Case report of ventricular tachycardia simulation facilitated ablation for refractory ventricular arrhythmia post-myocardial infarction: aiming before firing.

Background: The management of ventricular arrhythmias (VA) following myocardial infarction presents substantial challenges due to the high morbidity and mortality rates, particularly in cases refractory to medical therapy. In certain cases, the arrhythmogenic anatomical substrate is located in the epicardium. Consequently, achieving a transmural injury by endocardial catheter ablation has always been infeasible.

Comparative analysis of the ten Tusscher and Tomek human ventricular cell models at cellular, tissue, and organ levels: Implications for post-infarct ventricular tachycardia simulation.

Computational modeling is a tool for exploring both normal electrical propagation in healthy hearts and cardiac arrhythmias in patients. While numerous human ventricular cell models exist, the ten Tusscher (TT2) model is one of the most used for simulating ventricular arrhythmia. Recently, the Tomek model has been proposed, offering improved accuracy by better reproducing key depolarization, repolarization, and calcium dynamics in healthy ventricular cardiomyocytes.

Progress in the Clinical Application of Artificial Intelligence for Left Ventricle Analysis in Cardiac Magnetic Resonance.

Cardiac magnetic resonance (CMR) imaging enables a one-stop assessment of heart structure and function. Artificial intelligence (AI) can simplify and automate work flows and improve image post-processing speed and diagnostic accuracy; thus, it greatly affects many aspects of CMR. This review highlights the application of AI for left heart analysis in CMR, including quality control, image segmentation, and global and regional functional assessment.

TF-Unet:An automatic cardiac MRI image segmentation method.

Personalized heart models are widely used to study the mechanisms of cardiac arrhythmias and have been used to guide clinical ablation of different types of arrhythmias in recent years. MRI images are now mostly used for model building. In cardiac modeling studies, the degree of segmentation of the heart image determines the success of subsequent 3D reconstructions.

Preliminary Study: Learning the Impact of Simulation Time on Reentry Location and Morphology Induced by Personalized Cardiac Modeling.

Personalized cardiac modeling is widely used for studying the mechanisms of cardiac arrythmias. Due to the high demanding of computational resource of modeling, the arrhythmias induced in the models are usually simulated for just a few seconds. In clinic, it is common that arrhythmias last for more than several minutes and the morphologies of reentries are not always stable, so it is not clear that whether the simulation of arrythmias for just a few seconds is long enough to match the arrhythmias detected in patients.

Current progress of computational modeling for guiding clinical atrial fibrillation ablation.

Atrial fibrillation (AF) is one of the most common arrhythmias, associated with high morbidity, mortality, and healthcare costs, and it places a significant burden on both individuals and society. Anti-arrhythmic drugs are the most commonly used strategy for treating AF. However, drug therapy faces challenges because of its limited efficacy and potential side effects.

Fully Automatic Scar Segmentation for Late Gadolinium Enhancement MRI Images in Left Ventricle with Myocardial Infarction.

Numerous methods have been published to segment the infarct tissue in the left ventricle, most of them either need manual work, post-processing, or suffer from poor reproducibility. We proposed an automatic segmentation method for segmenting the infarct tissue in left ventricle with myocardial infarction. Cardiac images of a total of 60 diseased hearts (55 human hearts and 5 porcine hearts) were used in this study.

Characterizing Conduction Channels in Postinfarction Patients Using a Personalized Virtual Heart.

Patients with myocardial infarction have an abundance of conduction channels (CC); however, only a small subset of these CCs sustain ventricular tachycardia (VT). Identifying these critical CCs (CCCs) in the clinic so that they can be targeted by ablation remains a significant challenge. The objective of this study is to use a personalized virtual-heart approach to conduct a three-dimensional (3D) assessment of CCCs sustaining VTs of different morphologies in these patients, to investigate their 3D structural features, and to determine the optimal ablation strategy for each VT.

Computationally guided personalized targeted ablation of persistent atrial fibrillation.

Atrial fibrillation (AF)-the most common arrhythmia-significantly increases the risk of stroke and heart failure. Although catheter ablation can restore normal heart rhythms, patients with persistent AF who develop atrial fibrosis often undergo multiple failed ablations, and thus increased procedural risks. Here, we present personalized computational modelling for the reliable predetermination of ablation targets, which are then used to guide the ablation procedure in patients with persistent AF and atrial fibrosis.

Sensitivity of Ablation Targets Prediction to Electrophysiological Parameter Variability in Image-Based Computational Models of Ventricular Tachycardia in Post-infarction Patients.

