SQUARE: Super-resolved QUantified Assessment of valvular Regurgitation using Echocardiography

Cardiac valves are vital to support heart function by ensuring the efficient oxygenation of our body. More than 2% of the population suffer from improper valve closure, leading to regurgitation (i.e. backflow) of part of the blood. Valve regurgitation can severely and silently compromise cardiac efficiency, leading to cardiovascular complications. Accurately assessing the valve anatomy and function is critical to determine the regurgitation severity, cause, repair probability, and optimal surgical time window. 2D transthoracic echocardiography is by far the most commonly used modality to assess the regurgitation severity by combining qualitative and semi-quantitative parameters. Quantification techniques are rarely used, being inaccurate, patient and operator-dependent. This leads to suboptimal clinical decision making and poor patient prognosis. In SQUARE, we channel recent advances in echography to develop a new method to accurately quantify valve regurgitation, by improving the spatiotemporal resolution of intracardiac 3D blood flow images by several orders of magnitude. We expect our method to improve both the feasibility and accuracy of regurgitation quantification.

Keywords:super-resolution ultrasound imaging, valve regurgitation, diagnostic imaging, echocardiography, cardiac flow imaging

Disciplines:Diagnostic radiology, Biomedical modelling, Cardiology, Biomedical instrumentation, Biomedical image processing