Yuxuan Hu

A computational approach to understanding the cardiac electromechanical activation sequence in the normal and failing heart, with translation to the clinical practice of CRT

Cardiac resynchronization therapy (CRT) is an established clinical treatment modality that aims to recoordinate contraction of the heart in dyssynchrous heart failure (DHF) patients. Although CRT reduces morbidity and mortality, a significant percentage of CRT patients fail to respond to the therapy, reflecting an insufficient understanding of the electromechanical activity of the DHF heart. Computational models of ventricular electromechanics are now poised to fill this knowledge gap and provide a comprehensive characterization of the spatiotemporal electromechanical interactions in the normal and DHF heart. The objective of this paper is to demonstrate the powerful utility of computational models of ventricular electromechanics in characterizing the relationship between the electrical and mechanical activation in the DHF heart, and how this understanding can be utilized to devise better CRT strategies. The computational research presented here exploits knowledge regarding the three dimensional distribution of the electromechanical delay, defined as the time interval between myocyte depolarization and onset of myofiber shortening, in determining the optimal location of the LV pacing electrode for CRT. The simulation results shown here also suggest utilizing myocardial efficiency and regional energy consumption as a guide to optimize CRT.

Computational cardiology: how computer simulations could be used to develop new therapies and advance existing ones.

This article reviews the latest developments in computational cardiology. It focuses on the contribution of cardiac modelling to the development of new therapies as well as the advancement of existing ones for cardiac arrhythmias and pump dysfunction. Reviewed are cardiac modelling efforts aimed at advancing and optimizing existent therapies for cardiac disease (defibrillation, ablation of ventricular tachycardia, and cardiac resynchronization therapy) and at suggesting novel treatments, including novel molecular targets, as well as efforts to use cardiac models in stratification of patients likely to benefit from a given therapy, and the use of models in diagnostic procedures.

Unstable QT Interval Dynamics Precedes Ventricular Tachycardia Onset in Patients With Acute Myocardial Infarction A Novel Approach to Detect Instability in QT Interval Dynamics From Clinical ECG

Background— Instability in ventricular repolarization in the presence of premature activations (PA) plays an important role in arrhythmogenesis. However, such instability cannot be detected clinically. This study developed a methodology for detecting QT interval (QTI) dynamics instability from the ECG and explored the contribution of PA and QTI instability to ventricular tachycardia (VT) onset. Methods and Results— To examine the contribution of PAs and QTI instability to VT onset, ECGs of 24 patients with acute myocardial infarction, 12 of whom had sustained VT (VT) and 12 nonsustained VT (NSVT), were used. From each patient ECG, 2 10-minute-long ECG recordings were extracted, 1 right before VT onset (onset epoch) and 1 at least 1 hour before it (control epoch). To ascertain how PA affects QTI dynamics stability, pseudo-ECGs were calculated from an MRI-based human ventricular model. Clinical and pseudo-ECGs were subdivided into 1-minute recordings (minECGs). QTI dynamics stability of each minECG was assessed with a novel approach. Frequency of PAs (fPA) and the number of minECGs with unstable QTI dynamics (Nus) were determined for each patient. In the VT group, fPA and Nus of the onset epoch were larger than in control. Positive regression relationships between fPA and Nus were identified in both groups. The simulations showed that both fPA and the PA degree of prematurity contribute to QTI dynamics instability. Conclusions— Increased PA frequency and QTI dynamics instability precede VT onset in patients with acute myocardial infarction, as determined by novel methodology for detecting instability in QTI dynamics from clinical ECGs.Background— Instability in ventricular repolarization in the presence of premature activations (PA) plays an important role in arrhythmogenesis. However, such instability cannot be detected clinically. This study developed a methodology for detecting QT interval (QTI) dynamics instability from the ECG and explored the contribution of PA and QTI instability to ventricular tachycardia (VT) onset. Methods and Results— To examine the contribution of PAs and QTI instability to VT onset, ECGs of 24 patients with acute myocardial infarction, 12 of whom had sustained VT (VT) and 12 nonsustained VT (NSVT), were used. From each patient ECG, 2 10-minute-long ECG recordings were extracted, 1 right before VT onset (onset epoch) and 1 at least 1 hour before it (control epoch). To ascertain how PA affects QTI dynamics stability, pseudo-ECGs were calculated from an MRI-based human ventricular model. Clinical and pseudo-ECGs were subdivided into 1-minute recordings (minECGs). QTI dynamics stability of each minECG was assessed with a novel approach. Frequency of PAs (fPA) and the number of minECGs with unstable QTI dynamics (Nus) were determined for each patient. In the VT group, fPA and Nus of the onset epoch were larger than in control. Positive regression relationships between fPA and Nus were identified in both groups. The simulations showed that both fPA and the PA degree of prematurity contribute to QTI dynamics instability. Conclusions— Increased PA frequency and QTI dynamics instability precede VT onset in patients with acute myocardial infarction, as determined by novel methodology for detecting instability in QTI dynamics from clinical ECGs.

