Virtual pacing of a patient's digital twin to predict left ventricular reverse remodelling after cardiac resynchronization therapy

AIMS

Identifying heart failure (HF) patients who will benefit from cardiac resynchronization therapy (CRT) remains challenging. We evaluated whether virtual pacing in a digital twin (DT) of the patient's heart could be used to predict the degree of left ventricular (LV) reverse remodelling post-CRT.

METHODS AND RESULTS

Forty-five HF patients with wide QRS complex (≥130 ms) and reduced LV ejection fraction (≤35%) receiving CRT were retrospectively enrolled. Echocardiography was performed before (baseline) and 6 months after CRT implantation to obtain LV volumes and 18-segment longitudinal strain. A previously developed algorithm was used to generate 45 DTs by personalizing the CircAdapt model to each patient's baseline measurements. From each DT, baseline septal-to-lateral myocardial work difference (MWLW-S,DT) and maximum rate of LV systolic pressure rise (dP/dtmax,DT) were derived. Biventricular pacing was then simulated using patient-specific atrioventricular delay and lead location. Virtual pacing-induced changes ΔMWLW-S,DT and ΔdP/dtmax,DT were correlated with real-world LV end-systolic volume change at 6-month follow-up (ΔLVESV). The DT's baseline MWLW-S,DT and virtual pacing-induced ΔMWLW-S,DT were both significantly associated with the real patient's reverse remodelling ΔLVESV (r = -0.60, P < 0.001 and r = 0.62, P < 0.001, respectively), while correlation between ΔdP/dtmax,DT and ΔLVESV was considerably weaker (r = -0.34, P = 0.02).

CONCLUSION

Our results suggest that the reduction of septal-to-lateral work imbalance by virtual pacing in the DT can predict real-world post-CRT LV reverse remodelling. This DT approach could prove to be an additional tool in selecting HF patients for CRT and has the potential to provide valuable insights in optimization of CRT delivery.

Monitoring of Myocardial Involvement in Early Arrhythmogenic Right Ventricular Cardiomyopathy Across the Age Spectrum

BACKGROUND

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is characterized by fibrofatty replacement of primarily the right ventricular myocardium, a substrate for life-threatening ventricular arrhythmias (VAs). Repeated cardiac imaging of at-risk relatives is important for early disease detection. However, it is not known whether screening should be age-tailored.

OBJECTIVES

The goal of this study was to assess the need for age-tailoring of follow-up protocols in early ARVC by evaluating myocardial disease progression in different age groups.

METHODS

We divided patients with early-stage ARVC and genotype-positive relatives without overt structural disease and VA at first evaluation into 3 groups: age <30 years, 30 to 50 years, and ≥50 years. Longitudinal biventricular deformation characteristics were used to monitor disease progression. To link deformation abnormalities to underlying myocardial disease substrates, Digital Twins were created using an imaging-based computational modeling framework.

RESULTS

We included 313 echocardiographic assessments from 82 subjects (57% female, age 39 ± 17 years, 10% probands) during 6.7 ± 3.3 years of follow-up. Left ventricular global longitudinal strain slightly deteriorated similarly in all age groups (0.1%-point per year [95% CI: 0.05-0.15]). Disease progression in all age groups was more pronounced in the right ventricular lateral wall, expressed by worsening in longitudinal strain (0.6%-point per year [95% CI: 0.46-0.70]) and local differences in myocardial contractility, compliance, and activation delay in the Digital Twin. Six patients experienced VA during follow-up.

CONCLUSIONS

Disease progression was similar in all age groups, and sustained VA also occurred in patients aged >50 years without overt ARVC phenotype at first evaluation. Unlike recommended by current guidelines, our study suggests that follow-up of ARVC patients and relatives should not stop at older age.

Left atrial remodeling in mitral regurgitation: A combined experimental-computational study

Aims

Progressive changes to left atrial (LA) structure and function following mitral regurgitation (MR) remain incompletely understood. This study aimed to demonstrate potential underlying mechanisms using experimental canine models and computer simulations.

Methods

A canine model of MR was created by cauterization of mitral chordae followed by radiofrequency ablation-induced left bundle-branch block (LBBB) after 4 weeks (MR-LBBB group). Animals with LBBB alone served as control. Echocardiography was performed at baseline, acutely after MR induction, and at 4 and 20 weeks, and correlated with histology and computer simulations.

