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Dynamic soft tissue deformation estimation based on energy analysi

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Abstract

The needle placement accuracy of millimeters is required in many needle-based surgeries. The tissue deformation, especially that occurring on the surface of organ tissue, affects the needle-targeting accuracy of both manual and robotic needle insertions. It is necessary to understand the mechanism of tissue deformation during needle insertion into soft tissue. In this paper, soft tissue surface deformation is investigated on the basis of continuum mechanics, where a geometry model is presented to quantitatively approximate the volume of tissue deformation. The energy-based method is presented to the dynamic process of needle insertion into soft tissue based on continuum mechanics, and the volume of the cone is exploited to quantitatively approximate the deformation on the surface of soft tissue. The external work is converted into potential, kinetic, dissipated, and strain energies during the dynamic rigid needle-tissue interactive process. The needle insertion experimental setup, consisting of a linear actuator, force sensor, needle, tissue container, and a light, is constructed while an image-based method for measuring the depth and radius of the soft tissue surface deformations is introduced to obtain the experimental data. The relationship between the changed volume of tissue deformation and the insertion parameters is created based on the law of conservation of energy, with the volume of tissue deformation having been obtained using image-based measurements. The experiments are performed on phantom specimens, and an energy-based analytical fitted model is presented to estimate the volume of tissue deformation. The experimental results show that the energy-based analytical fitted model can predict the volume of soft tissue deformation, and the root mean squared errors of the fitting model and experimental data are 0.61 and 0.25 at the velocities 2.50 mm/s and 5.00 mm/s. The estimating parameters of the soft tissue surface deformations are proven to be useful for compensating the needle-targeting error in the rigid needle insertion procedure, especially for percutaneous needle insertion into organs.

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Authors and Affiliations

  1. State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, 310027, China

    Dedong Gao, Yong Lei & Bin Yao

  2. School of Mechanical Engineering, Qinghai University, Xining, 810016, China

    Dedong Gao

  3. School of Mechanical Engineering, Purdue University, West Lafayette, USA

    Bin Yao

Authors
  1. Dedong Gao
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  2. Yong Lei
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  3. Bin Yao
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Corresponding author

Correspondence to Yong Lei.

Additional information

Supported by National Natural Science Foundation of China (Grant No. 51665049, 51165040), Science Fund for Creative Research Groups of National Natural Science Foundation of China (Grant No. 51521064), and Qinghai Provincial Natural Science Foundation of China (Grant No. 2015-ZJ-906)

GAO Dedong, born in 1980, is currently a PhD candidate at State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, China, as well as working as an associate professor at School of Mechanical Engineering, Qinghai University, China. He received his master degree from Tsinghua University, China, in 2007. His research interests include computer simulation and bio-manufacturing.

LEI Yong, born in 1976, is currently an associate professor at State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, China. He received his PhD degree from The University of Michigan, USA, in 2007. His research interests include fault analysis, intelligent maintenance, and precision control.

YAO Bin, received the B.E. degree in applied mechanics from Beihang University, China, in 1987, the M.E. degree in electrical engineering from Nanyang Technological University in 1992, and the Ph.D. degree in mechanical engineering from the University of California, USA, in 1996. Since 1996, he has been with the School of Mechanical Engineering, Purdue University, West Lafayette, IN, where he was promoted to the rank of associate professor in 2002 and professor in 2007. He was honored as a Kuang-piu Professor in 2005 and a Chang Jiang Chair Professor in 2010 at Zhejiang University, as well. His research interests include the design and control of intelligent high performance coordinated control of electro-mechanical/hydraulic systems, optimal adaptive and robust control, nonlinear observer design and neural networks for virtual sensing, modeling, fault detection, diagnostics, and adaptive fault-tolerant control, and data fusion. He has published significantly on the subjects with well over 150 technical papers while enjoying the application of the theory through industrial consulting.

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Gao, D., Lei, Y. & Yao, B. Dynamic soft tissue deformation estimation based on energy analysi. Chin. J. Mech. Eng. 29, 1167–1175 (2016). https://doi.org/10.3901/CJME.2016.0909.111

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  • DOI: https://doi.org/10.3901/CJME.2016.0909.111

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