Effects of Mechano-Electric Feedback on Scroll Wave Stability in Human Ventricular Fibrillation

Recruitment of stretch-activated channels, one of the mechanisms of mechano-electric feedback, has been shown to influence the stability of scroll waves, the waves that underlie reentrant arrhythmias. However, a comprehensive study to examine the effects of recruitment of stretch-activated channels with different reversal potentials and conductances on scroll wave stability has not been undertaken; the mechanisms by which stretch-activated channel opening alters scroll wave stability are also not well understood. The goals of this study were to test the hypothesis that recruitment of stretch-activated channels affects scroll wave stability differently depending on stretch-activated channel reversal potential and channel conductance, and to uncover the relevant mechanisms underlying the observed behaviors. We developed a strongly-coupled model of human ventricular electromechanics that incorporated human ventricular geometry and fiber and sheet orientation reconstructed from MR and diffusion tensor MR images. Since a wide variety of reversal potentials and channel conductances have been reported for stretch-activated channels, two reversal potentials, −60 mV and −10 mV, and a range of channel conductances (0 to 0.07 mS/µF) were implemented. Opening of stretch-activated channels with a reversal potential of −60 mV diminished scroll wave breakup for all values of conductances by flattening heterogeneously the action potential duration restitution curve. Opening of stretch-activated channels with a reversal potential of −10 mV inhibited partially scroll wave breakup at low conductance values (from 0.02 to 0.04 mS/µF) by flattening heterogeneously the conduction velocity restitution relation. For large conductance values (>0.05 mS/µF), recruitment of stretch-activated channels with a reversal potential of −10 mV did not reduce the likelihood of scroll wave breakup because Na channel inactivation in regions of large stretch led to conduction block, which counteracted the increased scroll wave stability due to an overall flatter conduction velocity restitution.

Unstable QT Interval Dynamics Precedes VT Onset in Patients with Acute Myocardial Infarction: A Novel Approach to Detect Instability in QT Interval Dynamics from Clinical ECG

Background— Instability in ventricular repolarization in the presence of premature activations (PA) plays an important role in arrhythmogenesis. However, such instability cannot be detected clinically. This study developed a methodology for detecting QT interval (QTI) dynamics instability from the ECG and explored the contribution of PA and QTI instability to ventricular tachycardia (VT) onset. Methods and Results— To examine the contribution of PAs and QTI instability to VT onset, ECGs of 24 patients with acute myocardial infarction, 12 of whom had sustained VT (VT) and 12 nonsustained VT (NSVT), were used. From each patient ECG, 2 10-minute-long ECG recordings were extracted, 1 right before VT onset (onset epoch) and 1 at least 1 hour before it (control epoch). To ascertain how PA affects QTI dynamics stability, pseudo-ECGs were calculated from an MRI-based human ventricular model. Clinical and pseudo-ECGs were subdivided into 1-minute recordings (minECGs). QTI dynamics stability of each minECG was assessed with a novel approach. Frequency of PAs (fPA) and the number of minECGs with unstable QTI dynamics (Nus) were determined for each patient. In the VT group, fPA and Nus of the onset epoch were larger than in control. Positive regression relationships between fPA and Nus were identified in both groups. The simulations showed that both fPA and the PA degree of prematurity contribute to QTI dynamics instability. Conclusions— Increased PA frequency and QTI dynamics instability precede VT onset in patients with acute myocardial infarction, as determined by novel methodology for detecting instability in QTI dynamics from clinical ECGs.Background— Instability in ventricular repolarization in the presence of premature activations (PA) plays an important role in arrhythmogenesis. However, such instability cannot be detected clinically. This study developed a methodology for detecting QT interval (QTI) dynamics instability from the ECG and explored the contribution of PA and QTI instability to ventricular tachycardia (VT) onset. Methods and Results— To examine the contribution of PAs and QTI instability to VT onset, ECGs of 24 patients with acute myocardial infarction, 12 of whom had sustained VT (VT) and 12 nonsustained VT (NSVT), were used. From each patient ECG, 2 10-minute-long ECG recordings were extracted, 1 right before VT onset (onset epoch) and 1 at least 1 hour before it (control epoch). To ascertain how PA affects QTI dynamics stability, pseudo-ECGs were calculated from an MRI-based human ventricular model. Clinical and pseudo-ECGs were subdivided into 1-minute recordings (minECGs). QTI dynamics stability of each minECG was assessed with a novel approach. Frequency of PAs (fPA) and the number of minECGs with unstable QTI dynamics (Nus) were determined for each patient. In the VT group, fPA and Nus of the onset epoch were larger than in control. Positive regression relationships between fPA and Nus were identified in both groups. The simulations showed that both fPA and the PA degree of prematurity contribute to QTI dynamics instability. Conclusions— Increased PA frequency and QTI dynamics instability precede VT onset in patients with acute myocardial infarction, as determined by novel methodology for detecting instability in QTI dynamics from clinical ECGs.

