Evaluation of a deep learning-enabled automated computational heart modelling workflow for personalized assessment of ventricular arrhythmias.

Personalized, image-based computational heart modelling is a powerful technology that can be used to improve patient-specific arrhythmia risk stratification and ventricular tachycardia (VT) ablation targeting. However, most state-of-the-art methods still require manual interactions by expert users. The goal of this study is to evaluate the feasibility of an automated, deep learning-based workflow for reconstructing personalized computational electrophysiological heart models to guide patient-specific treatment of VT. Contrast-enhanced computed tomography (CE-CT) images with expert ventricular myocardium segmentations were acquired from 111 patients across five cohorts from three different institutions. A deep convolutional neural network (CNN) for segmenting left ventricular myocardium from CE-CT was developed, trained and evaluated. From both CNN-based and expert segmentations in a subset of patients, personalized electrophysiological heart models were reconstructed and rapid pacing was used to induce VTs. CNN-based and expert segmentations were more concordant in the middle myocardium than in the heart's base or apex. Wavefront propagation during pacing was similar between CNN-based and original heart models. Between most sets of heart models, VT inducibility was the same, the number of induced VTs was strongly correlated, and VT circuits co-localized. Our results demonstrate that personalized computational heart models reconstructed from deep learning-based segmentations even with a small training set size can predict similar VT inducibility and circuit locations as those from expertly-derived heart models. Hence, a user-independent, automated framework for simulating arrhythmias in personalized heart models could feasibly be used in clinical settings to aid VT risk stratification and guide VT ablation therapy. KEY POINTS: Personalized electrophysiological heart modelling can aid in patient-specific ventricular tachycardia (VT) risk stratification and VT ablation targeting. Current state-of-the-art, image-based heart models for VT prediction require expert-dependent, manual interactions that may not be accessible across clinical settings. In this study, we develop an automated, deep learning-based workflow for reconstructing personalized heart models capable of simulating arrhythmias and compare its predictions with that of expert-generated heart models. The number and location of VTs was similar between heart models generated from the deep learning-based workflow and expert-generated heart models. These results demonstrate the feasibility of using an automated computational heart modelling workflow to aid in VT therapeutics and has implications for generalizing personalized computational heart technology to a broad range of clinical centres.

3D-cardiomics: A spatial transcriptional atlas of the mammalian heart.

Understanding the spatial gene expression and regulation in the heart is key to uncovering its developmental and physiological processes, during homeostasis and disease. Numerous techniques exist to gain gene expression and regulation information in organs such as the heart, but few utilize intuitive true-to-life three-dimensional representations to analyze and visualise results. Here we combined transcriptomics with 3D-modelling to interrogate spatial gene expression in the mammalian heart. For this, we microdissected and sequenced transcriptome-wide 18 anatomical sections of the adult mouse heart. Our study has unveiled known and novel genes that display complex spatial expression in the heart sub-compartments. We have also created 3D-cardiomics, an interface for spatial transcriptome analysis and visualization that allows the easy exploration of these data in a 3D model of the heart. 3D-cardiomics is accessible from http://3d-cardiomics.erc.monash.edu/.

Ultrastructural insights into the replication cycle of salmon pancreas disease virus (SPDV) using salmon cardiac primary cultures (SCPCs).

Salmon pancreas disease virus (SPDV) has been affecting the salmon farming industry for over 30 years, but despite the substantial amount of studies, there are still a number of recognized knowledge gaps, for example in the transmission of the virus. In this work, an ultrastructural morphological approach was used to describe observations after infection by SPDV of an ex vivo cardiac model generated from Atlantic salmon embryos. The observations in this study and those available on previous ultrastructural work on SPDV are compared and contrasted with the current knowledge on terrestrial mammalian and insect alphaviral replication cycles, which is deeper than that of SPDV both morphologically and mechanistically. Despite their limitations, morphological descriptions remain an excellent way to generate novel hypotheses, and this has been the aim of this work. This study has used a target host, ex vivo model and resulted in some previously undescribed features, including filopodial membrane projections, cytoplasmic stress granules or putative intracytoplasmic budding. The latter suggests a new hypothesis that warrants further mechanistic research: SPDV in salmon may have retained the capacity for non-cytolytic (persistent) infections by intracellular budding, similar to that noted in arthropod vectors of other alphaviruses. In the notable absence of a known intermediate host for SPDV, the presence of this pattern suggests that both cytopathic and persistent infections may coexist in the same host. It is our hope that the ultrastructural comparison presented here stimulates new research that brings the knowledge on SPDV replication cycle up to a similar level to that of terrestrial alphaviruses.

