Model-based analysis of myocardial strain data acquired by tissue Doppler imaging

Summary 

Objective

Tissue Doppler imaging (TDI) is commonly used to evaluate regional ventricular contraction properties through the analysis of myocardial strain. During the clinical examination, a set of strain signals is acquired concurrently at different locations. However, the joint interpretation of these signals remains difficult. This paper proposes a model-based approach in order to assist the clinician in making an analysis of myocardial strain.

Methods and materials

The proposed method couples a model of the left ventricle, which takes into account cardiac electrical, mechanical and hydraulic activities with an adapted identification algorithm, in order to obtain patient-specific model representations. The proposed model presents a tissue-level resolution, adapted to TDI strain analysis. The method is applied in order to reproduce TDI strain signals acquired from two healthy subjects and a patient presenting with dilated cardiomyopathy (DCM).

Results

The comparison between simulated and experimental strains for the three subjects reflects a satisfying adaptation of the model on different strain morphologies. The mean error between real and synthesized signals is equal to 2.34% and 2.09%, for the two healthy subjects and 1.30% for the patient suffering from DCM. Identified parameters show significant electrical conduction and mechanical activation delays for the pathologic case and have shown to be useful for the localization of the failing myocardial segments, which are situated on the anterior and lateral walls of the ventricular base.

Conclusion

The present study shows the feasibility of a model-based method for the analysis of TDI strain signals. The identification of delayed segments in the pathologic case produces encouraging results and may represent a way to better utilize the information included in strain signals and to improve the therapy assistance.

Keywords: Biomedical systems modeling, Biomedical model simulation, Model-based interpretation, Echocardiography