Cardiac Displacement Tracking with Data Assimilation Combining a Biomechanical Model and an Automatic Contour Detection

Abstract

Data assimilation in computational models represents an essential step in building patient-specific simulations. This work aims at circumventing one major bottleneck in the practical use of data assimilation strategies in cardiac applications, namely, the difficulty of formulating and effectively computing adequate data-fitting term for cardiac imaging such as cine MRI. We here provide a proof-of-concept study of data assimilation based on automatic contour detection. The tissue motion simulated by the data assimilation framework is then assessed with displacements extracted from tagged MRI in six subjects, and the results illustrate the performance of the proposed method, including for circumferential displacements, which are not well extracted from cine MRI alone.

Translational Cardiovascular Modeling: Tetralogy of Fallot and Modeling of Diseases

“…The correction of model by data leads to increasing the patient-specificity of the models, as presented e.g. in [72,73]. The biophysical character then allows to estimate some clinically relevant parameters contributing to a detailed description of physiology state.…”