Cardiomyocyte cell cycling, maturation, and growth by multinucleation in postnatal swine.

BACKGROUND: Rodent cardiomyocytes (CM) undergo mitotic arrest and decline of mononucleated-diploid population post-birth, which are implicated in neonatal loss of heart regenerative potential. However, the dynamics of postnatal CM maturation are largely unknown in swine, despite a similar neonatal cardiac regenerative capacity as rodents. Here, we provide a comprehensive analysis of postnatal cardiac maturation in swine, including CM cell cycling, multinucleation and hypertrophic growth, as well as non-CM cardiac factors such as extracellular matrix (ECM), immune cells, capillaries, and neurons. Our study reveals discordance in postnatal pig heart maturational events compared to rodents. METHODS AND RESULTS: Left-ventricular myocardium from White Yorkshire-Landrace pigs at postnatal day (P)0 to 6 months (6mo) was analyzed. Mature cardiac sarcomeric characteristics, such as fetal TNNI1 repression and Cx43 co-localization to cell junctions, were not evident until P30 in pigs. In CMs, appreciable binucleation is observed by P7, with extensive multinucleation (4-16 nuclei per CM) beyond P15. Individual CM nuclei remain predominantly diploid at all ages. CM mononucleation at ~50% incidence is observed at P7-P15, and CM mitotic activity is measurable up to 2mo. CM cross-sectional area does not increase until 2mo-6mo in pigs, though longitudinal CM growth proportional to multinucleation occurs after P15. RNAseq analysis of neonatal pig left ventricles showed increased expression of ECM maturation, immune signaling, neuronal remodeling, and reactive oxygen species response genes, highlighting significance of the non-CM milieu in postnatal mammalian heart maturation. CONCLUSIONS: CM maturational events such as decline of mononucleation and cell cycle arrest occur over a 2-month postnatal period in pigs, despite reported loss of heart regenerative potential by P3. Moreover, CMs grow primarily by multinucleation and longitudinal hypertrophy in older pig CMs, distinct from mice and humans. These differences are important to consider for preclinical testing of cardiovascular therapies using swine, and may offer opportunities to study aspects of heart regeneration unavailable in other models.

Considering discrepancy when calibrating a mechanistic electrophysiology model.

Uncertainty quantification (UQ) is a vital step in using mathematical models and simulations to take decisions. The field of cardiac simulation has begun to explore and adopt UQ methods to characterize uncertainty in model inputs and how that propagates through to outputs or predictions; examples of this can be seen in the papers of this issue. In this review and perspective piece, we draw attention to an important and under-addressed source of uncertainty in our predictions-that of uncertainty in the model structure or the equations themselves. The difference between imperfect models and reality is termed model discrepancy, and we are often uncertain as to the size and consequences of this discrepancy. Here, we provide two examples of the consequences of discrepancy when calibrating models at the ion channel and action potential scales. Furthermore, we attempt to account for this discrepancy when calibrating and validating an ion channel model using different methods, based on modelling the discrepancy using Gaussian processes and autoregressive-moving-average models, then highlight the advantages and shortcomings of each approach. Finally, suggestions and lines of enquiry for future work are provided. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.

Four-dimensional virtual reality cine cardiac models using free open-source software.

This is a proof-of-concept study to create a four-dimensional (4-D) cine model of the heart and visualize it in virtual reality by using freely available open-source software and inexpensive hardware. Four-dimensional cine models allow for real-time visualization of cardiac structures during processes such as complex congenital heart disease. Such models can be used for patient and trainee education, and potentially for surgical planning. Currently, 3-D printed models are more commonly used, but they are static, showing only one selected phase of the cardiac cycle. Second, they are limited by the selection of clipping planes before printing. Four-dimensional segmentation and virtual reality visualization overcome these limitations. Currently, most of the work in virtual/augmented reality models involves the segmentation of one cardiac phase or the use of expensive software for multiphase segmentation. In this study, we show an approach for multiphase cardiac segmentation as well as its display using free open-source software and relatively inexpensive hardware.

