Material stiffness parameters as potential predictors of presence of left ventricle myocardial infarction: 3D echo-based computational modeling study.
Material stiffness parameters as potential predictors of presence of left ventricle myocardial infarction: 3D echo-based computational modeling study.
复制标题
材料硬度参数作为左心室心肌梗塞存在的潜在预测因子：基于 3D 回波的计算建模研究
DOI：
10.1186/s12938-016-0151-8
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发表时间：
2016-04-05
影响因子：
3.9
通讯作者：
Tang D
中科院分区：
文献类型：
--
作者：
Fan L;Yao J;Yang C;Wu Z;Xu D;Tang D
背景技术在体内条件下难以获得支架材料的性质，并且在当前的文献中不易获得。还期望在推荐更昂贵的检查之前，基于回波数据来初始确定患者是否患有梗塞。一种无创的回声为基础的建模方法和预测方法，以确定左心室的材料参数和区分患者与最近的心肌梗死（MI）从那些没有。MethodsEcho数据从10例患者，5与MI（心肌梗死组）和5没有（非心肌梗死组）。构建基于回波的患者特定计算左心室（LV）模型，以量化LV材料特性。所有患者在建模过程中均得到平等对待，不使用MI信息。调整Mooney-Rivlin模型中的收缩压和舒张压材料参数值，以匹配回波容积数据。通过线性拟合获得每种材料应力-应变曲线的等效杨氏模量（YM）值，以便于比较。预测Logistic回归分析，以确定最佳的参数为infractprediction.ResultsThe LV收缩末期材料硬度（ES-YMf）是最好的单一预测12个参数与受试者工作特征（ROC）曲线下面积为0.9841。左室壁厚度（WT）、收缩末期纤维方向材料刚度（ES-YMf）和材料刚度变异（ES-YMf）与左室射血分数呈正相关，相关系数分别为r = 0.8125、r = 0.9495和r = 0.9619。最佳参数组合WT + BJYMf是最佳的综合预测值，ROC曲线下面积为0.9951。结论计算模型和材料刚度参数可作为一种潜在的工具，根据超声数据提示患者是否有梗死。需要大规模的临床研究来验证这些初步发现。
BackgroundVentricle material properties are difficult to obtain under in vivo conditions and are not readily available in the current literature. It is also desirable to have an initial determination if a patient had an infarction based on echo data before more expensive examinations are recommended. A noninvasive echo-based modeling approach and a predictive method were introduced to determine left ventricle material parameters and differentiate patients with recent myocardial infarction (MI) from those without.MethodsEcho data were obtained from 10 patients, 5 with MI (Infarct Group) and 5 without (Non-Infarcted Group). Echo-based patient-specific computational left ventricle (LV) models were constructed to quantify LV material properties. All patients were treated equally in the modeling process without using MI information. Systolic and diastolic material parameter values in the Mooney-Rivlin models were adjusted to match echo volume data. The equivalent Young’s modulus (YM) values were obtained for each material stress–strain curve by linear fitting for easy comparison. Predictive logistic regression analysis was used to identify the best parameters for infract prediction.ResultsThe LV end-systole material stiffness (ES-YMf) was the best single predictor among the 12 individual parameters with an area under the receiver operating characteristic (ROC) curve of 0.9841. LV wall thickness (WT), material stiffness in fiber direction at end-systole (ES-YMf) and material stiffness variation (∆YMf) had positive correlations with LV ejection fraction with correlation coefficients r = 0.8125, 0.9495 and 0.9619, respectively. The best combination of parameters WT + ∆YMfwas the best over-all predictor with an area under the ROC curve of 0.9951.ConclusionComputational 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.