Parameter subset reduction for imaging-based digital twin generation of patients with left ventricular mechanical discoordination.

BACKGROUND: Integration of a patient's non-invasive imaging data in a digital twin (DT) of the heart can provide valuable insight into the myocardial disease substrates underlying left ventricular (LV) mechanical discoordination. However, when generating a DT, model parameters should be identifiable to obtain robust parameter estimations. In this study, we used the CircAdapt model of the human heart and circulation to find a subset of parameters which were identifiable from LV cavity volume and regional strain measurements of patients with different substrates of left bundle branch block (LBBB) and myocardial infarction (MI). To this end, we included seven patients with heart failure with reduced ejection fraction (HFrEF) and LBBB (study ID: 2018-0863, registration date: 2019-10-07), of which four were non-ischemic (LBBB-only) and three had previous MI (LBBB-MI), and six narrow QRS patients with MI (MI-only) (study ID: NL45241.041.13, registration date: 2013-11-12). Morris screening method (MSM) was applied first to find parameters which were important for LV volume, regional strain, and strain rate indices. Second, this parameter subset was iteratively reduced based on parameter identifiability and reproducibility. Parameter identifiability was based on the diaphony calculated from quasi-Monte Carlo simulations and reproducibility was based on the intraclass correlation coefficient ( ICC ) obtained from repeated parameter estimation using dynamic multi-swarm particle swarm optimization. Goodness-of-fit was defined as the mean squared error ( χ 2 ) of LV myocardial strain, strain rate, and cavity volume. RESULTS: A subset of 270 parameters remained after MSM which produced high-quality DTs of all patients ( χ 2 < 1.6), but minimum parameter reproducibility was poor ( ICC min = 0.01). Iterative reduction yielded a reproducible ( ICC min = 0.83) subset of 75 parameters, including cardiac output, global LV activation duration, regional mechanical activation delay, and regional LV myocardial constitutive properties. This reduced subset produced patient-resembling DTs ( χ 2 < 2.2), while septal-to-lateral wall workload imbalance was higher for the LBBB-only DTs than for the MI-only DTs (p < 0.05). CONCLUSIONS: By applying sensitivity and identifiability analysis, we successfully determined a parameter subset of the CircAdapt model which can be used to generate imaging-based DTs of patients with LV mechanical discoordination. Parameters were reproducibly estimated using particle swarm optimization, and derived LV myocardial work distribution was representative for the patient's underlying disease substrate. This DT technology enables patient-specific substrate characterization and can potentially be used to support clinical decision making.

Mitral valve prolapse: arrhythmic risk during pregnancy and postpartum.

BACKGROUND AND AIMS: Arrhythmic mitral valve prolapse (AMVP) is linked to life-threatening ventricular arrhythmias (VAs), and young women are considered at high risk. Cases of AMVP in women with malignant VA during pregnancy have emerged, but the arrhythmic risk during pregnancy is unknown. The authors aimed to describe features of women with high-risk AMVP who developed malignant VA during the perinatal period and to assess if pregnancy and the postpartum period were associated with a higher risk of malignant VA. METHODS: This retrospective international multi-centre case series included high-risk women with AMVP who experienced malignant VA and at least one pregnancy. Malignant VA included ventricular fibrillation, sustained ventricular tachycardia, or appropriate shock from an implantable cardioverter defibrillator. The authors compared the incidence of malignant VA in non-pregnant periods and perinatal period; the latter defined as occurring during pregnancy and within 6 months after delivery. RESULTS: The authors included 18 women with AMVP from 11 centres. During 7.5 (interquartile range 5.8-16.6) years of follow-up, 37 malignant VAs occurred, of which 18 were pregnancy related occurring in 13 (72%) unique patients. Pregnancy and 6 months after delivery showed increased incidence rate of malignant VA compared to the non-pregnancy period (univariate incidence rate ratio 2.66, 95% confidence interval 1.23-5.76). CONCLUSIONS: The perinatal period could impose increased risk of malignant VA in women with high-risk AMVP. The data may provide general guidance for pre-conception counselling and for nuanced shared decision-making between patients and clinicians.