Myocardial Slices: an Intermediate Complexity Platform for Translational Cardiovascular Research.

Myocardial slices, also known as "cardiac tissue slices" or "organotypic heart slices," are ultrathin (100-400 µm) slices of living adult ventricular myocardium prepared using a high-precision vibratome. They are a model of intermediate complexity as they retain the native multicellularity, architecture, and physiology of the heart, while their thinness ensures adequate oxygen and metabolic substrate diffusion in vitro. Myocardial slices can be produced from a variety of animal models and human biopsies, thus providing a representative human in vitro platform for translational cardiovascular research. In this review, we compare myocardial slices to other in vitro models and highlight some of the unique advantages provided by this platform. Additionally, we discuss the work performed in our laboratory to optimize myocardial slice preparation methodology, which resulted in highly viable myocardial slices from both large and small mammalian hearts with only 2-3% cardiomyocyte damage and preserved structure and function. Applications of myocardial slices span both basic and translational cardiovascular science. Our laboratory has utilized myocardial slices for the investigation of cardiac multicellularity, visualizing 3D collagen distribution and micro/macrovascular networks using tissue clearing protocols and investigating the effects of novel conductive biomaterials on cardiac physiology. Myocardial slices have been widely used for pharmacological testing. Finally, the current challenges and future directions for the technology are discussed.

Is a Three-Dimensional Printing Model Better Than a Traditional Cardiac Model for Medical Education? A Pilot Randomized Controlled Study.

BACKGROUND: Three-dimensional (3D) printing is a newly-emerged technology converting a series of two-dimensional images to a touchable 3D model, but no studies have investigated whether or not a 3D printing model is better than a traditional cardiac model for medical education. METHODS: A 3D printing cardiac model was generated using multi-slice computed tomography datasets. Thirty-four medical students were randomized to either the 3D Printing Group taught with the aid of a 3D printing cardiac model or the Traditional Model Group with a commonly used plastic cardiac model. Questionnaires with 10 medical questions and 3 evaluative questions were filled in by the students. RESULTS: A 3D printing cardiac model was successfully generated. Students in the 3D Printing Group were slightly quicker to answer all questions when compared with the Traditional Model Group (224.53 ± 44.13 s vs. 238.71 ± 68.46 s, p = 0.09), but the total score was not significantly different (6.24 ± 1.30 vs. 7.18 ± 1.70, p = 0.12). Neither the students'satisfaction (p = 0.48) nor their understanding of cardiac structures (p = 0.24) was significantly different between two groups. More students in the 3D Printing Group believed that they had understood at least 90% of teaching content (6 vs. 1). Both groups had 12 (70.6%) students who preferred a 3D printing model for medical education. CONCLUSIONS: A 3D printing model was not significantly superior to a traditional model in teaching cardiac diseases in our pilot randomized controlled study, yet more studies may be conducted to validate the real effect of 3D printing on medical education.

Integrated whole-heart computational workflow for inverse potential mapping and personalized simulations.

BACKGROUND: Integration of whole-heart activation simulations and inverse potential mapping (IPM) could benefit the guidance and planning of electrophysiological procedures. Routine clinical application requires a fast and adaptable workflow. These requirements limit clinical translation of existing simulation models. This study proposes a comprehensive finite element model (FEM) based whole-heart computational workflow suitable for IPM and simulations. METHODS: Three volunteers and eight patients with premature ventricular contractions underwent body surface potential (BSP) acquisition followed by a cardiac MRI (CMR) scan. The cardiac volumes were segmented from the CMR images using custom written software. The feasibility to integrate tissue-characteristics was assessed by generating meshes with virtual edema and scar. Isochronal activation maps were constructed by identifying the fastest route through the cardiac volume using the Möller-Trumbore and Floyd-Warshall algorithms. IPM's were reconstructed from the BSP's. RESULTS: Whole-heart computational meshes were generated within seconds. The first point of atrial activation on IPM was located near the crista terminalis of the superior vena cave into the right atrium. The IPM demonstrated the ventricular epicardial breakthrough at the attachment of the moderator band with the right ventricular free wall. Simulations of sinus rhythm were successfully performed. The conduction through the virtual edema and scar meshes demonstrated delayed activation or a complete conductional block respectively. CONCLUSION: The proposed FEM based whole-heart computational workflow offers an integrated platform for cardiac electrical assessment using simulations and IPM. This workflow can incorporate patient-specific electrical parameters, perform whole-heart cardiac activation simulations and accurately reconstruct cardiac activation sequences from BSP's.

