Advanced search
Publication Cover
Computer Assisted Surgery Volume 24, 2019 - Issue sup1: Advances in Minimally Invasive Surgery and Clinical Measurement. Guest Editors: Chengyu Liu & Lung-kwang Pan
Submit an article Journal homepage
1,596
Views
5
CrossRef citations to date
0
Altmetric
Research Article

Modeling of soft tissue thermal damage based on GPU acceleration

Jinao ZhangSchool of Engineering, RMIT University, Bundoora, Australia;
,
Jeremy HillsSchool of Engineering, RMIT University, Bundoora, Australia;
,
Yongmin ZhongSchool of Engineering, RMIT University, Bundoora, Australia; Correspondence[email protected]
,
Bijan ShirinzadehRobotics and Mechatronics Research Laboratory, Department of Mechanical and Aerospace Engineering, Monash University, Clayton, Australia;
,
Julian SmithDepartment of Surgery, School of Clinical Sciences at Monash Health, Monash University, Clayton, Australia;
&
Chengfan GuCity of Whittlesea, Mill Park, Australia
Pages 5-12 | Published online: 24 Jul 2019

References

  • Kok H, Kotte A, Crezee J. Planning, optimisation and evaluation of hyperthermia treatments. Int J Hyperthermia. 2017;33:593–607.
  • Zhang J, Zhong Y, Gu C. Deformable models for surgical simulation: a survey. IEEE Rev Biomed Eng. 2018;11:143–164.
  • Zhang J, Zhong Y, Smith J, et al. ChainMail based neural dynamics modeling of soft tissue deformation for surgical simulation. Technol Health Care. 2017;25:231–239.
  • Lopresto V, Pinto R, Farina L, et al. Treatment planning in microwave thermal ablation: clinical gaps and recent research advances. Int J Hyperthermia. 2017;33:83–100.
  • Prakash P. Theoretical modeling for hepatic microwave ablation. Open Biomed Eng J. 2010;4:27–38.
  • Shen W, Zhang J, Yang F. Modeling and numerical simulation of bioheat transfer and biomechanics in soft tissue. Math Comput Modell. 2005;41:1251–1265.
  • Li X, Zhong Y, Subic A, et al. Prediction of tissue thermal damage. Technol Health Care. 2016;24 Suppl 2:S625–S629.
  • Li X, Zhong Y, Jazar R, et al. Thermal-mechanical deformation modelling of soft tissues for thermal ablation. Biomed Mater Eng. 2014;24:2299–2310.
  • Prakash P, Diederich CJ. Considerations for theoretical modelling of thermal ablation with catheter-based ultrasonic sources: implications for treatment planning, monitoring and control. Int J Hyperthermia. 2012;28:69–86.
  • Wang Z, Aarya I, Gueorguieva M, et al. Image-based 3D modeling and validation of radiofrequency interstitial tumor ablation using a tissue-mimicking breast phantom. Int J Cars. 2012;7:941–948.
  • Rattanadecho P, Keangin P. Numerical study of heat transfer and blood flow in two-layered porous liver tissue during microwave ablation process using single and double slot antenna. Int J Heat Mass Transf. 2013;58:457–470.
  • Watanabe H, Kobayashi Y, Hashizume M, et al. Modeling the temperature dependence of thermophysical properties: study on the effect of temperature dependence for RFA. Conf Proc IEEE Eng Med Biol Soc. 2009;2009:5100–5105.
  • Mariappan P, Weir P, Flanagan R, et al. GPU-based RFA simulation for minimally invasive cancer treatment of liver tumours. Int J Cars. 2017;12:59–68.
  • Kröger T, Altrogge I, Preusser T, et al. Numerical simulation of radio frequency ablation with state dependent material parameters in three space dimensions. Berlin, Heidelberg: Springer Berlin Heidelberg; 2006.
  • Rieder C, Kröger T, Schumann C, et al. GPU-based real-time approximation of the ablation zone for radiofrequency ablation. IEEE Trans Vis Comput Graph. 2011;17:1812–1821.
  • Borsic A, Hoffer E, Attardo EA. GPU-accelerated real time simulation of radio frequency ablation thermal dose. 2014 40th Annual Northeast Bioengineering Conference (Nebec); Boston, MA: IEEE; 2014: p. 1–2.
  • Chen G, Stang J, Haynes M, et al. Real-time three-dimensional microwave monitoring of interstitial thermal therapy. IEEE Trans Biomed Eng. 2018;65:528–538.
  • Pennes HH. Analysis of tissue and arterial blood temperatures in the resting human forearm. J Appl Physiol. 1948;1:93–122.
  • Zhang J, Zhong Y, Smith J, et al. Cellular neural network modelling of soft tissue dynamics for surgical simulation. Technol Health Care. 2017;25:337–344.
  • Zhang JN, Zhong YM, Gu CF. Energy balance method for modelling of soft tissue deformation. Comput-Aided Desi. 2017;93:15–25.
  • Zhang J, Zhong Y, Smith J, et al. Energy propagation modeling of nonlinear soft tissue deformation for surgical simulation. Simulation 2018;94:3–10.
  • Zhang J, Zhong Y, Smith J, et al. Neural dynamics-based Poisson propagation for deformable modelling. Neural Comput Appl. 2019;31:1091–1101.
  • Xu F, Lu TJ, Seffen KA. Biothermomechanics of skin tissues. J Mech Phys Solids. 2008;56:1852–1884.
  • Zhang J, Zhong Y, Gu C. Ellipsoid bounding region-based ChainMail algorithm for soft tissue deformation in surgical simulation. Int J Interact Des Manuf. 2018;12:903–918.
  • Zhang J, Zhong Y, Smith J, et al. A new ChainMail approach for real-time soft tissue simulation. Bioengineered 2016;7:246–252.
  • Zhang J, Zhong Y, Gu C. Soft tissue deformation modelling through neural dynamics-based reaction-diffusion mechanics. Med Biol Eng Comput. 2018;12:2163–2176.
  • Zhang J, Shin J, Zhong Y, et al. Heat conduction-based methodology for nonlinear soft tissue deformation. Int J Interactive Des Manufacturing. 2018;13:147–161.

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.