Automated assessment of dipyridamole 201Tl myocardial SPECT perfusion scintigraphy by case-based reasoning

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.

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.

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).

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.