Prostate Tissue Motion Tracking and Ultrasound Elastography Using Tissue Mechanics Derived Constraints
Abstract
Current prostate cancer detection methods can be costly to obtain, such as magnetic resonance imaging, or lack specificity, such as a digital rectal exam. Ultrasound elastography, a method that can be used to develop and test algorithms that output stiffness, strain, and displacement data captured by ultrasound radio frequency readings, offers a potential solution to these challenges. An initial algorithm utilizing dynamic programming and analytic minimization estimates the radial and angular displacements from a pre- and post-compression data set to determine the required material properties. This estimate of displacements is then refined through an algorithm where incompressibility, Laplacian smoothing, and strain compatibility are enforced. The refined displacement field can generate a strain image of the prostate. Material properties such as Young’s modulus, Poisson’s ratio, and shear modulus can be iteratively reconstructed using finite element analysis to enhance the output images further. The material property calculation process, known for its accuracy, yields informative results to clinicians when diagnosing prostate malignancies.