Diseases of the heart and blood vessels are the most common cause of death in the United States. Atherogenesis is the production of degenerative accumulation of material (also known as plaque), especially in arterial walls, that are a predominant cause of heart attacks. Current clinical practice is based on angiography, which produces a 2D projection of the 3D lumen area. However, essential information about arterial volume, plaque volume, lumen volume, minimum- and maximum volumes of each type, etc. cannot be assessed. Intracoronary ultrasound is becoming a popular technique, because it provides transmural images of coronary arteries in vivo. Potentially, it can provide the volume information.
The aim of the project is to provide an off-line image processing system for an objective and quantitative description of the degree of atherosclerosis. We propose the development of robust and automated algorithms to extract the medically relevant features. The developed algorithms will undergo first-stage clinical testing to provide a statistical assessment of robustness, accuracy, reproducibility, and reliability. The long term objective is to create an integrated, and easy to operate clinical imaging system for the on-line analysis of intravascular ultrasound images that uses the new image processing software as a basic building bloc.
A system, which is capable of quantitatively measuring the additional information obtained by ultrasound imaging, opens up new possibilities in both interventional and diagnostic procedures in hospitals and pharmacological environments. The product allows an objective measure of interventional success and also a statistical evaluation of the long-term progression of the disease. An automatic system reduces the cost of a medical treatment by providing faster and more accurate measurements, eliminating time-consuming manual evaluation of the data. Considering the increasing number of ultrasound interventions, the proposed system has a large commercial potential.
