Porenta G, Dorffner G, Kundrat S, Petta P, Duit-Schedlmayer J, Sochor H
Department of Cardiology, University of Vienna Medical School, Austria.
J Nucl Med. 1994 Dec;35(12):2041-7.
To develop an automated image interpretation system of planar cardiac 201Tl dipyridamole stress/redistribution scintigrams, the authors used artificial neural networks that associate patterns of segmental myocardial thallium uptake with a diagnostic assessment about the presence, severity and localization of significant coronary artery disease.
Artificial neural networks were trained and evaluated using the results from segmental thallium analysis and either expert readings in 159 cases or coronary angiography in a subgroup of 81 patients.
Based on receiver operating characteristics analysis, the sensitivity for the detection of significant coronary artery disease at a specificity of 90% was 51% compared with angiography and 72% compared with the human expert. For severity and localization of disease, two vascular territories assigned to the vascular bed of the left anterior descending (LAD) artery and to the territory subtended by the left circumflex artery and the right coronary artery together (CX/RCA) were included in the analysis.
Artificial neural networks may be useful to develop automated computer-based image interpretation systems of 201Tl perfusion scintigrams. However, utilization of large training datasets appears to be a prerequisite to achieve adequate diagnostic performance.
为开发一种平面心脏201铊双嘧达莫负荷/再分布闪烁扫描图的自动图像解读系统，作者使用了人工神经网络，该网络将节段性心肌铊摄取模式与关于显著冠状动脉疾病的存在、严重程度和定位的诊断评估相关联。
使用节段性铊分析结果以及159例病例中的专家解读或81例患者亚组中的冠状动脉造影结果对人工神经网络进行训练和评估。
基于受试者工作特征分析，在特异性为90%时，与冠状动脉造影相比，检测显著冠状动脉疾病的敏感性为51%，与人类专家相比为72%。对于疾病的严重程度和定位，分析中包括了分配给左前降支（LAD）动脉血管床以及左旋支动脉和右冠状动脉共同覆盖区域（CX/RCA）的两个血管区域。
人工神经网络可能有助于开发基于计算机的201铊灌注闪烁扫描图自动图像解读系统。然而，使用大型训练数据集似乎是实现足够诊断性能的先决条件。
