A simple tool for Visualizing Time Sections of Transesophageal Echocardiography with Python

Background Transesophageal echocardiography (TEE) is a critical tool in diagnosing and managing infectious endocarditis, providing detailed images of cardiac structures. However, identifying vegetations on valves and their dynamic behavior in ultrasound videos can be challenging. TEEs metadata often does not include scale enabling computation of speed. Objectives To address this, we developed a simple Python-based tool that enhances the visualization of these dynamic characteristics. This tool reconstructs an optical flow from TEE images, capturing the motion of cardiac structures and offering deeper insights into their behavior. The tool also recovers scale from visual information on the TEES. Methods By leveraging the Marching Cubes algorithm and 2D Fast Fourier Transform (FFT) to recover scale from images, the tool efficiently processes video frames to create a 3D representation where time is the third dimension. Wit his mouse the user can select temporal slices and a view of the dynamic evolution in that slice is created together with the speeds. Results This approach allows for measurement of thicknesses and speeds, aiding in the evaluation of valvular and vegetation dynamics. Conclusions The tool’s user-friendly interface, built with Dash and Plotly, enables interactive analysis and visualization, making it a valuable asset for cardiologists in clinical settings to further analyze valvular behavior.