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首页> 外文期刊>Artificial intelligence in medicine >Automated assessment of myocardial SPECT perfusion scintigraphy: A comparison of different approaches of case-based reasoning
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Automated assessment of myocardial SPECT perfusion scintigraphy: A comparison of different approaches of case-based reasoning

机译：心肌SPECT灌注闪烁显像的自动评估：基于案例的推理的不同方法的比较

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Objective: This study compared the diagnostic accuracy of different approaches of case-based reasoning (CBR) for the assessment of coronary artery disease (CAD) using thallium-201 myocardial perfusion scintigraphy in comparison with coronary angiography. Methods and material: For each scintigraphic image set, regional myocardial tracer uptake was obtained by polar map analysis. CBR algorithms based on a similarity measure were employed to identify similar scintigraphic images within the case library, where each case contained the scintigraphic data together with results of coronary angiography. The angiographic data of retrieved cases were then used to determine whether significant CAD was present in one of the major coronary arteries. Three different approaches of CBR were compared: (1) case retrieval based on a global comparison of polar map data (GLOB), (2) case retrieval based on a territorial comparison of polar map data (TER), and (3) case retrieval based on a comparison of a given case with eight sub-libraries classified according to the involvement of the three major coronary vessels using a group similarity measure (GROUP). Two matching algorithms the best-match approach and an adapted retrieving approach were combined with all three case retrieval methods and their influence on the diagnostic accuracy were investigated. Results: For overall detection of significant CAD, the best-match approach of both TER and GROUP retrieval methods showed a higher diagnostic accuracy than the GLOB retrieval method (75% and 77% versus 70%, respectively). ROC analysis for the adapted retrieving approach showed a similar diagnostic accuracy for all three methods with an area under the curve of 0.79, 0.8, and 0.8 for GLOB, TER, and GROUP, respectively. Conclusion: The observed improvement in the diagnostic accuracy by the new approaches may lead to further improvements of CBR systems, which have the potential to offer valuable decision support for human readers, especially for less experienced investigators.
机译：目的：本研究比较了采用201 201心肌灌注闪烁显像技术与冠状动脉造影技术进行病例案例推理（CBR）评估冠状动脉疾病（CAD）的不同方法的诊断准确性。方法和材料：对于每个闪烁图像集，通过极谱图分析获得局部心肌示踪剂摄取。采用基于相似性度量的CBR算法来识别病例库中的相似闪烁图像，其中每个病例都包含闪烁数据和冠状动脉造影结果。然后使用检索到的病例的血管造影数据确定主要冠状动脉之一中是否存在明显的CAD。比较了三种不同的CBR方法：（1）基于极图数据（GLOB）全局比较的案例检索；（2）基于极图数据（TER）的地域比较的案例检索；（3）案例检索基于给定病例的比较，并使用组相似性度量（GROUP）根据三个主要冠状动脉的参与程度将其归类为八个子库。将两种匹配算法，最佳匹配方法和自适应检索方法与所有三种案例检索方法相结合，并研究了它们对诊断准确性的影响。结果：对于整体检测重要的CAD，TER和GROUP检索方法的最佳匹配方法显示出比GLOB检索方法更高的诊断准确性（分别为75％和77％对70％）。自适应检索方法的ROC分析显示，对于这三种方法，其GLOB，TER和GROUP的曲线下面积分别为0.79、0.8和0.8，具有相似的诊断准确性。结论：通过新方法观察到的诊断准确性的提高可能会导致CBR系统的进一步改进，这有可能为人类读者（尤其是经验不足的研究人员）提供有价值的决策支持。

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