Interaction of a Transapical Miniaturized Ventricular Assist Device With the Left Ventricle: Hemodynamic Evaluation and Visualization in an Isolated Heart Setup.

New left ventricular assist devices (LVADs) offer both important advantages and potential hazards. VAD development requires better and expeditious ways to identify these advantages and hazards. We validated in an isolated working heart the hemodynamic performance of an intraventricular LVAD and investigated how its outflow cannula interacted with the aortic valve. Hearts from six pigs were explanted and connected to an isolated working heart setup. A miniaturized LVAD was implanted within the left ventricle (tMVAD, HeartWare Inc., Miami Lakes, FL, USA). In four experiments blood was used to investigate hemodynamics under various loading conditions. In two experiments crystalloid perfusate was used, allowing visualization of the outflow cannula within the aortic valve. In all hearts the transapical miniaturized ventricular assist device (tMVAD) implantation was successful. In the blood experiments hemodynamics similar to those observed clinically were achieved. Pump speeds ranged from 9 to 22 krpm with a maximum of 7.6 L/min against a pressure difference between ventricle and aorta of ∼50 mm Hg. With crystalloid perfusate, central positioning of the outflow cannula in the aortic root was observed during full and partial support. With decreasing aortic pressures the cannula tended to drift toward the aortic root wall. The tMVAD could unload the ventricle similarly to LVADs under conventional cannulation. Aortic pressure influenced central positioning of the outflow cannula in the aortic root. The isolated heart is a simple, accessible evaluation platform unaffected by complex reactions within a whole, living animal. This platform allowed detection and visualization of potential hazards.

Development of a three-dimensional computer model of the equine heart using a polyurethane casting technique and in vivo contrast-enhanced computed tomography.

INTRODUCTION/OBJECTIVES: Insight into the three-dimensional (3D) anatomy of the equine heart is essential in veterinary education and to develop minimally invasive intracardiac procedures. The aim was to create a 3D computer model simulating the in vivo anatomy of the adult equine heart. ANIMALS: Ten horses and five ponies. MATERIALS AND METHODS: Ten horses, euthanized for non-cardiovascular reasons, were used for in situ cardiac casting with polyurethane foam and subsequent computed tomography (CT) of the excised heart. In five anaesthetized ponies, a contrast-enhanced electrocardiogram-gated CT protocol was optimized to image the entire heart. Dedicated image processing software was used to create 3D models of all CT scans derived from both methods. Resulting models were compared regarding relative proportions, detail and ease of segmentation. RESULTS: The casting protocol produced high detail, but compliant structures such as the pulmonary trunk were disproportionally expanded by the foam. Optimization of the contrast-enhanced CT protocol, especially adding a delayed phase for visualization of the cardiac veins, resulted in sufficiently detailed CT images to create an anatomically correct 3D model of the pony heart. Rescaling was needed to obtain a horse-sized model. CONCLUSIONS: Three-dimensional computer models based on contrast-enhanced CT images appeared superior to those based on casted hearts to represent the in vivo situation and are preferred to obtain an anatomically correct heart model useful for education, client communication and research purposes. Scaling was, however, necessary to obtain an approximation of an adult horse heart as cardiac CT imaging is restricted by thoracic size.

An Exploratory Pilot Study on the Application of Radiofrequency Ablation for Atrial Fibrillation Guided by Computed Tomography-Based 3D Printing Technology.

