Abstract

Our purpose is in the automated evaluation of the physiological relevance of lesions in coronary angiograms. We aim to extract as much as possible quantitative information about the physiological condition of the heart from standard angiographic image sequences. Coronary angiography is still the gold standard for evaluating and diagnosing coronary abnormalities as it is able to locate precisely the coronary artery lesions. The dimensions of the stenosis can be assessed nowadays successfully with image processing based Quantitative Coronary Angiography (QCA) techniques. Our purpose is to assess the clinical relevance of the pertinent stenosis. We therefore analyze the myocardial perfusion as revealed in standard angiographic image sequences. In a Region-of-Interest (ROI) on the angiogram (without an overlaying major blood vessel) the contrast is measured as a function of time (the so-called time-density curve). The required hyperemic state of exercise is induced artificially by the injection of a vasodilator drug e.g. papaverine. In order to minimize motion artifacts we select based on the recorded ECG signal end-diastolic images in both a basal and a hyperemic run in the same projection to position the ROI. We present the development of the algorithms together with results of a small study of 20 patients which have been catheterized following the standard protocol.

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