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Numerical Heat Transfer, Part B: Fundamentals
An International Journal of Computation and Methodology
Volume 75, 2019 - Issue 4
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Original Articles

Real-time computation of bio-heat transfer in the fast explicit dynamics finite element algorithm (FED-FEM) framework

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Pages 217-238 | Received 27 Feb 2019, Accepted 31 May 2019, Published online: 13 Jun 2019

References

  • H. P. Kok, A. Kotte, and J. Crezee, “Planning, optimisation and evaluation of hyperthermia treatments,” Int J Hyperthermia, vol. 33, no. 6, pp. 593–607, 2017. DOI:10.1080/02656736.2017.1295323.
  • B. R. Loiola, H. R. Orlande, and G. S. Dulikravich, “Thermal damage during ablation of biological tissues,” Numerical Heat Transfer Part A: Appl., vol. 73, no. 10, pp. 685–701, 2018. DOI:10.1080/10407782.2018.1464794.
  • N. Afrin, and Y. Zhang, “Uncertainty analysis of thermal damage to living biological tissues by laser irradiation based on a generalized duel-phase lag model,” Numer. Heat Transf. Part A Appl., vol. 71, no. 7, pp. 693–706, 2017. DOI:10.1080/10407782.2017.1308714.
  • J. Zhang, Y. Zhong, and C. Gu, “Deformable models for surgical simulation: a survey,” IEEE Rev. Biomed. Eng., vol. 11, pp. 143–164, 2018. DOI:10.1109/RBME.2017.2773521.
  • M. M. Paulides et al., “Simulation techniques in hyperthermia treatment planning,” Int. J. Hyperthermia, vol. 29, no. 4, pp. 346–357, 2013. DOI:10.3109/02656736.2013.790092.
  • V. Lopresto, R. Pinto, L. Farina, and M. Cavagnaro, “Treatment planning in microwave thermal ablation: clinical gaps and recent research advances,” Int. J. Hyperthermia, vol. 33, no. 1, pp. 83–100, 2017. DOI:10.1080/02656736.2016.1214883.
  • H. P. Kok, P. Wust, P. R. Stauffer, F. Bardati, G. C. van Rhoon, and J. Crezee, “Current state of the art of regional hyperthermia treatment planning: a review,” Radiat. Oncol., vol. 10, no. no. 1, pp. 196, 2015.
  • S. C. Wu, G. R. Liu, H. O. Zhang, X. Xu, and Z. R. Li, “A node-based smoothed point interpolation method (NS-PIM) for three-dimensional heat transfer problems,” Int. J. Thermal Sci., vol. 48, no. 7, pp. 1367–1376, 2009. DOI:10.1016/j.ijthermalsci.2008.10.010.
  • K. Yang, G.-H. Jiang, H.-Y. Li, Z-b Zhang, and X.-W. Gao, “Element differential method for solving transient heat conduction problems,” Int. J. Heat Mass Transf., vol. 127, pp. 1189–1197, 2018. DOI:10.1016/j.ijheatmasstransfer.2018.07.155.
  • Z. C. Li, X. Y. Cui, and Y. Cai, “Analysis of heat transfer problems using a novel low-order FEM based on gradient weighted operation,” Int. J. Thermal Sci., vol. 132, pp. 52–64, 2018. DOI:10.1016/j.ijthermalsci.2018.05.039.
  • T. J. Yang, and X. Y. Cui, “A random field model based on nodal integration domain for stochastic analysis of heat transfer problems,” Int. J. Thermal Sci., vol. 122, pp. 231–247, 2017. DOI:10.1016/j.ijthermalsci.2017.08.009.
  • E. Li, G. R. Liu, V. Tan, and Z. C. He, “Modeling and simulation of bioheat transfer in the human eye using the 3D alpha finite element method (αFEM),” Int. J. Numer. Methods Biomed. Eng., vol. 26, no. 8, pp. 955–976, 2010. DOI:10.1002/cnm.1372.
  • E. Li, G. R. Liu, and V. Tan, “Simulation of hyperthermia treatment using the edge-based smoothed finite-element method,” Numer. Heat Transfer Part A Appl., vol. 57, no. 11, pp. 822–847, 2010. DOI:10.1080/10407782.2010.489483.
