A clinically applicable strategy to estimate the in vivo distribution of mechanical material properties of the right ventricular wall

A clinically applicable approach to estimate the in vivo mechanical material properties of the heart wall is presented. This optimization‐based inverse estimation approach applies a shape‐based objective functional combined with rigid body registration and incremental parameterization of heterogeneity to use standard clinical imaging data along with simplified representations of cardiac function to provide consistent and physically meaningful solution estimates. The capability of the inverse estimation algorithm is evaluated through application to two clinically obtained human datasets to estimate the passive elastic mechanical properties of the heart wall, with an emphasis on the right ventricle. One dataset corresponded to a subject with normal heart function, while the other corresponded to a subject with severe pulmonary hypertension, and therefore expected to have a substantially stiffer right ventricle. Patient‐specific pressure‐driven bi‐ventricle finite element analysis was used as the forward model and the endocardial surface of the right ventricle was used as the target data for the inverse problem. By using the right ventricle alone as the target of the inverse problem the relative sensitivity of the objective function to the right ventricle properties is increased. The method was able to identify material properties to accurately match the corresponding shape of the simplified forward model to the clinically obtained target data, and the properties obtained for the example cases are consistent with the clinical expectation for the right ventricle. Additionally, the material property estimates indicate significant heterogeneity in the heart wall for both subjects, and more so for the subject with pulmonary hypertension. An approach is presented using a shape‐based objective functional combined with registration and incremental parameterization to use standard clinical imaging data along with simplified representations of cardiac function to provide consistent and physically meaningful estimates of mechanical heart wall properties. The method was able to identify material properties to accurately match the corresponding heart shape of clinically obtained target data, and the properties obtained for the example cases are consistent with the clinical expectation for the right ventricle.