2 results for Augenstein, KF

  • Estimation of Cardiac Hyperelastic Material Properties from MRI Tissue Tagging and Diffusion Tensor Imaging

    Augenstein, KF; Cowan, Brett; Le Grice, Ian; Young, Alistair (2006)

    Journal article
    The University of Auckland Library

    The passive material properties of myocardium are important in the understanding of diastolic cardiac dysfunction. We determined hyperelastic myocardial material parameters in four isolated arrested pig hearts undergoing passive inflation of the left ventricle. Using geometry from MRI, recorded boundary conditions, muscle fiber architecture from diffusion tensor imaging, and deformation from tissue tagging, finite element models were constructed to solve the finite elasticity stress estimation problem. The constitutive parameters of a hyperelastic transversely isotropic material law were determined by minimizing the difference between the predicted and imaged deformation field. The optimized parameters were in a similar range as those reported by previous studies, showing increased passive stiffness in the muscle fiber direction. The average RMS error was 0.92 mm, similar to the image resolution of 0.80 mm. Optimization of hyperelastic models of myocardial mechanics can thus be performed to extract meaningful biophysical parameters from MRI data.

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  • Extraction and Quantification of Left Ventricular Deformation Modes

    Remme, EW; Young, AA; Augenstein, KF; Cowan, Brett; Hunter, PJ (2004)

    Journal article
    The University of Auckland Library

    We have developed a method that decomposes the deformation of the left ventricle (LV) between end diastole (ED) and end systole (ES) into separate deformation modes such as longitudinal shortening, wall thickening, and twisting. The deformation was initially found from the motion of an LV finite-element mesh that was fitted to clinically obtained magnetic resonance (MR) tagged images. A mode coefficient was calculated for each deformation mode to quantify the different modes and, thus allowing for discrimination of normal and abnormal deformation patterns. We applied the method to 13 normal subjects and 13 diabetes patients. By using the ED mesh as reference and adding the extracted deformation modes multiplied by their mode coefficients, an approximate ES mesh was calculated and compared with the "true" ES mesh found from the MR images. For the 26 subjects the average Euclidean distance was less than 1.7±0.9 mm between the nodes of the approximated and true ES meshes. The coefficient values for the patient group showed significantly less longitudinal shortening, less wall thickening, more longitudinal twisting and also more bulging of the septum into the LV when compared with the normal subjects. We conclude that the developed method successfully quantifies the deformation into several modes of deformation and is capable of distinguishing the deformation of a group of patients from a group of normal subjects.

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