Development of a Robust Algorithm for 3D-Rendering of Multi-2D Electromechanical Wave Imaging Maps and CT Registration

Abstract

This study addresses the need for improved, non-invasive localization of arrhythmogenic sources in cardiac arrhythmias, which are common and can be life-threatening if untreated. Current methods for arrhythmia characterization can be either imprecise or highly invasive, limiting their clinical accessibility. Electromechanical Wave Imaging (EWI), a non-invasive ultrasound based modality, offers real-time 2D and 3D maps of the heart’s electrical activation and holds promise for advancing arrhythmia localization. The primary objective of this thesis is to develop an advanced algorithm for rendering multiple 2D EWI views, improving cardiac arrhythmia localization and enhancing clinical utility. This work also introduces a 3D registration process with cardiac CT data to refine anatomical accuracy and provide patient-specific insights. Significant upgrades to the existing 3D EWI algorithm focused on increasing automation, flexibility, and accuracy in visualizing the heart’s electromechanical activity. Additionally, 3D point clouds were registered to CT data, followed by non-rigid surface registration to align 3D EWI maps with CT derived anatomy. Key findings show improvements in spatial coverage and activation mapping accuracy, particularly in under-sampled regions, with the inclusion of structures like the left ventricular outflow tract (LVOT) and mitral valve. The development of a user-friendly graphical interface enhances accessibility for researchers and clinicians. The fusion of functional EWI data with anatomical CT models allows more precise arrhythmia localization, which may lead to improved treatment outcomes. In conclusion, this thesis enhances the accuracy, efficiency, and usability of 3D EWI, positioning it as a more robust and clinically viable tool for studying and treating cardiac conditions. Algorithmic improvements, enhanced visualization, and user-centered design push the boundaries of current EWI technology, making it more adaptable and easier to implement in clinical practice.