Radiofrequency ablation (RFA) is the treatment of choice for atrial fibrillation (AF). Additionally, the utilization of 3D printing for cardiac models offers an in-depth insight into cardiac anatomy and cardiovascular diseases. The study aims to evaluate the clinical utility and outcomes of RFA following in vitro visualization of the left atrium (LA) and pulmonary vein (PV) structures via 3D printing (3DP). Between November 2017 and April 2021, patients who underwent RFA at the First Affiliated Hospital of Xinxiang Medical University were consecutively enrolled and randomly allocated into two groups: the 3DP group and the control group, in a 1:1 ratio. Computed tomography angiography (CTA) was employed to capture the morphology and diameter of the LA and PV, which facilitated the construction of a 3D entity model. Additionally, surgical procedures were simulated using the 3D model. Parameters such as the duration of the procedure, complications, and rates of RFA recurrence were meticulously documented. Statistical analysis was performed using the t-test or Mann-Whitney U test to evaluate the differences between the groups, with a P-value of less than 0.05 considered statistically significant. In this study, a total of 122 patients were included, with 53 allocated to the 3DP group and 69 to the control group. The analysis of the morphological measurements of the LA and PV taken from the workstation or direct entity measurement showed no significant difference between the two groups (P > 0.05). However, patients in the 3DP group experienced significantly shorter RFA times (97.03 ± 28.39 compared to 120.51 ± 44.76 min, t = 3.05, P = 0.003), reduced duration of radiation exposure (2.55 [interquartile range 2.01, 3.24] versus 3.20 [2.28, 3.91] min, Z = 3.23, P < 0.001), and shorter modeling times (7.68 ± 1.03 compared to 8.89 ± 1.45 min, t = 5.38, P < 0.001). 3DP technology has the potential to enhance standard RFA practices by reducing the time required for intraoperative interventions and exposure to radiation.

Surgical Correction of a Sinus Venosus Atrial Septal Defect with Partial Anomalous Pulmonary Venous Connections Using Cardiac Computed Tomography Imaging and a 3D-Printed Model.

Sinus venosus atrial septal defects (SVASDs), concurrent with partial anomalous pulmonary venous connections (PAPVCs), are a rare congenital heart disease in dogs. Surgical correction is essential when clinical signs or significant hemodynamic changes are present. We aimed to report on the successful surgical correction of an SVASD with PAPVCs, using a computed tomography (CT)-based customized 3D cardiac model. A 10-month-old male poodle was referred for corrective surgery for an ASD. Echocardiography confirmed a hemodynamically significant left-to-right shunting flow through an interatrial septal defect and severe right-sided heart volume overload. For a comprehensive diagnosis, a CT scan was performed, which confirmed an SVASD with PAPVCs. A customized 3D cardiac model was used for preoperative decision-making and surgical rehearsal. The defect was repaired using an autologous pericardial patch under a cardiopulmonary bypass (CPB). Temporary pacing was applied for sinus bradycardia and third-degree atrioventricular block. The patient recovered from the anesthesia without further complications. The pacemaker was removed during hospitalization and the patient was discharged without complications 2 weeks post-surgery. At the three-month follow-up, there was no shunting flow in the interatrial septum and the right-sided volume overload had been resolved. The cardiac medications were discontinued, and there were no complications. This report indicates the validity of surgical correction under CPB for an SVASD with PAPVCs, and the advantages of utilizing a CT-based 3D cardiac model for preoperative planning to increase the surgical success rate.

Toward a Physiologically Relevant 3D Helicoidal-Oriented Cardiac Model: Simultaneous Application of Mechanical Stimulation and Surface Topography.

Myocardium consists of cardiac cells that interact with their environment through physical, biochemical, and electrical stimulations. The physiology, function, and metabolism of cardiac tissue are affected by this dynamic structure. Within the myocardium, cardiomyocytes' orientations are parallel, creating a dominant orientation. Additionally, local alignments of fibers, along with a helical organization, become evident at the macroscopic level. For the successful development of a reliable in vitro cardiac model, evaluation of cardiac cells' behavior in a dynamic microenvironment, as well as their spatial architecture, is mandatory. In this study, we hypothesize that complex interactions between long-term contraction boundary conditions and cyclic mechanical stimulation may provide a physiological mechanism to generate off-axis alignments in the preferred mechanical stretch direction. This off-axis alignment can be engineered in vitro and, most importantly, mirrors the helical arrangements observed in vivo. For this purpose, uniaxial mechanical stretching of dECM-fibrin hydrogels was performed on pre-aligned 3D cultures of cardiac cells. In view of the potential development of helical structures similar to those in native hearts, the possibility of generating oblique alignments ranging between 0° and 90° was explored. Indeed, our investigations of cell alignment in 3D, employing both mechanical stimulation and groove constraint, provide a reliable mechanism for the generation of helicoidal structures in the myocardium. By combining cyclic stretch and geometric alignment in grooves, an intermediate angle toward favored direction can be achieved experimentally: while cyclic stretch produces a perpendicular orientation, geometric alignment is associated with a parallel one. In our 2D and 3D culture conditions, nonlinear cellular addition of the strains and strain avoidance concept reliably predicted the preferred cellular alignment. The 3D dECM-fibrin model system in this study shows that cyclical stretching supports cell survival and development. Using mechanical stimulation of pre-aligned heart cells, maturation markers are augmented in neonatal cardiomyocytes, while the beating culture period is prolonged, indicating an improved model function. We propose a simplified theoretical model based on numerical simulation and nonlinear strain avoidance by cells to explain oblique alignment angles. Thus, this work lays a possible rational basis for understanding and engineering oblique cellular alignments, such as the helicoidal layout of the heart, using approaches that simultaneously enhance maturation and function.