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.

Body surface potential mapping detects early disease onset in plakophilin-2-pathogenic variant carriers.

AIMS: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a progressive inherited cardiac disease. Early detection of disease and risk stratification remain challenging due to heterogeneous phenotypic expression. The standard configuration of the 12 lead electrocardiogram (ECG) might be insensitive to identify subtle ECG abnormalities. We hypothesized that body surface potential mapping (BSPM) may be more sensitive to detect subtle ECG abnormalities. METHODS AND RESULTS: We obtained 67 electrode BSPM in plakophilin-2 (PKP2)-pathogenic variant carriers and control subjects. Subject-specific computed tomography/magnetic resonance imaging based models of the heart/torso and electrode positions were created. Cardiac activation and recovery patterns were visualized with QRS- and STT-isopotential map series on subject-specific geometries to relate QRS-/STT-patterns to cardiac anatomy and electrode positions. To detect early signs of functional/structural heart disease, we also obtained right ventricular (RV) echocardiographic deformation imaging. Body surface potential mapping was obtained in 25 controls and 42 PKP2-pathogenic variant carriers. We identified five distinct abnormal QRS-patterns and four distinct abnormal STT-patterns in the isopotential map series of 31/42 variant carriers. Of these 31 variant carriers, 17 showed no depolarization or repolarization abnormalities in the 12 lead ECG. Of the 19 pre-clinical variant carriers, 12 had normal RV-deformation patterns, while 7/12 showed abnormal QRS- and/or STT-patterns. CONCLUSION: Assessing depolarization and repolarization by BSPM may help in the quest for early detection of disease in variant carriers since abnormal QRS- and/or STT-patterns were found in variant carriers with a normal 12 lead ECG. Because electrical abnormalities were observed in subjects with normal RV-deformation patterns, we hypothesize that electrical abnormalities develop prior to functional/structural abnormalities in ARVC.

The added value of abnormal regional myocardial function for risk prediction in arrhythmogenic right ventricular cardiomyopathy.

AIMS: A risk calculator for individualized prediction of first-time sustained ventricular arrhythmia (VA) in arrhythmogenic right ventricular cardiomyopathy (ARVC) patients has recently been developed and validated (www.ARVCrisk.com). This study aimed to investigate whether regional functional abnormalities, measured by echocardiographic deformation imaging, can provide additional prognostic value. METHODS AND RESULTS: From two referral centres, 150 consecutive patients with a definite ARVC diagnosis, no prior sustained VA, and an echocardiogram suitable for deformation analysis were included (aged 41 ± 17 years, 50% female). During a median follow-up of 6.3 (interquartile range 3.1-9.8) years, 37 (25%) experienced a first-time sustained VA. All tested left and right ventricular (LV and RV) deformation parameters were univariate predictors for first-time VA. While LV function did not add predictive value in multivariate analysis, two RV deformation parameters did; RV free wall longitudinal strain and regional RV deformation patterns remained independent predictors after adjusting for the calculator-predicted risk [hazard ratio 1.07 (95% CI 1.02-1.11); P = 0.004 and 4.45 (95% CI 1.07-18.57); P = 0.040, respectively] and improved its discriminative value (from C-statistic 0.78 to 0.82 in both; Akaike information criterion change > 2). Importantly, all patients who experienced VA within 5 years from the echocardiographic assessment had abnormal regional RV deformation patterns at baseline. CONCLUSIONS: This study showed that regional functional abnormalities measured by echocardiographic deformation imaging can further refine personalized arrhythmic risk prediction when added to the ARVC risk calculator. The excellent negative predictive value of normal RV deformation could support clinicians considering the timing of implantable cardioverter defibrillator implantation in patients with intermediate arrhythmic risk.

State-of-the-Art Multimodality Imaging in Sudden Cardiac Arrest with Focus on Idiopathic Ventricular Fibrillation: A Review.

