HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH RSS TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Figures Only Full Text Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Khorsand, A. Articles by Porenta, G. Search for Related Content PubMed PubMed Citation Articles by Khorsand, A. Articles by Porenta, G.

Automated Assessment of Dipyridamole ²⁰¹Tl Myocardial SPECT Perfusion Scintigraphy by Case-Based Reasoning

Department of Cardiology, University of Vienna, Vienna; and Rudolfinerhaus, Vienna, Austria

This study evaluated the diagnostic accuracy of case-based reasoning (CBR) to automatically detect significant coronary artery disease from dipyridamole ²⁰¹Tl myocardial SPECT perfusion scintigrams. Methods: The study population included 240 patients (182 men, 58 women; mean age ± SD, 61 ± 12 y) on whom coronary angiography and perfusion scintigraphy were performed within 6 ± 11 d of each other. The patients were divided into two groups according to the presence or absence of significant coronary disease in any major coronary vessel. Regional myocardial tracer uptake was observed in 84 segments by polar map analysis. For each scintigraphic image, a CBR algorithm based on a similarity metric was used to identify similar scintigraphic images within the case library. The angiographic results of these similar cases were used to obtain the CBR reading, which was compared with the true angiographic results. Myocardial scintigrams were also analyzed by a first-generation Cedars-Sinai (CS) method, including a comparison with a reference database, and by the visual analysis of an expert reader. Results: By receiver-operating-characteristic analysis, the diagnostic accuracy of CBR was not different from the interpretation by the CS algorithm and from visual interpretation (P = not significant [NS]). For detection of significant coronary disease, the respective sensitivities at 50% and 80% specificity were 90% and 67% for CBR, 88% and 65% for CS polar map analysis, and 91% and 74% for visual interpretation. For the detection of coronary disease in the vascular territories assigned to the left anterior descending and the right coronary arteries, CBR and CS polar map analysis showed similar diagnostic accuracy (P = NS). However, for detection of disease in the circumflex artery, CS polar map analysis was slightly better than CBR (P = 0.03). Conclusion: Automated interpretation of dipyridamole ²⁰¹Tl myocardial SPECT perfusion images by CBR has diagnostic accuracy similar to that of visual interpretation or CS analysis. Thus, use of a case library that includes a variety of normal and abnormal perfusion images does not appear to have greater diagnostic power than use of reference limits.

Key Words: case-based reasoning • myocardial perfusion • dipyridamole • ²⁰¹Tl • SPECT

This article has been cited by other articles:

				J. W. Wallis Use of Artificial Intelligence in Cardiac Imaging J. Nucl. Med., August 1, 2001; 42(8): 1192 - 1194. [Full Text] [PDF]