An electrical heart model incorporating real geometry and motion

ST segment and T wave abnormalities: A narrative review

INTRODUCTION

The electrocardiogram (ECG) is a valuable tool for interpreting ventricular repolarization. This article aims to broaden the diagnostic scope beyond the conventional ischemia-centric approach, integrating an understanding of pathophisiological influences on ST-T wave changes.

METHODS

A review was conducted on the physiological underpinnings of ventricular repolarization and the pathophisiological processes that can change ECG patterns. The research encompassed primary repolarization abnormalities due to uniform variations in ventricular action potential, secondary changes from electrical or mechanical alterations, and non-ischemic conditions influencing ST-T segments.

RESULTS

Primary T waves are characterized by symmetrical waves with broad bases and variable QT intervals, indicative of direct myocardial action potential modifications due to ischemia, electrolyte imbalances, and channelopathies. Secondary T waves are asymmetric and often unassociated with significant QT interval changes, suggesting depolarization alterations or changes in cardiac geometry and contractility.

CONCLUSION

We advocate for a unified ECG analysis, recognizing primary and secondary ST-T changes, and their clinical implications. Our proposed analytical framework enhances the clinician's ability to discern a wide array of cardiac conditions, extending diagnostic accuracy beyond myocardial ischemia.

An Introductory Overview of Image-Based Computational Modeling in Personalized Cardiovascular Medicine

Cardiovascular diseases account for the number one cause of deaths in the world. Part of the reason for such grim statistics is our limited understanding of the underlying mechanisms causing these devastating pathologies, which is made difficult by the invasiveness of the procedures associated with their diagnosis (e.g., inserting catheters into the coronal artery to measure blood flow to the heart). Likewise, it is also difficult to design and test assistive devices without implanting them in vivo. However, with the recent advancements made in biomedical scanning technologies and computer simulations, image-based modeling (IBM) has arisen as the next logical step in the evolution of non-invasive patient-specific cardiovascular medicine. Yet, due to its novelty, it is still relatively unknown outside of the niche field. Therefore, the goal of this manuscript is to review the current state-of-the-art and the limitations of the methods used in this area of research, as well as their applications to personalized cardiovascular investigations and treatments. Specifically, the modeling of three different physics – electrophysiology, biomechanics and hemodynamics – used in the cardiovascular IBM is discussed in the context of the physiology that each one of them describes and the mechanisms of the underlying cardiac diseases that they can provide insight into. Only the “bare-bones” of the modeling approaches are discussed in order to make this introductory material more accessible to an outside observer. Additionally, the imaging methods, the aspects of the unique cardiac anatomy derived from them, and their relation to the modeling algorithms are reviewed. Finally, conclusions are drawn about the future evolution of these methods and their potential toward revolutionizing the non-invasive diagnosis, virtual design of treatments/assistive devices, and increasing our understanding of these lethal cardiovascular diseases.

Three-dimensional cardiac computational modelling: methods, features and applications

The combination of computational models and biophysical simulations can help to interpret an array of experimental data and contribute to the understanding, diagnosis and treatment of complex diseases such as cardiac arrhythmias. For this reason, three-dimensional (3D) cardiac computational modelling is currently a rising field of research. The advance of medical imaging technology over the last decades has allowed the evolution from generic to patient-specific 3D cardiac models that faithfully represent the anatomy and different cardiac features of a given alive subject. Here we analyse sixty representative 3D cardiac computational models developed and published during the last fifty years, describing their information sources, features, development methods and online availability. This paper also reviews the necessary components to build a 3D computational model of the heart aimed at biophysical simulation, paying especial attention to cardiac electrophysiology (EP), and the existing approaches to incorporate those components. We assess the challenges associated to the different steps of the building process, from the processing of raw clinical or biological data to the final application, including image segmentation, inclusion of substructures and meshing among others. We briefly outline the personalisation approaches that are currently available in 3D cardiac computational modelling. Finally, we present examples of several specific applications, mainly related to cardiac EP simulation and model-based image analysis, showing the potential usefulness of 3D cardiac computational modelling into clinical environments as a tool to aid in the prevention, diagnosis and treatment of cardiac diseases.