FEASIBILITY ANALYSIS OF A CASE-BASED REASONING SYSTEM FOR AUTOMATED DETECTION OF CORONARY HEART-DISEASE FROM MYOCARDIAL SCINTIGRAMS

Myocardial perfusion scintigraphy is a noninvasive diagnostic method f or the evaluation of patients with suspected or proven coronary artery disease (CAD). We utilized case-based reasoning (CBR) methods to deve lop the computer-based image interpretation system SCINA which automat ically derives from a scintigraphic image data set an assessment conce rning the presence of CAD. We compiled a case library of 100 patients who underwent both perfusion scintigraphy and coronary angiography to document or exclude the presence of CAD. The angiographic diagnosis of the retrieved nearest neighbor match of a scintigraphic input case wa s selected as the CBR diagnosis. We examined the effects of input data granularity, case indexing, similarity metric, and adaptation on the diagnostic accuracy of the CBR application SCINA. For the final protot ype, sensitivity and specificity for detection of coronary heart disea se were 98% and 70% suggesting that CBR systems may achieve a diagnost ic accuracy that appears feasible for clinical use. Copyright (C) 1997 Elsevier Science B.V.