On the differences between two-dimensional and three-dimensional simulations for assessing elastographic image quality: a simulation study

Ultrasound Med Biol. 2008 Jul;34(7):1129-38. doi: 10.1016/j.ultrasmedbio.2007.12.007. Epub 2008 Mar 14.

Abstract

In this work, we introduced an elastographic simulation framework, which estimates upper bounds on elastographic image quality by accounting for three-dimensional (3D) tissue motion and the 3D nature of the ultrasound beam. For the boundary conditions and the range of applied strains considered in this study, it was observed that for applied strains smaller than 0.7%, fast two-dimensional (2D) simulations and 3D simulations predicted similar upper bounds on elastographic signal-to-noise (SNR(e)) and contrast-to-noise ratios (CNR(e)); however, for applied strains greater than 0.7%, the predictions by 2D simulations grossly overestimated the achievable results when compared with upper bound results from 3D simulations. It was also found that linear increments in the elevational-to-lateral beamwidth ratio (beam ratio) resulted in nonlinear degradation in the achievable upper bounds on elastographic signal-to-noise ratio. For the modulus contrast ratio of ten between the target and the background, the peak difference in the prediction of contrast-to-noise by 2D and 3D simulations was approximately 10 dB, whereas, for modulus contrast ratio of 1.5, the peak difference increased to approximately 30 dB. No significant difference was observed between the spatial resolution predicted by 2D and 3D simulations; however, increase in beam ratio resulted in decrease in target detectability, especially at lower modulus contrast ratios.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Elasticity Imaging Techniques / methods*
  • Finite Element Analysis
  • Humans
  • Image Interpretation, Computer-Assisted / methods*
  • Imaging, Three-Dimensional / methods
  • Models, Biological
  • Phantoms, Imaging
  • Signal Processing, Computer-Assisted
  • Stress, Mechanical