@Article{cmes.2018.114.221, AUTHOR = {Longling Fan, Jing Yao , Chun Yang, Di Xu, Dalin Tang}, TITLE = {Patient-Specific Echo-Based Fluid-Structure Interaction Modeling Study of Blood Flow in the Left Ventricle with Infarction and Hypertension}, JOURNAL = {Computer Modeling in Engineering \& Sciences}, VOLUME = {114}, YEAR = {2018}, NUMBER = {2}, PAGES = {221--237}, URL = {http://www.techscience.com/CMES/v114n2/33262}, ISSN = {1526-1506}, ABSTRACT = {Understanding cardiac blood flow behaviors is of importance for cardiovascular research and clinical assessment of ventricle functions. Patient-specific Echo-based left ventricle (LV) fluid-structure interaction (FSI) models were introduced to perform ventricle mechanical analysis, investigate flow behaviors, and evaluate the impact of myocardial infarction (MI) and hypertension on blood flow in the LV. Echo image data were acquired from 3 patients with consent obtained: one healthy volunteer (P1), one hypertension patient (P2), and one patient who had an inferior and posterior myocardial infarction (P3). The nonlinear Mooney-Rivlin model was used for ventricle tissue with material parameter values chosen to match echo-measure LV volume data. Using the healthy case as baseline, LV with MI had lower peak flow velocity (30% lower at begin-ejection) and hypertension LV had higher peak flow velocity (16% higher at begin-filling). The vortex area (defined as the area with vorticity>0) for P3 was 19% smaller than that of P1. The vortex area for P2 was 12% smaller than that of P1. At peak of filling, the maximum flow shear stress (FSS) for P2 and P3 were 390% higher and 63% lower than that of P1, respectively. Meanwhile, LV stress and strain of P2 were 41% and 15% higher than those of P1, respectively. LV stress and strain of P3 were 36% and 42% lower than those of P1, respectively. In conclusion, FSI models could provide both flow and structural stress/strain information which would serve as the base for further cardiovascular investigations related to disease initiation, progression, and treatment strategy selections. Large-scale studies are needed to validate our findings.}, DOI = {10.3970/cmes.2018.114.221} }