Results

Acute MR augmented LA reservoir and contractile strain (40±4 to 53±6% and -11±5 to -22±9% respectively, p<0.05). LA fractional area change increased significantly (47±4 to 56±4%, p<0.05) while LA end-systolic area remained unchanged (7.2±1.1 versus 7.9±1.1 cm2 respectively, p = 0.08). LA strain ‘pseudonormalized’ after 4 weeks and decompensated at 20 weeks with both strains decreasing to 25±6% and -3±2% respectively (p<0.05) together with a progressive increase in LA end-systolic area (7.2±1.1 to 14.0±6.3 cm2, p<0.05). In the LBBB-group, LA remodeling was less pronounced. Histology showed a trend towards increased interstitial fibrosis in the LA of the MR-LBBB group. Computer simulations indicated that the progressive changes in LA structure and function are a combination of progressive eccentric remodeling and fibrosis.

Conclusion

MR augmented LA strain acutely to supranormal values without significant LA dilation. However, over time, LA strain gradually decreases (pseudornormal and decompensated) with LA dilation. Histology and computer simulations indicated a correlation to a varying degree of LA eccentric remodeling and fibrosis.

Uncertainty Quantification of Regional Cardiac Tissue Properties in Arrhythmogenic Cardiomyopathy Using Adaptive Multiple Importance Sampling

Introduction: Computational models of the cardiovascular system are widely used to simulate cardiac (dys)function. Personalization of such models for patient-specific simulation of cardiac function remains challenging. Measurement uncertainty affects accuracy of parameter estimations. In this study, we present a methodology for patient-specific estimation and uncertainty quantification of parameters in the closed-loop CircAdapt model of the human heart and circulation using echocardiographic deformation imaging. Based on patient-specific estimated parameters we aim to reveal the mechanical substrate underlying deformation abnormalities in patients with arrhythmogenic cardiomyopathy (AC). Methods: We used adaptive multiple importance sampling to estimate the posterior distribution of regional myocardial tissue properties. This methodology is implemented in the CircAdapt cardiovascular modeling platform and applied to estimate active and passive tissue properties underlying regional deformation patterns, left ventricular volumes, and right ventricular diameter. First, we tested the accuracy of this method and its inter- and intraobserver variability using nine datasets obtained in AC patients. Second, we tested the trueness of the estimation using nine in silico generated virtual patient datasets representative for various stages of AC. Finally, we applied this method to two longitudinal series of echocardiograms of two pathogenic mutation carriers without established myocardial disease at baseline. Results: Tissue characteristics of virtual patients were accurately estimated with a highest density interval containing the true parameter value of 9% (95% CI [0-79]). Variances of estimated posterior distributions in patient data and virtual data were comparable, supporting the reliability of the patient estimations. Estimations were highly reproducible with an overlap in posterior distributions of 89.9% (95% CI [60.1-95.9]). Clinically measured deformation, ejection fraction, and end-diastolic volume were accurately simulated. In presence of worsening of deformation over time, estimated tissue properties also revealed functional deterioration. Conclusion: This method facilitates patient-specific simulation-based estimation of regional ventricular tissue properties from non-invasive imaging data, taking into account both measurement and model uncertainties. Two proof-of-principle case studies suggested that this cardiac digital twin technology enables quantitative monitoring of AC disease progression in early stages of disease.

Electromechanical substrate characterization in arrhythmogenic cardiomyopathy using imaging-based patient-specific computer simulations

AIMS

Arrhythmogenic cardiomyopathy (AC) is an inherited cardiac disease, characterized by life-threatening ventricular arrhythmias and progressive cardiac dysfunction. The aim of this study is to use computer simulations to non-invasively estimate the individual patient's myocardial tissue substrates underlying regional right ventricular (RV) deformation abnormalities in a cohort of AC mutation carriers.