  • C. Rieder, T. Kroger, C. Schumann, and H. K. Hahn, “GPU-based real-time approximation of the ablation zone for radiofrequency ablation,” IEEE Trans. Vis. Comput. Graph, vol. 17, no. 12, pp. 1812–1821, 2011. DOI:10.1109/TVCG.2011.207.
  • T. Kröger et al., “Numerical simulation of radio frequency ablation with state dependent material parameters in three space dimensions,” Med. Image Comput. Comput. Assisted Interv. – MICCAI, pp. 380–388, 2006.
  • C. W. Huang, M. K. Sun, B. T. Chen, J. Shieh, C. S. Chen, and W. S. Chen, “Simulation of thermal ablation by high-intensity focused ultrasound with temperature-dependent properties,” Ultrason. Sonochem., vol. 27, pp. 456–465, 2015. DOI:10.1016/j.ultsonch.2015.06.003.
  • S. R. Guntur, K. I. Lee, D. G. Paeng, A. J. Coleman, and M. J. Choi, “Temperature-dependent thermal properties of ex vivo liver undergoing thermal ablation,” Ultrasound Med. Biol, vol. 39, no. 10, pp. 1771–1784, 2013. DOI:10.1016/j.ultrasmedbio.2013.04.014.
  • J. Zhang, J. Hills, Y. Zhong, B. Shirinzadeh, J. Smith, and C. Gu, “Temperature-dependent thermomechanical modeling of soft tissue deformation,” J. Mech. Med. Biol., vol. 18, no. 08, pp. 1840021, 2018. DOI:10.1142/S0219519418400213.
  • T. Wegner, and A. Pęczak, “Implementation of a strain energy-based nonlinear finite element in the object-oriented environment,” Comput. Phys. Commun., vol. 181, no. 3, pp. 520–531, 2010. DOI:10.1016/j.cpc.2009.10.027.
  • M. Schwenke, J. Georgii, and T. Preusser, “Fast numerical simulation of focused ultrasound treatments during respiratory motion with discontinuous motion boundaries,” IEEE Trans. Biomed. Eng., vol. 64, no. 7, pp. 1455–1468, 2017. DOI:10.1109/TBME.2016.2619741.
  • Z.-Z. He, and J. Liu, “An efficient parallel numerical modeling of bioheat transfer in realistic tissue structure,” Int. J. Heat Mass Transf., vol. 95, pp. 843–852, 2016. DOI:10.1016/j.ijheatmasstransfer.2015.12.028.
  • G. Carluccio, D. Erricolo, S. Oh, and C. M. Collins, “An approach to rapid calculation of temperature change in tissue using spatial filters to approximate effects of thermal conduction,” IEEE Trans. Biomed. Eng, vol. 60, no. 6, pp. 1735–1741, 2013.
  • G. Kalantzis, W. Miller, W. Tichy, and S. LeBlang, “A GPU accelerated finite differences method of the bioheat transfer equation for ultrasound thermal ablation,” in Software Engineering, Artificial Intelligence, Networking Parallel/Distributed Computing, Springer, 2016, pp. 45–55.
  • J. L. Dillenseger, and S. Esneault, “Fast FFT-based bioheat transfer equation computation,” Comput Biol Med, vol. 40, no. 2, pp. 119–123, 2010. DOI:10.1016/j.compbiomed.2009.11.008.
  • G. Chen, J. Stang, M. Haynes, E. Leuthardt, and M. Moghaddam, “Real-time three-dimensional microwave monitoring of interstitial thermal therapy,” IEEE Trans. Biomed. Eng., vol. 65, no. 3, pp. 528–538, 2018. DOI:10.1109/TBME.2017.2702182.
  • P. C. Johnson, and G. M. Saidel, “Thermal model for fast simulation during magnetic resonance imaging guidance of radio frequency tumor ablation,” Ann. Biomed. Eng., vol. 30, no. 9, pp. 1152–1161, 2002. DOI:10.1114/1.1519263.
  • J. H. Niu, H. Z. Wang, H. X. Zhang, J. Y. Yan, and Y. S. Zhu, “Cellular neural network analysis for two-dimensional bioheat transfer equation,” Med. Biol. Eng. Comput., vol. 39, no. 5, pp. 601–604, 2001. DOI:10.1007/BF02345153.
  • J. H. Indik, R. A. Indik, and T. C. Cetas, “Fast and efficient computer modeling of ferromagnetic seed arrays of arbitrary orientation for hyperthermia treatment planning,” Int. J. Radiat. Oncol. Biol. Phys., vol. 30, no. 3, pp. 653–662, 1994. DOI:10.1016/0360-3016(92)90952-E.
