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Proceedings Paper

Automated myocardial perfusion from coronary x-ray angiography
Author(s): Corstiaan J. Storm; Cornelis H. Slump
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Paper Abstract

The purpose of our study is the evaluation of an algorithm to determine the physiological relevance of a coronary lesion as seen in a coronary angiogram. The aim is to extract as much as possible information from a standard coronary angiogram to decide if an abnormality, percentage of stenosis, as seen in the angiogram, results in physiological impairment of the blood supply of the region nourished by the coronary artery. Coronary angiography, still the golden standard, is used to determine the cause of angina pectoris based on the demonstration of an important stenose in a coronary artery. Dimensions of a lesion such as length and percentage of narrowing can at present easily be calculated by using an automatic computer algorithm such as Quantitative Coronary Angiography (QCA) techniques resulting in just anatomical information ignoring the physiological relevance of the lesion. In our study we analyze myocardial perfusion images in standard coronary angiograms in rest and in artificial hyperemic phases, using a drug e.g. papaverine intracoronary. Setting a Region of Interest (ROI) in the angiogram without overlying major vessels makes it possible to calculate contrast differences as a function of time, so called time-density curves, in the basal and hyperemic phases. In minimizing motion artifacts, end diastolic images are selected ECG based in basal and hyperemic phase in an identical ROI in the same angiographic projection. The development of new algorithms for calculating differences in blood supply in the region as set are presented together with the results of a small clinical case study using the standard angiographic procedure.

Paper Details

Date Published: 9 March 2010
PDF: 12 pages
Proc. SPIE 7624, Medical Imaging 2010: Computer-Aided Diagnosis, 76242S (9 March 2010); doi: 10.1117/12.840018
Show Author Affiliations
Corstiaan J. Storm, Ziekenhuis Walcheren (Netherlands)
Cornelis H. Slump, Univ. Twente (Netherlands)

Published in SPIE Proceedings Vol. 7624:
Medical Imaging 2010: Computer-Aided Diagnosis
Nico Karssemeijer; Ronald M. Summers, Editor(s)

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