METHODS AND RESULTS

In 68 AC mutation carriers and 20 control subjects, regional longitudinal deformation patterns of the RV free wall (RVfw), interventricular septum (IVS), and left ventricular free wall (LVfw) were obtained using speckle-tracking echocardiography. We developed and used a patient-specific parameter estimation protocol based on the multi-scale CircAdapt cardiovascular system model to create virtual AC subjects. Using the individual's deformation data as model input, this protocol automatically estimated regional RVfw and global IVS and LVfw tissue properties. The computational model was able to reproduce clinically measured regional deformation patterns for all subjects, with highly reproducible parameter estimations. Simulations revealed that regional RVfw heterogeneity of both contractile function and compliance were increased in subjects with clinically advanced disease compared to mutation carriers without clinically established disease (17 ± 13% vs. 8 ± 4%, P = 0.01 and 18 ± 11% vs. 10 ± 7%, P < 0.01, respectively). No significant difference in activation delay was found.

CONCLUSION

Regional RV deformation abnormalities in AC mutation carriers were related to reduced regional contractile function and tissue compliance. In clinically advanced disease stages, a characteristic apex-to-base heterogeneity of tissue abnormalities was present in the majority of the subjects, with most pronounced disease in the basal region of the RVfw.

Increased myocardial stiffness more than impaired relaxation function limits cardiac performance during exercise in heart failure with preserved ejection fraction: a virtual patient study

AIMS

The relative impact of left ventricular (LV) diastolic dysfunction (LVDD) and impaired left atrial (LA) function on cardiovascular haemodynamics in heart failure with preserved ejection fraction (HFpEF) is largely unknown. We performed virtual patient simulations to elucidate the relative effects of these factors on haemodynamics at rest and during exercise.

METHODS AND RESULTS

The CircAdapt cardiovascular system model was used to simulate cardiac haemodynamics in wide ranges of impaired LV relaxation function, increased LV passive stiffness, and impaired LA function. Simulations showed that LV ejection fraction (LVEF) was preserved (>50%), despite these changes in LV and LA function. Impairment of LV relaxation function decreased E/A ratio and mildly increased LV filling pressure at rest. Increased LV passive stiffness resulted in increased E/A ratio, LA dilation and markedly elevated LV filling pressure. Impairment of LA function increased E/A ratio and LV filling pressure, explaining inconsistent grading of LVDD using echocardiographic indices. Exercise simulations showed that increased LV passive stiffness exerts a stronger exercise-limiting effect than impaired LV relaxation function does, especially with impaired LA function.

CONCLUSION

The CircAdapt model enabled realistic simulation of virtual HFpEF patients, covering a wide spectrum of LVDD and related limitations of cardiac exercise performance, all with preserved resting LVEF. Simulations suggest that increased LV passive stiffness, more than impaired relaxation function, reduces exercise tolerance, especially when LA function is impaired. In future studies, the CircAdapt model can serve as a valuable platform for patient-specific simulations to identify the disease substrate(s) underlying the individual HFpEF patient's cardiovascular phenotype.

Parameter subset reduction for patient-specific modelling of arrhythmogenic cardiomyopathy-related mutation carriers in the CircAdapt model

Arrhythmogenic cardiomyopathy (AC) is an inherited cardiac disease, clinically characterized by life-threatening ventricular arrhythmias and progressive cardiac dysfunction. Patient-specific computational models could help understand the disease progression and may help in clinical decision-making. We propose an inverse modelling approach using the CircAdapt model to estimate patient-specific regional abnormalities in tissue properties in AC subjects. However, the number of parameters (n = 110) and their complex interactions make personalized parameter estimation challenging. The goal of this study is to develop a framework for parameter reduction and estimation combining Morris screening, quasi-Monte Carlo (qMC) simulations and particle swarm optimization (PSO). This framework identifies the best subset of tissue properties based on clinical measurements allowing patient-specific identification of right ventricular tissue abnormalities. We applied this framework on 15 AC genotype-positive subjects with varying degrees of myocardial disease. Cohort studies have shown that atypical regional right ventricular (RV) deformation patterns reveal an early-stage AC disease. The CircAdapt model of cardiovascular mechanics and haemodynamics has already demonstrated its ability to capture typical deformation patterns of AC subjects. We, therefore, use clinically measured cardiac deformation patterns to estimate model parameters describing myocardial disease substrates underlying these AC-related RV deformation abnormalities. Morris screening reduced the subset to 48 parameters. qMC and PSO further reduced the subset to a final selection of 16 parameters, including regional tissue contractility, passive stiffness, activation delay and wall reference area. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.