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首页> 外文会议>International conference on functional imaging and modeling of the heart >Strain-Based Parameters for Infarct Localization: Evaluation via a Learning Algorithm on a Synthetic Database of Pathological Hearts
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Strain-Based Parameters for Infarct Localization: Evaluation via a Learning Algorithm on a Synthetic Database of Pathological Hearts

机译：基于应变的梗塞定位参数：通过病理心脏合成数据库中的学习算法进行评估

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Localization of infarcted regions is essential to determine the most appropriate treatment for patients with cardiac ischemia. Myocar-dial strain partially reflects the location of infarcted regions, which demonstrated potential use in clinical practice. However, strain patterns are complex and simple thresholding is not sufficient to locate the infarcts. Besides, many strain-based parameters exist and their sensitivities to myocardial infarcts have not been directly investigated. In our study, we propose to evaluate nine strain-based parameters to locate infarcted regions. For this purpose, we designed a large database (n = 200) of synthetic pathological finite-element heart models from 5 real healthy left ventricle geometries. The infarcts were incorporated with random location, shape and degree of severity. In addition, we used a state-of-the-art learning algorithm to link deformation patterns and infarct location. Based on our evaluation, we propose to sort the strain-based parameters into three groups according to their performances in locating infarcts.
机译：对于确定心肌缺血患者最合适的治疗方法，梗塞区域的定位至关重要。心肌应变部分反映了梗塞区域的位置，这证明了其在临床实践中的潜在用途。然而，应变模式很复杂，简单的阈值化不足以定位梗塞。此外，存在许多基于应变的参数，尚未直接研究它们对心肌梗塞的敏感性。在我们的研究中，我们建议评估九个基于应变的参数来定位梗塞区域。为此，我们设计了一个大型数据库（n = 200），该数据库由5种真实健康的左心室几何结构构成的合成病理有限元心脏模型。梗死合并有随机的位置，形状和严重程度。此外，我们使用了最新的学习算法来链接变形模式和梗塞位置。根据我们的评估，我们建议根据应变参数在梗死定位中的表现将其分为三类。

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