Biomimetic Cardiac Tissue Models for In Vitro Arrhythmia Studies.

Cardiac arrhythmias are a major cause of cardiovascular mortality worldwide. Many arrhythmias are caused by reentry, a phenomenon where excitation waves circulate in the heart. Optical mapping techniques have revealed the role of reentry in arrhythmia initiation and fibrillation transition, but the underlying biophysical mechanisms are still difficult to investigate in intact hearts. Tissue engineering models of cardiac tissue can mimic the structure and function of native cardiac tissue and enable interactive observation of reentry formation and wave propagation. This review will present various approaches to constructing cardiac tissue models for reentry studies, using the authors' work as examples. The review will highlight the evolution of tissue engineering designs based on different substrates, cell types, and structural parameters. A new approach using polymer materials and cellular reprogramming to create biomimetic cardiac tissues will be introduced. The review will also show how computational modeling of cardiac tissue can complement experimental data and how such models can be applied in the biomimetics of cardiac tissue.

Predicting human cardiac QT alterations and pro-arrhythmic effects of compounds with a 3D beating heart-on-chip platform.

Determining the potential cardiotoxicity and pro-arrhythmic effects of drug candidates remains one of the most relevant issues in the drug development pipeline (DDP). New methods enabling to perform more representative preclinical in vitro studies by exploiting induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) are under investigation to increase the translational power of the outcomes. Here we present a pharmacological campaign conducted to evaluate the drug-induced QT alterations and arrhythmic events on uHeart, a 3D miniaturized in vitro model of human myocardium encompassing iPSC-CM and dermal fibroblasts embedded in fibrin. uHeart was mechanically trained resulting in synchronously beating cardiac microtissues in 1 week, characterized by a clear field potential (FP) signal that was recorded by means of an integrated electrical system. A drug screening protocol compliant with the new International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) guidelines was established and uHeart was employed for testing the effect of 11 compounds acting on single or multiple cardiac ion channels and well-known to elicit QT prolongation or arrhythmic events in clinics. The alterations of uHeart's electrophysiological parameters such as the beating period, the FP duration, the FP amplitude, and the detection of arrhythmic events prior and after drug administration at incremental doses were effectively analyzed through a custom-developed algorithm. Results demonstrated the ability of uHeart to successfully anticipate clinical outcome and to predict the QT prolongation with a sensitivity of 83.3%, a specificity of 100% and an accuracy of 91.6%. Cardiotoxic concentrations of drugs were notably detected in the range of the clinical highest blood drug concentration (Cmax), qualifying uHeart as a fit-to-purpose preclinical tool for cardiotoxicity studies.

Constructing bilayer and volumetric atrial models at scale.