Idiopathic ventricular fibrillation is a rare cause of sudden cardiac arrest and a diagnosis by exclusion. Unraveling the mechanism of ventricular fibrillation is important for targeted management, and potentially for initiating family screening. Sudden cardiac arrest survivors undergo extensive clinical testing, with a growing role for multimodality imaging, before diagnosing "idiopathic" ventricular fibrillation. Multimodality imaging, considered as using multiple imaging modalities as diagnostics, is important for revealing structural myocardial abnormalities in patients with cardiac arrest. This review focuses on combining imaging modalities (echocardiography, cardiac magnetic resonance and computed tomography) and the electrocardiographic characterization of sudden cardiac arrest survivors and discusses the surplus value of multimodality imaging in the diagnostic routing of these patients. We focus on novel insights obtained through electrostructural and/or electromechanical imaging in apparently idiopathic ventricular fibrillation patients, with special attention to non-invasive electrocardiographic imaging.

Prevalence of Mitral Annulus Disjunction and Mitral Valve Prolapse in Patients With Idiopathic Ventricular Fibrillation.

Background Idiopathic ventricular fibrillation (IVF) is diagnosed in patients with ventricular fibrillation of which the origin is not identified after extensive evaluations. Recent studies suggest an association between mitral annulus disjunction (MAD), mitral valve prolapse (MVP), and ventricular arrhythmias. The prevalence of MAD and MVP in patients with IVF in this regard is not well established. We aimed to explore the prevalence of MAD and MVP in a consecutive cohort of patients with IVF compared with matched controls. Methods and Results In this retrospective, multicenter cohort study, cardiac magnetic resonance images from patients with IVF (ie, negative for ischemia, cardiomyopathy, and channelopathies) and age- and sex-matched control subjects were analyzed for the presence of MAD (≥2 mm) and MVP (>2 mm). In total, 72 patients (mean age 39±14 years, 42% women) and 72 control subjects (mean age 41±11 years, 42% women) were included. MAD in the inferolateral wall was more prevalent in patients with IVF versus healthy controls (7 [11%] versus 1 [1%], P=0.024). MVP was only seen in patients with IVF and not in controls (5 [7%] versus 0 [0%], P=0.016). MAD was observed in both patients with (n=4) and without (n=3) MVP. Conclusions Inferolateral MAD and MVP were significantly more prevalent in patients with IVF compared with healthy controls. The authors advocate that evaluation of the mitral valve region deserves extra attention in the extensive screening of patients with unexplained cardiac arrest. These findings support further exploration of the pathophysiological mechanisms underlying a subset of IVF that associates with MAD and MVP.

A Lumped Two-Compartment Model for Simulation of Ventricular Pump and Tissue Mechanics in Ischemic Heart Disease.

Introduction: Computational modeling of cardiac mechanics and hemodynamics in ischemic heart disease (IHD) is important for a better understanding of the complex relations between ischemia-induced heterogeneity of myocardial tissue properties, regional tissue mechanics, and hemodynamic pump function. We validated and applied a lumped two-compartment modeling approach for IHD integrated into the CircAdapt model of the human heart and circulation. Methods: Ischemic contractile dysfunction was simulated by subdividing a left ventricular (LV) wall segment into a hypothetical contractile and noncontractile compartment, and dysfunction severity was determined by the noncontractile volume fraction ( N C V F ). Myocardial stiffness was determined by the zero-passive stress length ( L s 0 , p a s ) and nonlinearity ( k E C M ) of the passive stress-sarcomere length relation of the noncontractile compartment. Simulated end-systolic pressure volume relations (ESPVRs) for 20% acute ischemia were qualitatively compared between a two- and one-compartment simulation, and parameters of the two-compartment model were tuned to previously published canine data of regional myocardial deformation during acute and prolonged ischemia and reperfusion. In six patients with myocardial infarction (MI), the N C V F was automatically estimated using the echocardiographic LV strain and volume measurements obtained acutely and 6 months after MI. Estimated segmental N C V F values at the baseline and 6-month follow-up were compared with percentage late gadolinium enhancement (LGE) at 6-month follow-up. Results: Simulation of 20% of N C V F shifted the ESPVR rightward while moderately reducing the slope, while a one-compartment simulation caused a leftward shift with severe reduction in the slope. Through tuning of the N C V F , L s 0 , p a s , and k E C M , it was found that manipulation of the N C V F alone reproduced the deformation during acute ischemia and reperfusion, while additional manipulations of L s 0 , p a s and k E C M were required to reproduce deformation during prolonged ischemia and reperfusion. Out of all segments with LGE>25% at the follow-up, the majority (68%) had higher estimated N C V F at the baseline than at the follow-up. Furthermore, the baseline N C V F correlated better with percentage LGE than N C V F did at the follow-up. Conclusion: We successfully used a two-compartment model for simulation of the ventricular pump and tissue mechanics in IHD. Patient-specific optimizations using regional myocardial deformation estimated the N C V F in a small cohort of MI patients in the acute and chronic phase after MI, while estimated N C V F values closely approximated the extent of the myocardial scar at the follow-up. In future studies, this approach can facilitate deformation imaging-based estimation of myocardial tissue properties in patients with cardiovascular diseases.

