A novel ultrasound indentation system for measuring biomechanical properties of in vivo soft tissue.

Technologies for soft tissue analysis are advancing at a rapid place. For instance, elastography, which provides soft tissue strain images, is starting to be tried in clinical practice as a tool for diagnosing cancer. Soft tissue deformation modeling and analysis is also an active area of research that has application in surgery planning and treatment. Typically, quantitative soft tissue analysis uses nominal values of soft tissue biomechanical properties. However, in practice, soft tissue properties can vary significantly between individuals. Hence, for soft tissue methodologies to reach their full potential as patient-specific techniques, there is a need to develop ways to efficiently measure soft tissue mechanical properties in vivo. This paper describes a prototype real-time ultrasound (US) indentation test system developed to meet this need. The system is based on the integration of a force sensor and an optical tracking system with a commercial US machine integrated with a suite of analysis methodologies. In a study on a single-layer phantom, we used the system to compare various methods of estimating linear elastic properties (via a theoretical approximation, 2-D finite element analysis, 3-D finite element analysis and a standard material-testing method). In a second study on a three-layer gelatin phantom, we describe a new finite-element-based inverse solution for recovering the Young's moduli of each layer to show how the system can estimate properties of internal components of soft tissue. Finally, we show how the system can be used to derive a modified quasilinear viscoelastic (QVL) model on real breast tissue.

Nonrigid registration of 3-D free-hand ultrasound images of the breast.

Three-dimensional (3-D) ultrasound imaging of the breast enables better assessment of diseases than conventional two-dimensional (2-D) imaging. Free-hand techniques are often used for generating 3-D data from a sequence of 2-D slice images. However, the breast deforms substantially during scanning because it is composed primarily of soft tissue. This often causes tissue mis-registration in spatial compounding of multiple scan sweeps. To overcome this problem, in this paper, instead of introducing additional constraints on scanning conditions, we use image processing techniques. We present a fully automatic algorithm for 3-D nonlinear registration of free-hand ultrasound data. It uses a block matching scheme and local statistics to estimate local tissue deformation. A Bayesian regularization method is applied to the sample displacement field. The final deformation field is obtained by fitting a B-spline approximating mesh to the sample displacement field. Registration accuracy is evaluated using phantom data and similar registration errors are achieved with (0.19 mm) and without (0.16 mm) gaps in the data. Experimental results show that registration is crucial in spatial compounding of different sweeps. The execution time of the method on moderate hardware is sufficiently fast for fairly large research studies.