Ventricular tachycardia (VT), which could lead to sudden cardiac death, occurs frequently in patients with myocardial infarction. Computational modeling has emerged as a powerful platform for the non-invasive investigation of lethal heart rhythm disorders in post-infarction patients and for guiding patient VT ablation. However, it remains unclear how VT dynamics and predicted ablation targets are influenced by inter-patient variability in action potential duration (APD) and conduction velocity (CV).

Antibiotics in a typical karst river system in China: Spatiotemporal variation and environmental risks.

Karst aquifers are highly susceptible to contamination because compounds in water from the land surface are able to enter aquifers directly through sinkholes and travel rapidly through conduits. To investigate the occurrence and profiles of antibiotics in the typical karst river system in Kaiyang, southwest China, 34 aqueous samples were collected periodically to delineate seasonal trends in antibiotic levels. Thirty-five antibiotics, including nine sulfonamides, four tetracyclines, five macrolides, 16 quinolones and chloramphenicol, were analysed via solid phase extraction combined with ultra-performance liquid chromatography-tandem mass spectrometry.

Optimal contrast-enhanced MRI image thresholding for accurate prediction of ventricular tachycardia using ex-vivo high resolution models.

Patient specific models created from contrast-enhanced (i.e. late-gadolinium, LGE) MRI images can be used for prediction of reentry location and clinical ablation planning.

Sensitivity of reentrant driver localization to electrophysiological parameter variability in image-based computational models of persistent atrial fibrillation sustained by a fibrotic substrate.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, causing morbidity and mortality in millions worldwide. The atria of patients with persistent AF (PsAF) are characterized by the presence of extensive and distributed atrial fibrosis, which facilitates the formation of persistent reentrant drivers (RDs, i.e.

A feasibility study of arrhythmia risk prediction in patients with myocardial infarction and preserved ejection fraction.

Aim: To predict arrhythmia susceptibility in myocardial infarction (MI) patients with left ventricular ejection fraction (LVEF)  >35% using a personalized virtual heart simulation approach.

Methods And Results: A total of four contrast enhanced magnetic resonance imaging (MRI) datasets of patient hearts with MI and average LVEF of 44.0 ± 2.

Accuracy of prediction of infarct-related arrhythmic circuits from image-based models reconstructed from low and high resolution MRI.

Identification of optimal ablation sites in hearts with infarct-related ventricular tachycardia (VT) remains difficult to achieve with the current catheter-based mapping techniques. Limitations arise from the ambiguities in determining the reentrant pathways location(s). The goal of this study was to develop experimentally validated, individualized computer models of infarcted swine hearts, reconstructed from high-resolution ex-vivo MRI and to examine the accuracy of the reentrant circuit location prediction when models of the same hearts are instead reconstructed from low clinical-resolution MRI scans.

A study of mechanical optimization strategy for cardiac resynchronization therapy based on an electromechanical model.

An optimal electrode position and interventricular (VV) delay in cardiac resynchronization therapy (CRT) improves its success. However, the precise quantification of cardiac dyssynchrony and magnitude of resynchronization achieved by biventricular (BiV) pacing therapy with mechanical optimization strategies based on computational models remain scant. The maximum circumferential uniformity ratio estimate (CURE) was used here as mechanical optimization index, which was automatically computed for 6 different electrode positions based on a three-dimensional electromechanical canine model of heart failure (HF) caused by complete left bundle branch block (CLBBB).

An image-based model of the whole human heart with detailed anatomical structure and fiber orientation.

Many heart anatomy models have been developed to study the electrophysiological properties of the human heart. However, none of them includes the geometry of the whole human heart. In this study, an anatomically detailed mathematical model of the human heart was firstly reconstructed from the computed tomography images.

Simulation of biatrial conduction via different pathways during sinus rhythm with a detailed human atrial model.

In order to better understand biatrial conduction, investigate various conduction pathways, and compare the differences between isotropic and anisotropic conductions in human atria, we present a simulation study of biatrial conduction with known/assumed conduction pathways using a recently developed human atrial model. In addition to known pathways: (1) Bachmann's bundle (BB), (2) limbus of fossa ovalis (LFO), and (3) coronary sinus (CS), we also hypothesize that there exist two fast conduction bundles that connect the crista terminalis (CT), LFO, and CS. Our simulation demonstrates that use of these fast conduction bundles results in a conduction pattern consistent with experimental data.