| description abstract | Methods to quantify ventricle material properties noninvasively using in vivo data are of great important in clinical applications. An ultrasound echobased computational modeling approach was proposed to quantify left ventricle (LV) material properties, curvature, and stress/strain conditions and find differences between normal LV and LV with infarct. Echo image data were acquired from five patients with myocardial infarction (IGroup) and five healthy volunteers as control (HGroup). Finite element models were constructed to obtain ventricle stress and strain conditions. Material stiffening and softening were used to model ventricle active contraction and relaxation. Systolic and diastolic material parameter values were obtained by adjusting the models to match echo volume data. Young's modulus (YM) value was obtained for each material stress–strain curve for easy comparison. LV wall thickness, circumferential and longitudinal curvatures (Cand Lcurvature), material parameter values, and stress/strain values were recorded for analysis. Using the mean value of HGroup as the base value, at enddiastole, IGroup mean YM value for the fiber direction stress–strain curve was 54% stiffer than that of HGroup (136.24 kPa versus 88.68 kPa). At endsystole, the mean YM values from the two groups were similar (175.84 kPa versus 200.2 kPa). More interestingly, HGroup endsystole mean YM was 126% higher that its enddiastole value, while IGroup endsystole mean YM was only 29% higher that its enddiastole value. This indicated that HGroup had much greater systole–diastole material stiffness variations. At beginningofejection (BE), LV ejection fraction (LVEF) showed positive correlation with Ccurvature, stress, and strain, and negative correlation with LV volume, respectively. At beginningoffilling (BF), LVEF showed positive correlation with Ccurvature and strain, but negative correlation with stress and LV volume, respectively. Using averaged values of two groups at BE, IGroup stress, strain, and wall thickness were 32%, 29%, and 18% lower (thinner), respectively, compared to those of HGroup. Lcurvature from IGroup was 61% higher than that from HGroup. Difference in Ccurvature between the two groups was not statistically significant. Our results indicated that our modeling approach has the potential to determine in vivo ventricle material properties, which in turn could lead to methods to infer presence of infarct from LV contractibility and material stiffness variations. Quantitative differences in LV volume, curvatures, stress, strain, and wall thickness between the two groups were provided. | |
