Prediction Model of Left Ventricle Myocardial Infarction Based on Echo Image Data
Determining ventricle tissue material properties and myocardial infarction(MI)noninvasively based on in vivo image data is of great important in clinical applications.Echo data were obtained form 10 patients.The patients were divided into Group 1(n=5,with infarct)and Group 2(n=5,without infarct).Echo-based patient-specific computational LV models were constructed to quantify LV material properties and identify predictors for presence of infarction.Systolic and diastolic material parameter values were adjusted to match echo volume data.The equivalent Young”s modulus(YM)values were obtained for each material stress-strain curve for easy comparison.LV wall thickness,volume,ejection fraction,diameter,height,material stiffness parameter values,circumferential and longitudinal curvatures,stress and strain values were collected for analysis.Logistic regression analysis was used to identify the best parameters for infract prediction.The LV stiffness in fiber direction at end-systole was the best single predictor among the 12 individual parameters with an area under the ROC of 0.9841.Computational modeling and material stiffness parameters may be used as a potential tool to suggest if a patient had infarction based on echo data.Large-scale clinical studies are needed to validate these preliminary findings.
Tissue material property prediction ventricle model ventricle mechanics left ventricle
Longling Fan Jing Yao Chun Yang Zheyang Wu Di Xu Dalin Tang
Department of Mathematics,Southeast University,Nanjing,210096,China Department of Cardiology,First Affiliated Hospital of Nanjing Medical University,Nanjing 210029,Chin Network Technology Research Institute,China United Network Communications Co.,Ltd.,Beijing,100048,Ch Mathematical Sciences Department,Worcester Polytechnic Institute,MA 01609 USA Department of Mathematics,Southeast University,Nanjing,210096,China;Mathematical Sciences Department
国内会议
南京
英文
1-5
2015-10-16（万方平台首次上网日期，不代表论文的发表时间）