To enable large in silico trials and personalized model predictions on clinical timescales, it is imperative that models can be constructed quickly and reproducibly. First, we aimed to overcome the challenges of constructing cardiac models at scale through developing a robust, open-source pipeline for bilayer and volumetric atrial models. Second, we aimed to investigate the effects of fibres, fibrosis and model representation on fibrillatory dynamics. To construct bilayer and volumetric models, we extended our previously developed coordinate system to incorporate transmurality, atrial regions and fibres (rule-based or data driven diffusion tensor magnetic resonance imaging (MRI)). We created a cohort of 1000 biatrial bilayer and volumetric models derived from computed tomography (CT) data, as well as models from MRI, and electroanatomical mapping. Fibrillatory dynamics diverged between bilayer and volumetric simulations across the CT cohort (correlation coefficient for phase singularity maps: left atrial (LA) 0.27 ± 0.19, right atrial (RA) 0.41 ± 0.14). Adding fibrotic remodelling stabilized re-entries and reduced the impact of model type (LA: 0.52 ± 0.20, RA: 0.36 ± 0.18). The choice of fibre field has a small effect on paced activation data (less than 12 ms), but a larger effect on fibrillatory dynamics. Overall, we developed an open-source user-friendly pipeline for generating atrial models from imaging or electroanatomical mapping data enabling in silico clinical trials at scale (https://github.com/pcmlab/atrialmtk).

Advancing clinical translation of cardiac biomechanics models: a comprehensive review, applications and future pathways.

Cardiac mechanics models are developed to represent a high level of detail, including refined anatomies, accurate cell mechanics models, and platforms to link microscale physiology to whole-organ function. However, cardiac biomechanics models still have limited clinical translation. In this review, we provide a picture of cardiac mechanics models, focusing on their clinical translation. We review the main experimental and clinical data used in cardiac models, as well as the steps followed in the literature to generate anatomical meshes ready for simulations. We describe the main models in active and passive mechanics and the different lumped parameter models to represent the circulatory system. Lastly, we provide a summary of the state-of-the-art in terms of ventricular, atrial, and four-chamber cardiac biomechanics models. We discuss the steps that may facilitate clinical translation of the biomechanics models we describe. A well-established software to simulate cardiac biomechanics is lacking, with all available platforms involving different levels of documentation, learning curves, accessibility, and cost. Furthermore, there is no regulatory framework that clearly outlines the verification and validation requirements a model has to satisfy in order to be reliably used in applications. Finally, better integration with increasingly rich clinical and/or experimental datasets as well as machine learning techniques to reduce computational costs might increase model reliability at feasible resources. Cardiac biomechanics models provide excellent opportunities to be integrated into clinical workflows, but more refinement and careful validation against clinical data are needed to improve their credibility. In addition, in each context of use, model complexity must be balanced with the associated high computational cost of running these models.

Case Report: Fluoroless implantation of left branch bundle pacing in a pregnant patient.

A pregnant patient had symptomatic atrial standstill and indications for pacing therapy with an expected high ventricular pacing ratio. With the consideration of potential pacing-induced cardiomyopathy in the future we conducted zero-fluoro left bundle branch pacing (zLBBP) implantation for heart failure prevention. An ex vivo 3D cardiac model (Medtronic, USA) was used preoperatively to simulate the zLBBP implantation to improve procedure safety and efficiency. Intraoperatively, the simulation steps were followed, and a combination of electroanatomic navigation systems (EANS) and intracardiac echocariography (ICE) were used to ensure that the procedure was performed efficiently and safely.

A Three-Dimensional Engineered Cardiac In Vitro Model: Controlled Alignment of Cardiomyocytes in 3D Microphysiological Systems.

Cardiomyocyte alignment in myocardium tissue plays a significant role in the physiological, electrical, and mechanical functions of the myocardium. It remains, however, difficult to align cardiac cells in a 3D in vitro heart model. This paper proposes a simple method to align cells using microfabricated Polydimethylsiloxane (PDMS) grooves with large dimensions (of up to 350 µm in width), similar to the dimensions of trabeculae carneae, the smallest functional unit of the myocardium. Two cell groups were used in this work; first, H9c2 cells in combination with Nor10 cells for proof of concept, and second, neonatal cardiac cells to investigate the functionality of the 3D model. This model compared the patterned and nonpatterned 3D constructs, as well as the 2D cell cultures, with and without patterns. In addition to alignment, we assessed the functionality of our proposed 3D model by comparing beating rates between aligned and non-aligned structures. In order to assess the practicality of the model, the 3D aligned structures should be demonstrated to be detachable and alignable. This evaluation is crucial to the use of this 3D functional model in future studies related to drug screening, building blocks for tissue engineering, and as a heart-on-chip by integrating microfluidics.