Optimizing cardiac resynchronization therapy to minimize ATP consumption heterogeneity throughout the left ventricle: a simulation analysis using a canine heart failure model.

BACKGROUND Cardiac resynchronization therapy (CRT) has been demonstrated to lead to restoration of oxygen consumption homogeneity throughout the left ventricle (LV), which is important for long-term reverse remodeling of the ventricles. However, research has focused exclusively on identifying the LV pacing sites that led to acute hemodynamic improvements. It remains unclear whether there exist LV pacing sites that could both improve the hemodynamics and result in ATP consumption homogeneity throughout the LV, thus maximizing both CRT short-term and long-term benefits. OBJECTIVE The purpose of this study was to demonstrate the feasibility of optimizing CRT pacing locations to achieve maximal improvement in both ATPCTHI (an ATP consumption heterogeneity index) and stroke work. METHODS We used an magnetic resonance image-based electromechanical model of the dyssynchronous heart failure (DHF) canine ventricles. ATPCTHI and stroke work improvement were determined for each of 34 CRT pacing sites evenly spaced over the LV epicardium. RESULTS Results demonstrated the feasibility of determining the optimal LV pacing site that achieves simultaneous maximum improvements in ATPCTHI and stroke work. The optimal LV CRT pacing sites in the DHF canine ventricles were located midway between apex and base. The improvement in ATPCTHI decreased more rapidly with the distance from the optimal sites compared to stroke work improvement. CRT from the optimal sites homogenized ATP consumption by increasing septal ATP consumption and decreasing that of the lateral wall. CONCLUSION Simulation results using a canine heart failure model demonstrated that CRT can be optimized to achieve improvements in both ATPCTHI and stroke work.

Efficient preloading of the ventricles by a properly timed atrial contraction underlies stroke work improvement in the acute response to cardiac resynchronization therapy.

BACKGROUND The acute response to cardiac resynchronization therapy (CRT) has been shown to be due to 3 mechanisms: resynchronization of ventricular contraction, efficient preloading of the ventricles by a properly timed atrial contraction, and mitral regurgitation reduction. However, the contribution of each of the 3 mechanisms to the acute response to CRT, specifically stroke work improvement, has not been quantified. OBJECTIVE To use a magnetic resonance image-based anatomically accurate 3-dimensional model of failing canine ventricular electromechanics to quantify the contribution of each of the 3 mechanisms to stroke work improvement and identify the predominant mechanisms. METHODS An MRI-based electromechanical model of the failing canine ventricles assembled previously by our group was further developed and modified. Three different protocols were used to dissect the contribution of each of the 3 mechanisms to stroke work improvement. RESULTS Resynchronization of ventricular contraction did not lead to a significant stroke work improvement. Efficient preloading of the ventricles by a properly timed atrial contraction was the predominant mechanism underlying stroke work improvement. Stroke work improvement peaked at an intermediate atrioventricular delay, as it allowed ventricular filling by atrial contraction to occur at a low diastolic left ventricular pressure but also provided adequate time for ventricular filling before ventricular contraction. Reduction of mitral regurgitation by CRT led to stroke work worsening instead of improvement. CONCLUSION Efficient preloading of the ventricles by a properly timed atrial contraction is responsible for a significant stroke work improvement in the acute CRT response.

