Although coronary arteriography plays a critical role in the evaluation and treatment of patients with heart disease, the conventional visual approach to analysis of coronary arteriograms suffers from substantial variability and may provide poor estimates of coronary lesion functional significance. These limitations have generated considerable interest in automated approaches to the assessment of coronary lesion severity. We report a method of coronary border identification that is based upon graph searching principles and that is applicable to the broad spectrum of angiographic image quality observed clinically. Cine frames from clinical coronary angiograms were optically magnified, digitized, and graded for image quality. Minimal lumen diameters, referenced to catheter size, were derived from automatically-identified coronary borders and compared to those defined using quantitative coronary arteriography (method of Brown et al.) and to observer traced borders. Computer-derived minimal lumen diameters were also compared to intracoronary measurements of coronary vasodilator reserve, a measure of the functional significance of a coronary obstruction. To test the robustness of our border detection method, we compared computer-derived coronary borders to independent standards separately for “good” and “poor” angiographic images. Computer-derived minimal lumen diameters correlated well with quantitative coronary arteriography (r = 0.90, y = 0.99x + 0.17, n = 43) and with vasodilator reserve (r = 0.84, y = 0.69x-0.28, n = 18). The accuracy of computer-identified borders was similar in good and poor quality images. Automated coronary border identification based on graph searching is a robust method that has substantial promise for the evaluation of coronary lesion severity in the clinical setting.
Bibliographical noteFunding Information:
Manuscript received July 27. 1988: revised May 14. 1989. This work was supported by the Specialized Center of Research in Ischemic Heart Disease under Grant HL32295, by the Clinical Investigator Award HL00916. the New Investigator Research Award HL35267 (M. R. John-son), and the Research Career Development Award KO4 HL01290 (D. J. Skorton), all from the National Heart. Lung. and Blood Institute. National Institutes of Health. This work was a150 supported by the U.S. Veterans Administration and the F. E. Ripple Foundation. S. R. Fleagle is with the Department of Electrical and Computer Engineering and the Department of Medicine, University of Iowa, Iowa City, IA 52242. M. R. Johnson, D. J. Skorton. C. W. White, and M. L. Marcus are with the Department of Medicine. University of Iowa. Iowa City. 1A 52242. C. J. Wilbricht is with the Department of Electrical and Computer En- gineering, University of Iowa, Iowa City, IA 52242. R. F. Wilson is with the Department of Medicine. University of Iowa. Iowa City. 1A 52242. S. M. Collins is with the Department of Electrical and Computer En- gineering and the Department of Radiology. University of Iowa. Iowa City. IA 52242. IEEE Log Number 8929508.