Echocardiographic Deformation Imaging for Early Detection of Genetic Cardiomyopathies: JACC Review Topic of the Week.

Clinical screening of the relatives of patients with genetic cardiomyopathies is challenging, as they often lack detectable cardiac abnormalities at presentation. Life-threatening adverse events can already occur in these early stages of disease, so sensitive tools to reveal the earliest signs of disease are needed. The utility of echocardiographic deformation imaging for early detection has been explored for this population in multiple studies but has not been broadly implemented in clinical practice. The authors discuss contemporary evidence on the utility of deformation imaging in relatives of patients with genetic cardiomyopathies. The available body of data shows that deformation imaging reveals early disease-specific abnormalities in dilated cardiomyopathy, hypertrophic cardiomyopathy, and arrhythmogenic cardiomyopathy. Deformation imaging seems promising to enhance the screening and follow-up protocols in relatives, and the authors propose measures to accelerate its implementation in clinical care.

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.

Right Ventricular Functional Abnormalities in Arrhythmogenic Cardiomyopathy: Association With Life-Threatening Ventricular Arrhythmias.

OBJECTIVES: This study aimed to perform an external validation of the value of right ventricular (RV) deformation patterns and RV mechanical dispersion in patients with arrhythmogenic cardiomyopathy (AC). Secondly, this study assessed the association of these parameters with life-threatening ventricular arrhythmia (VA). BACKGROUND: Subtle RV dysfunction assessed by echocardiographic deformation imaging is valuable in AC diagnosis and risk prediction. Two different methods have emerged, the RV deformation pattern recognition and RV mechanical dispersion, but these have neither been externally validated nor compared. METHODS: We analyzed AC probands and mutation-positive family members, matched from 2 large European referral centers. We performed speckle tracking echocardiography, whereby we classified the subtricuspid deformation patterns from normal to abnormal and assessed RV mechanical dispersion from 6 segments. We defined VA as sustained ventricular tachycardia, appropriate implantable cardioverter-defibrillator therapy, or aborted cardiac arrest. RESULTS: We included 160 subjects, 80 from each center (43% proband, 55% women, age 41 ± 17 years). VA had occurred in 47 (29%) subjects. In both cohorts, patients with a history of VA showed abnormal deformation patterns (96% and 100%) and had greater RV mechanical dispersion (53 ± 30 ms vs. 30 ± 21 ms; p < 0.001 for the total cohort). Both parameters were independently associated to VA (adjusted odds ratio: 2.71 [95% confidence interval: 1.47 to 5.00] per class step-up, and 1.26 [95% confidence interval: 1.07 to 1.49]/10 ms, respectively). The association with VA significantly improved when adding RV mechanical dispersion to pattern recognition (net reclassification improvement 0.42; p = 0.02 and integrated diagnostic improvement 0.06; p = 0.01). CONCLUSIONS: We externally validated 2 RV dysfunction parameters in AC. Adding RV mechanical dispersion to RV deformation patterns significantly improved the association with life-threatening VA, indicating incremental value.