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1.
Article in English | MEDLINE | ID: mdl-18986950

ABSTRACT

Acoustic radiation force imaging methods distinguish tissue structure and composition by monitoring tissue responses to applied radiation force excitations. Although these responses are a complex, multidimensional function of the geometric and viscoelastic nature of tissue, simplified discrete biomechanical models offer meaningful insight to the physical phenomena that govern induced tissue motion. Applying Voigt and standard linear viscoelastic tissue models, we present a new radiation force technique - monitored steady-state excitation and recovery (MSSER) imaging - that tracks both steady-state displacement during prolonged force application and transient response following force cessation to estimate tissue mechanical properties such as elasticity and viscosity. In concert with shear wave elasticity imaging (SWEI) estimates for Young's modulus, MSSER methods are useful for estimating tissue mechanical properties independent of the applied force magnitude. We test our methods in gelatin phantoms and excised pig muscle, with confirmation through mechanical property measurement. Our results measured 10.6 kPa, 14.7 kPa, and 17.1 kPa (gelatin) and 122.4 kPa (pig muscle) with less than 10% error. This work demonstrates the feasibility of MSSER imaging and merits further efforts to incorporate relevant mechanical tissue models into the development of novel radiation force imaging techniques.


Subject(s)
Algorithms , Elasticity Imaging Techniques/methods , Image Interpretation, Computer-Assisted/methods , Models, Biological , Muscle, Skeletal/diagnostic imaging , Muscle, Skeletal/physiology , Animals , Computer Simulation , Elastic Modulus , Elasticity Imaging Techniques/instrumentation , In Vitro Techniques , Phantoms, Imaging , Stress, Mechanical , Swine , Viscosity
2.
Comput Methods Programs Biomed ; 85(3): 196-202, 2007 Mar.
Article in English | MEDLINE | ID: mdl-17207888

ABSTRACT

The objective of this work was to develop and test a semi-automated finite element mesh generation method using computed tomography (CT) image data of a canine radius. The present study employs a direct conversion from CT Hounsfield units to elastic moduli. Our method attempts to minimize user interaction and eliminate the need for mesh smoothing to produce a model suitable for finite element analysis. Validation of the computational model was conducted by loading the CT-imaged canine radius in four-point bending and using strain gages to record resultant strains that were then compared to strains calculated with the computational model. Geometry-based and uniform modulus voxel-based models were also constructed from the same imaging data set and compared. The nonuniform voxel-based model most accurately predicted the axial strain response of the sample bone (R(2)=0.9764).


Subject(s)
Bone and Bones/diagnostic imaging , Computer Simulation , Finite Element Analysis , Animals , Cadaver , Dogs , North Carolina , Tomography, X-Ray Computed
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