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Cardiovascular cartography - a new non-invasive technique to detect coronary artery disease

机译:心血管制图 - 一种探测冠状动脉疾病的新的非侵入性技术

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A multi-variable mathematical model specific to each individual can be designed to obtain the nominal basal haemodynamic behavior. By superimposing the measured data obtained from the individuals, on a predictive model, a pattern, called cardiovascular cartography (CCG) can be generated. In a pilot study it was observed that Coronary Artery Disease (CAD) characteristically altered the CCG pattern. These alterations were carefully analyzed using artificial neural networks and the exact Status of the coronary insufficiency was reconstructed on a realistic geometry coronary model. A strong correlation was found to exist between functional structures and structural functions. This study was designed to assess the feasibility of using such modeling and cartography techniques to detect the primary presence and assess the severity of CAD.
机译:可以设计针对每个单独的多变量数学模型以获得标称基础血管动力学行为。通过叠加从个体获得的测量数据,在预测模型上,可以生成称为心血管制图(CCG)的图案。在试验研究中,观察到冠状动脉疾病(CAD)特征性地改变了CCG模式。使用人工神经网络仔细分析这些改变,并在现实的几何冠状动脉模型上重建了冠状动脉功能不全的确切状态。发现功能结构和结构功能之间存在强烈的相关性。本研究旨在评估使用这种建模和制图技术检测初次存在并评估CAD的严重程度的可行性。

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