Feasibility analysis of a case-based reasoning system for automated detection of coronary heart disease from myocardial scintigrams
Feasibility analysis of a case-based reasoning system for automated detection of coronary heart disease from myocardial scintigrams
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DOI：
10.1016/s0933-3657(96)00361-2
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发表时间：
1997-01-01
影响因子：
7.5
通讯作者：
Porenta, G
中科院分区：
文献类型：
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作者：
Haddad, M;Adlassnig, KP;Porenta, G
心肌灌注闪烁扫描是一种无创诊断方法，用于评估疑似或确诊的冠状动脉疾病 (CAD) 患者。我们利用基于案例的推理 (CBR) 方法开发基于计算机的图像解释系统 SCINA，该系统自动从闪烁扫描图像数据集得出有关 CAD 存在的评估。我们编制了一个包含 100 名患者的病例库，这些患者接受了灌注闪烁扫描和冠状动脉造影，以记录或排除 CAD 的存在。选择检索到的闪烁扫描输入病例的最近邻匹配的血管造影诊断作为 CBR 诊断。我们研究了输入数据粒度、案例索引、相似性度量和适应性对 CBR 应用程序 SCINA 诊断准确性的影响。对于最终原型，检测冠心病的敏感性和特异性分别为 98% 和 70%，这表明 CBR 系统可能达到临床应用可行的诊断准确性。版权所有 (C) 1997 Elsevier Science B.V.
Myocardial perfusion scintigraphy is a noninvasive diagnostic method for the evaluation of patients with suspected or proven coronary artery disease (CAD). We utilized case-based reasoning (CBR) methods to develop the computer-based image interpretation system SCINA which automatically derives from a scintigraphic image data set an assessment concerning 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 was 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 prototype, sensitivity and specificity for detection of coronary heart disease were 98% and 70% suggesting that CBR systems may achieve a diagnostic accuracy that appears feasible for clinical use. Copyright (C) 1997 Elsevier Science B.V.