Strain-Based Regional Nonlinear Cardiac Material Properties Estimation From Medical Images

Abstract. Model personalization is essential for model-based surgical planning and treatment assessment. As alteration in material elasticity is a fundamental cause to various cardiac pathologies, estimation of material properties is important to model personalization. Although the myocardium is heterogeneous, hyperelastic, and orthotropic, existing image-based estimation frameworks treat the tissue as either heterogeneous but linear, or hyperelastic but homogeneous. In view of these, we present a physiology-based framework for estimating regional, hyperelastic, and orthotropic material properties. A cardiac physiological model is adopted to describe the macroscopic cardiac physiology. By using a strainbased objective function which properly reflects the change of material constants, the regional material properties of a hyperelastic and orthotropic constitutive law are estimated using derivative-free optimization. Experiments were performed on synthetic and real data to show the characteristics of the framework.

Non-Contact Intracardiac Potential Mapping Using Mesh-Based and Meshless Inverse Solvers

Atrial fibrillation (AF) is the most common cardiac dysrhythmia and percutaneous catheter ablation is widely used to treat it. Panoramic mapping with multi-electrode catheters has been used to identify ablation targets in persistent AF but is limited by poor contact and inadequate coverage of the left atrial cavity. In this paper, we investigate the accuracy with which atrial endocardial surface potentials can be reconstructed from electrograms recorded with non-contact catheters. An in-silico approach was employed in which "ground-truth" surface potentials from experimental contact mapping studies and computer models were compared with inverse potential maps constructed by sampling the corresponding intracardiac field using virtual basket catheters. We demonstrate that it is possible to 1) specify the mixed boundary conditions required for mesh-based formulations of the potential inverse problem fully, and 2) reconstruct accurate inverse potential maps from recordings made with appropriately designed catheters. Accuracy improved when catheter dimensions were increased but was relatively stable when the catheter occupied >30% of atrial cavity volume. Independent of this, the capacity of non-contact catheters to resolve the complex atrial potential fields seen in reentrant atrial arrhythmia depended on the spatial distribution of electrodes on the surface bounding the catheter. Finally, we have shown that reliable inverse potential mapping is possible in near real-time with meshless methods that use the Method of Fundamental Solutions

In vivo Human 3D Cardiac Fibre Architecture: Reconstruction Using Curvilinear Interpolation of Diffusion Tensor Images

In vivo imaging of the cardiac 3D fibre architecture is still a challenge, but it would have many clinical applications, for instance to better understand pathologies and to follow up remodelling after therapy. Recently, cardiac MRI enabled the acquisition of Diffusion Tensor images (DTI) of 2D slices. We propose a method for the complete 3D reconstruction of cardiac fibre architecture in the left ventricular myocardium from sparse in vivo DTI slices. This is achieved in two steps. First we map non-linearly the left ventricular geometry to a truncated ellipsoid. Second, we express coordinates and tensor components in Prolate Spheroidal System, where an anisotropic Gaussian kernel regression interpolation is performed. The framework is initially applied to a statistical cardiac DTI atlas in order to estimate the optimal anisotropic bandwidths. Then, it is applied to in vivo beating heart DTI data sparsely acquired on a healthy subject. Resulting in vivo tensor field shows good correlation with literature, especially the elevation (helix) angle transmural variation. To our knowledge, this is the first reconstruction of in vivo human 3D cardiac fibre structure. Such approach opens up possibilities in terms of analysis of the fibre architecture in patients