Functional Imaging and Modeling of the Heart

This book constitutes the refereed proceedings of the 11th International Conference on Functional Imaging and Modeling of the Heart, which took place online during June 21-24, 2021, organized by the University of Stanford.

The 65 revised full papers were carefully reviewed and selected from 68 submissions. They were organized in topical sections as follows: advanced cardiac and cardiovascular image processing; cardiac microstructure: measures and models; novel approaches to measuring heart deformation; cardiac mechanics: measures and models; translational cardiac mechanics; modeling electrophysiology, ECG, and arrhythmia; cardiovascular flow: measures and models; and atrial microstructure, modeling, and thrombosis prediction.

Contenu
Population-based personalization of geometric models of myocardial infarction.- Impact of Image Resolution and Resampling on Motion Tracking of the Left Chambers from Cardiac Scans.- Shape Constraints in Deep Learning for Robust 2D Echocardiography Analysis.- Image-Derived Geometric Characteristics Predict Abdominal Aortic Aneurysm Growth in a Machine Learning Model.- Cardiac MRI Left Ventricular Segmentation and Function Quantification Using Pre-trained Neural Networks.- Three-Dimensional Embedded Attentive RNN (3D-EAR) Segmentor for Left Ventricle Delineation from Myocardial Velocity Mapping.- Whole Heart Anatomical Refinement from CCTA using Extrapolation and Parcellation.- Optimisation of Left Atrial Feature Tracking using Retrospective Gated Computed Tomography Images.- Assessment of geometric models for the approximation of aorta cross-sections.- Improved High Frame Rate Speckle Tracking for Echocardiography.- Efficient Model Monitoring for Quality Control in Cardiac ImageSegmentation.- Domain adaptation for automatic aorta segmentation of 4D flow magnetic resonance imaging data from multiple vendor scanners.- A multi-step machine learning approach for short axis MR images segmentation.- Diffusion biomarkers in chronic myocardial infarction.- Spatially constrained Deep Learning approach for myocardial T1 mapping.- A methodology for accessing the local arrangement of the sheetlets that make up the extracellular heart tissue.- A High-Fidelity 3D Micromechanical Model of Ventricular Myocardium.- Quantitative Interpretation of Myocardial Fiber Structure in the Left and Right Ventricle of an Equine Heart using Diffusion Tensor Cardiovascular Magnetic Resonance Imaging.- Analysis of Location-Dependent Cardiomyocyte Branching.- Systematic Study of Joint Influence of Angular Resolution and Noise in Cardiac Diffusion Tensor Imaging.- Arbitrary Point Tracking with Machine Learning to Measure Cardiac Strain in Tagged MRI.- Investigation of the impact of normalization on the study of interactions between myocardial shape and deformation.- Reproducibility of Left Ventricular CINE DENSE Strain in Pediatric Subjects with Duchenne Muscular Dystrophy.- M-SiSSR: Regional Endocardial Function using Multilabel Simultaneous Subdivision Surface Registration.- CNN-based Cardiac Motion Extraction to Generate Deformable Geometric Left Ventricle Myocardial Models from Cine MRI.- Multiscale Graph Convolutional Networks for Cardiac Motion Analysis.- An image registration framework to estimate 3D myocardial strains from cine cardiac MRI in mice.- Sensitivity of Myocardial Stiffness Estimates to Inter-observer Variability in LV Geometric Modelling.- A computational approach on sensitivity of left ventricular wall strains to fiber orientation.- A Framework for Evaluating Myocardial Stiffness Using 3D-Printed Heart Phantoms.- Modeling patient-specific periaortic interactions with static and dynamic structures using a moving heterogeneous elastic foundation boundarycondition.- An Exploratory Assessment of Focused Septal Growth in Hypertrophic Cardiomyopathy.- Parameter Estimation in a Rule-Based Fiber Orientation model from End Systolic Strains Using the Reduced Order Unscented Kalman Filter.- Effects of fibre orientation on electrocardiographic and mechanical functions in a computational human biventricular model.- Model-assisted time-synchronization of cardiac MR image and catheter pressure data.- From clinical imaging to patient-specific computational model: Rapid adaptation of the Living Heart Human Model to a case of aortic stenosis.- Cardiac support for the right ventricle: effects of timing on hemodynamics-biomechanics tradeoff.- In vivo pressure-volume loops and chamber stiffness estimation using real-time 3D echocardiography and left ventricular catheterization application to post-heart transplant patients .- In silico mapping of the omecamtiv mecarbil effects from the sarcomere to the whole-heart and back again.- High-Speed Simulation of the 3D Behavior of Myocardium Using a Neural Network PDE Approach.- On the interrelationship between left ventricle infarction geometry and ischemic mitral regurgitation grade.- Cardiac modeling for Multisystem Inflammatory Syndrome in Children (MIS-C, PIMS-TS).- Personal-by-design: a 3D Electromechanical Model of the Heart Tailored for Personalisation.- Scar-Related Ventricular Arrhythmia Prediction from Imaging using Explainable Deep Learning.- Deep Adaptive Electrocardiographic Imaging with Generative Forward Model for Error Reduction.- EP-Net 2.0: Out-of-Domain Generalisation for Deep Learning Models of Cardiac Electrophysiology.- Simultaneous Multi-Heartbeat ECGI Solution with a Time-Varying Forward Model: a Joint Inverse Formulation.- The Effect of Modeling Assumptions on the ECG in Monodomain and Bidomain Simulations.- Uncertainty Quantification of the Effects of Segmentation Variability in ECGI.- Spiral Waves Generation using an Eikonal-reaction Cardiac Electrophysiology Model.- Simplified Electrophysiology Modeling Framework to Assess Ventricular Arrhythmia Risk in Infarcted Patients.- Sensitivity analysis of a smooth muscle cell electrophysiological model..- A volume source method for solving ECGI inverse problem.- Fast and Accurate Uncertainty Quantification for the ECG with Random Electrodes Location.- Quantitative Hemodynamics in Aortic Dissection: Comparing in vitro MRI with FSI Simulation in a Compliant Model.- 3-D Intraventricular Vector Flow mapping Using Triplane Doppler Echo.- The role of extra-coronary vascular conditions that affect coronary fractional flow reserve estimation..- In-silico analysis of the influence of pulmonary vein configuration on left atrial haemodynamics and thrombus formation in a large cohort.- Shape analysis and computational fluid simulations to assess feline left atrial function and thrombogenesis.- Using the Universal Atrial Coordinate system for MRI and electroanatomic data registration in patient-specific left atrial model construction and simulation.- Geometric Deep Learning for the Assessment of Thrombosis Risk in the Left Atrial Appendage.- Learning atrial fiber orientations and conductivity tensors from intracardiac maps using physics-informed neural networks.- The Effect of Ventricular Myofibre Orientation on Atrial Dynamics.- Intra-Cardiac Signatures of Atrial Arrhythmias Identified By Machine Learning and Traditional Features.- Computational Modelling of the Role of Atrial Fibrillation on Cerebral Blood Perfusion..