysiological mechanisms and may help to determine the best therapeutic strategy to correct them. In this review, we will describe the basic principles of the VA coupling assessment, its limitations, and the most common methods for its estimation at the bedside. Then, we will summarize the current knowledge of the application of VA coupling in critically ill patients and suggest some recommendations for further research.

On the importance of the nonuniform aortic stiffening in the hemodynamics of physiological aging

Mathematical models of the arterial tree constitute a valuable tool to investigate the hemodynamics of aging and pathology. Rendering such models as patient specific could allow for the assessment of central hemodynamic variables of clinical interest. However, this task is challenging, particularly with respect to the tuning of the local area compliance that varies significantly along the arterial tree. Accordingly, in this study, we demonstrate the importance of taking into account the differential effects of aging on the stiffness of central and peripheral arteries when simulating a person’s hemodynamic profile. More specifically, we propose a simple method for effectively adapting the properties of a generic one-dimensional model of the arterial tree based on the subject’s age and noninvasive measurements of aortic flow and brachial pressure. A key element for the success of the method is the implementation of different mechanisms of arterial stiffening for young and old individuals. The designed methodology was tested and validated against in vivo data from a population of n = 20 adults. Carotid-to-femoral pulse wave velocity was accurately predicted by the model (mean error = 0.14 m/s, SD = 0.77 m/s), with the greatest deviations being observed for older subjects. In regard to aortic pressure, model-derived systolic blood pressure and augmentation index were both in good agreement (mean difference of 2.3 mmHg and 4.25%, respectively) with the predictions of a widely used commercial device (Mobil-O-Graph). These preliminary results encourage us to further validate the method in larger samples and consider its potential as a noninvasive tool for hemodynamic monitoring.

NEW & NOTEWORTHY We propose a technique for adapting the parameters of a validated one-dimensional model of the arterial tree using noninvasive measurements of aortic flow and brachial pressure. Emphasis is given on the adjustment of the arterial tree distensibility, which incorporates the nonuniform effects of aging on central and peripheral vessel elasticity. Our method could find application in the derivation of important hemodynamic indices, paving the way for novel diagnostic tools.