Mechanistic insight into prolonged electromechanical delay in dyssynchronous heart failure: A computational study

In addition to the left bundle branch block type of electrical activation, there are further remodeling aspects associated with dyssynchronous heart failure (HF) that affect the electromechanical behavior of the heart. Among the most important are altered ventricular structure (both geometry and fiber/sheet orientation), abnormal Ca(2+) handling, slowed conduction, and reduced wall stiffness. In dyssynchronous HF, the electromechanical delay (EMD), the time interval between local myocyte depolarization and myofiber shortening onset, is prolonged. However, the contributions of the four major HF remodeling aspects in extending EMD in the dyssynchronous failing heart remain unknown. The goal of this study was to determine the individual and combined contributions of HF-induced remodeling aspects to EMD prolongation. We used MRI-based models of dyssynchronous nonfailing and HF canine electromechanics and constructed additional models in which varying combinations of the four remodeling aspects were represented. A left bundle branch block electrical activation sequence was simulated in all models. The simulation results revealed that deranged Ca(2+) handling is the primary culprit in extending EMD in dyssynchronous HF, with the other aspects of remodeling contributing insignificantly. Mechanistically, we found that abnormal Ca(2+) handling in dyssynchronous HF slows myofiber shortening velocity at the early-activated septum and depresses both myofiber shortening and stretch rate at the late-activated lateral wall. These changes in myofiber dynamics delay the onset of myofiber shortening, thus giving rise to prolonged EMD in dyssynchronous HF.

Unstable QT Interval Dynamics Precedes Ventricular Tachycardia Onset in Patients With Acute Myocardial InfarctionClinical Perspective

Background— Instability in ventricular repolarization in the presence of premature activations (PA) plays an important role in arrhythmogenesis. However, such instability cannot be detected clinically. This study developed a methodology for detecting QT interval (QTI) dynamics instability from the ECG and explored the contribution of PA and QTI instability to ventricular tachycardia (VT) onset. Methods and Results— To examine the contribution of PAs and QTI instability to VT onset, ECGs of 24 patients with acute myocardial infarction, 12 of whom had sustained VT (VT) and 12 nonsustained VT (NSVT), were used. From each patient ECG, 2 10-minute-long ECG recordings were extracted, 1 right before VT onset (onset epoch) and 1 at least 1 hour before it (control epoch). To ascertain how PA affects QTI dynamics stability, pseudo-ECGs were calculated from an MRI-based human ventricular model. Clinical and pseudo-ECGs were subdivided into 1-minute recordings (minECGs). QTI dynamics stability of each minECG was assessed with a novel approach. Frequency of PAs (fPA) and the number of minECGs with unstable QTI dynamics (Nus) were determined for each patient. In the VT group, fPA and Nus of the onset epoch were larger than in control. Positive regression relationships between fPA and Nus were identified in both groups. The simulations showed that both fPA and the PA degree of prematurity contribute to QTI dynamics instability. Conclusions— Increased PA frequency and QTI dynamics instability precede VT onset in patients with acute myocardial infarction, as determined by novel methodology for detecting instability in QTI dynamics from clinical ECGs.Background— Instability in ventricular repolarization in the presence of premature activations (PA) plays an important role in arrhythmogenesis. However, such instability cannot be detected clinically. This study developed a methodology for detecting QT interval (QTI) dynamics instability from the ECG and explored the contribution of PA and QTI instability to ventricular tachycardia (VT) onset. Methods and Results— To examine the contribution of PAs and QTI instability to VT onset, ECGs of 24 patients with acute myocardial infarction, 12 of whom had sustained VT (VT) and 12 nonsustained VT (NSVT), were used. From each patient ECG, 2 10-minute-long ECG recordings were extracted, 1 right before VT onset (onset epoch) and 1 at least 1 hour before it (control epoch). To ascertain how PA affects QTI dynamics stability, pseudo-ECGs were calculated from an MRI-based human ventricular model. Clinical and pseudo-ECGs were subdivided into 1-minute recordings (minECGs). QTI dynamics stability of each minECG was assessed with a novel approach. Frequency of PAs (fPA) and the number of minECGs with unstable QTI dynamics (Nus) were determined for each patient. In the VT group, fPA and Nus of the onset epoch were larger than in control. Positive regression relationships between fPA and Nus were identified in both groups. The simulations showed that both fPA and the PA degree of prematurity contribute to QTI dynamics instability. Conclusions— Increased PA frequency and QTI dynamics instability precede VT onset in patients with acute myocardial infarction, as determined by novel methodology for detecting instability in QTI dynamics from clinical ECGs.