Biomedical subjects

Kevin F Augenstein

Publications and source records attributed to Kevin F Augenstein.

3 recordsLinked to original sources

PubMed2005

Parameter distribution models for estimation of population based left ventricular deformation using sparse fiducial markers.

We present a method to estimate left ventricular (LV) motion based on three-dimensional (3-D) images that can be derived from any anatomical tomographic or 3-D modality, such as echocardiography, computed tomography, or magnetic resonance imaging. A finite element mesh of the LV was constructed to fit the geometry of the wall. The mesh was deformed by optimizing the nodal parameters to the motion of a sparse number of fiducial markers that were manually tracked in the images through the cardiac cycle. A parameter distribution model (PDM) of LV deformations was obtained from a database of MR tagging studies. This was used to filter the calculated deformation and incorporate a priori information on likely motions. The estimated deformation obtained from 13 normal untagged studies was compared with the deformation obtained from MR tagging. The end systolic (ES) circumferential and longitudinal strain values matched well with a mean difference of 0.1 +/- 3.2% and 0.3 +/- 3.0%, respectively. The calculated apex-base twist angle at ES had a mean difference of 1.0 +/- 2.3 degrees. We conclude that fiducial marker fitting in conjunction with a PDM provides accurate reconstruction of LV deformation in normal subjects.

Adult↗

PubMed2005

Method and apparatus for soft tissue material parameter estimation using tissue tagged Magnetic Resonance Imaging.

We describe an experimental method and apparatus for the estimation of constitutive parameters of soft tissue using Magnetic Resonance Imaging (MRI), in particular for the estimation of passive myocardial material properties. MRI tissue tagged images were acquired with simultaneous pressure recordings, while the tissue was cyclically deformed using a custom built reciprocating pump actuator A continuous three-dimensional (3D) displacement field was reconstructed from the imaged tag motion. Cavity volume changes and local tissue microstructure were determined from phase contrast velocity and diffusion tensor MR images, respectively. The Finite Element Method (FEM) was used to solve the finite elasticity problem and obtain the displacement field that satisfied the applied boundary conditions and a given set of material parameters. The material parameters which best fit the FEM predicted displacements to the displacements reconstructed from the tagged images were found by nonlinear optimization. The equipment and method were validated using inflation of a deformable silicon gel phantom in the shape of a cylindrical annulus. The silicon gel was well described by a neo-Hookian material law with a single material parameter C1=8.71+/-0.06kPa, estimated independently using a rotational shear apparatus. The MRI derived parameter was allowed to vary regionally and was estimated as C1 =8.80+/-0.86kPa across the model. Preliminary results from the passive inflation of an isolated arrested pig heart are also presented, demonstrating the feasibility of the apparatus and method for isolated heart preparations. FEM based models can therefore estimate constitutive parameters accurately and reliably from MRI tagging data.

Algorithms↗

PubMed2004

Extraction and quantification of left ventricular deformation modes.

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.

Adult↗