Predicting Target Displacements Using Ultrasound Elastography and Finite Element Modeling

Soft tissue displacements during minimally invasive surgical procedures may cause target motion and subsequent misplacement of the surgical tool. A technique is presented to predict target displacements using a combination of ultrasound elastography and finite element (FE) modeling. A cubic gelatin/agar phantom with stiff targets was manufactured to obtain pre- and post-loading ultrasound radio frequency (RF) data from a linear array transducer. The RF data were used to compute displacement and strain images, from which the distribution of elasticity was reconstructed using an inverse FE-based approach. The FE model was subsequently used to predict target displacements upon application of different boundary and loading conditions to the phantom. The influence of geometry was investigated by application of the technique to a breast-shaped phantom. The distribution of elasticity in the phantoms as determined from the strain distribution agreed well with results from mechanical testing. Upon application of different boundary and loading conditions to the cubic phantom, the FE model-predicted target motion were consistent with ultrasound measurements. The FE-based approach could also accurately predict the displacement of the target upon compression and indentation of the breast-shaped phantom. This study provides experimental evidence that organ geometry and boundary conditions surrounding the organ are important factors influencing target motion. In future work, the technique presented in this paper could be used for preoperative planning of minimally invasive surgical interventions.

[1]  Orcun Goksel,et al.  3D Needle-Tissue Interaction Simulation for Prostate Brachytherapy , 2005, MICCAI.

[2]  Andras Lasso,et al.  MRI-Guided Robotic Prostate Biopsy: A Clinical Accuracy Validation , 2010, MICCAI.

[3]  Assad A Oberai,et al.  Quantitative three-dimensional elasticity imaging from quasi-static deformation: a phantom study , 2009, Physics in medicine and biology.

[4]  Kenneth Y. Goldberg,et al.  Sensorless Motion Planning for Medical Needle Insertion in Deformable Tissues , 2009, IEEE Transactions on Information Technology in Biomedicine.

[5]  M. Doyley,et al.  Evaluation of an iterative reconstruction method for quantitative elastography , 2000 .

[6]  T. Belytschko,et al.  A comparative study on finite element methods for dynamic fracture , 2008 .

[7]  Allison M. Okamura,et al.  Modeling of Tool-Tissue Interactions for Computer-Based Surgical Simulation: A Literature Review , 2008, PRESENCE: Teleoperators and Virtual Environments.

[8]  C T Lancée,et al.  Intravascular elasticity imaging using ultrasound: feasibility studies in phantoms. , 1997, Ultrasound in medicine & biology.

[9]  Makoto Yamakawa,et al.  Tissue Elasticity Reconstruction Based on 3-Dimensional Finite-Element Model , 1999 .

[10]  F. Kallel,et al.  A Least-Squares Strain Estimator for Elastography , 1997, Ultrasonic imaging.

[11]  E. Deurloo,et al.  Displacement of Breast Tissue and Needle Deviations During Stereotactic Procedures , 2001, Investigative radiology.

[12]  R. Stock,et al.  Current topics in the treatment of prostate cancer with low-dose-rate brachytherapy. , 2010, The Urologic clinics of North America.

[13]  Benjamin Castaneda,et al.  US elastography of breast and prostate lesions. , 2009, Radiographics : a review publication of the Radiological Society of North America, Inc.

[14]  Guy Cloutier,et al.  Ultrasound dynamic micro-elastography applied to the viscoelastic characterization of soft tissues and arterial walls. , 2010, Ultrasound in medicine & biology.

[15]  Richard G P Lopata,et al.  Comparison of one-dimensional and two-dimensional least-squares strain estimators for phased array displacement data. , 2009, Ultrasonic imaging.

[16]  Rajni V. Patel,et al.  Needle insertion into soft tissue: a survey. , 2007, Medical engineering & physics.

[17]  C. D. de Korte,et al.  Performance evaluation of methods for two-dimensional displacement and strain estimation using ultrasound radio frequency data. , 2009, Ultrasound in medicine & biology.

[18]  Jingfeng Jiang,et al.  Elastic nonlinearity imaging , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[19]  T. Helbich,et al.  Accuracy of ultrasound-guided, large-core needle breast biopsy , 2008, European Radiology.

[20]  J. Schnabel,et al.  Factors influencing the accuracy of biomechanical breast models. , 2006, Medical physics.

[21]  J. Ophir,et al.  Elastography: A Quantitative Method for Imaging the Elasticity of Biological Tissues , 1991, Ultrasonic imaging.

[22]  J. Bishop,et al.  MR validation of soft tissue mimicing phantom deformation as modeled by nonlinear finite element analysis. , 2001, Medical physics.

[23]  C. D. de Korte,et al.  Comparison of One-Dimensional and Two-Dimensional Least-Squares Strain Estimators for Phased Array Displacement Data , 2009 .

[24]  Septimiu E. Salcudean,et al.  Interactive simulation of needle insertion models , 2005, IEEE Transactions on Biomedical Engineering.

[25]  K J Macura,et al.  The importance of organ geometry and boundary constraints for planning of medical interventions. , 2009, Medical engineering & physics.

[26]  Jeon-Hor Chen,et al.  Computational simulation of breast compression based on segmented breast and fibroglandular tissues on magnetic resonance images , 2010, Physics in medicine and biology.

[27]  Helmut Ermert,et al.  Ultrasonic strain imaging and reconstructive elastography for biological tissue. , 2006, Ultrasonics.

[28]  Margaret M Szabunio,et al.  Elastography for the characterization of breast lesions: initial clinical experience. , 2010, Cancer control : journal of the Moffitt Cancer Center.

[29]  Maud Marchal,et al.  Modeling of Needle-Tissue Interaction Using Ultrasound-Based Motion Estimation , 2007, MICCAI.

[30]  A F van der Steen,et al.  Elastic and Acoustic Properties of Vessel Mimicking Material for Elasticity Imaging , 1997, Ultrasonic imaging.

[31]  Peter Kazanzides,et al.  Robotic assistance for ultrasound-guided prostate brachytherapy , 2008, Medical Image Anal..

[32]  Assad A. Oberai,et al.  INVERSE PROBLEMS PII: S0266-5611(03)54272-1 Solution of inverse problems in elasticity imaging using the adjoint method , 2003 .

[33]  Werner A Kaiser,et al.  MRI‐guided interventions of the breast , 2008, Journal of magnetic resonance imaging : JMRI.

[34]  H. Lam,et al.  Minimally invasive technology in the management of breast disease , 2009, Breast cancer.

[35]  V. Kouloulias,et al.  Brachytherapy for Prostate Cancer: A Systematic Review , 2009, Advances in urology.

[36]  Arjan Bel,et al.  Finite element based bladder modeling for image-guided radiotherapy of bladder cancer. , 2010, Medical physics.

[37]  Faouzi Kallel,et al.  Tissue elasticity reconstruction using linear perturbation method , 1996, IEEE Trans. Medical Imaging.

[38]  Henkjan J. Huisman,et al.  3D Cardiac Segmentation Using Temporal Correlation of Radio Frequency Ultrasound Data , 2009, MICCAI.