  • R. A. Indik, and J. H. Indik, “A new computer method to quickly and accurately compute steady-state temperatures from ferromagnetic seed heating,” Med. Phys., vol. 21, no. 7, pp. 1135–1144, 1994. DOI:10.1118/1.597340.
  • P. Mariappan et al., “GPU-based RFA simulation for minimally invasive cancer treatment of liver tumours,” Int. J. CARS, vol. 12, no. 1, pp. 59–68, 2017. DOI:10.1007/s11548-016-1469-1.
  • J. Zhang, J. Hills, Y. Zhong, B. Shirinzadeh, J. Smith, and C. Gu, “GPU-accelerated finite element modeling of bio-heat conduction for simulation of thermal ablation,” J. Mech. Med. Biol., vol. 18, no. 07, pp. 1840012, 2018. DOI:10.1142/S0219519418400122.
  • G. C. Bourantas et al., “Real-time tumor ablation simulation based on the dynamic mode decomposition method,” Med. Phys., vol. 41, no. 5, pp. 053301, 2014. DOI:10.1118/1.4870976.
  • M. E. Kowalski, and J. M. Jin, “Model-order reduction of nonlinear models of electromagnetic phased-array hyperthermia,” IEEE Trans Biomed Eng, vol. 50, no. 11, pp. 1243–1254, 2003.
  • C. Ding, X. Cui, R. R. Deokar, G. Li, Y. Cai, and K. K. Tamma, “An isogeometric independent coefficients (IGA-IC) reduced order method for accurate and efficient transient nonlinear heat conduction analysis,” Numer. Heat Transf. Part A Appl., vol. 73, no. 10, pp. 667–684, 2018. DOI:10.1080/10407782.2018.1470420.
  • J. Zhang, Y. Zhong, and C. Gu, “Energy balance method for modelling of soft tissue deformation,” Comput. Aided Des., vol. 93, pp. 15–25, 2017. DOI:10.1016/j.cad.2017.07.006.
  • J. Zhang, and S. Chauhan, “Fast explicit dynamics finite element algorithm for transient heat transfer,” Int. J. Thermal Sci., vol. 139, pp. 160–175, 2019. DOI:10.1016/j.ijthermalsci.2019.01.030.
  • H. H. Pennes, “Analysis of tissue and arterial blood temperatures in the resting human forearm,” J. Appl. Phys., vol. 1, no. 2, pp. 93–122, 1948. DOI:10.1152/jappl.1948.1.2.93.
  • W. Shen, J. Zhang, and F. Yang, “Modeling and numerical simulation of bioheat transfer and biomechanics in soft tissue,” Math. Comput. Model., vol. 41, no. 11-12, pp. 1251–1265, 2005. DOI:10.1016/j.mcm.2004.09.006.
  • J. Durkee, Jr, and P. Antich, “Exact solutions to the multi-region time-dependent bioheat equation with transient heat sources and boundary conditions,” Phys. Med. Biol., vol. 36, no. 3, pp. 345, 1991. DOI:10.1088/0031-9155/36/3/004.
  • P. Prakash, and C. J. Diederich, “Considerations for theoretical modelling of thermal ablation with catheter-based ultrasonic sources: implications for treatment planning, monitoring and control,” Int. J. Hyperthermia, vol. 28, no. 1, pp. 69–86, 2012. DOI:10.3109/02656736.2011.630337.
  • Z.-Z. He, and J. Liu, “A coupled continuum-discrete bioheat transfer model for vascularized tissue,” Int. J. Heat Mass Transf., vol. 107, pp. 544–556, 2017. DOI:10.1016/j.ijheatmasstransfer.2016.11.053.
  • A. R. A. Khaled, and K. Vafai, “The role of porous media in modeling flow and heat transfer in biological tissues,” Int. J. Heat Mass Transf., vol. 46, no. 26, pp. 4989–5003, 2003. DOI:10.1016/S0017-9310(03)00301-6.
  • E. L. Wilson, K. J. Bathe, and F. E. Peterson, “Finite element analysis of linear and nonlinear heat transfer,” Nucl. Eng. Des., vol. 29, no. 1, pp. 110–124, 1974. DOI:10.1016/0029-5493(74)90101-0.
  • X. Rong, R. Niu, and G. Liu, “Stability analysis of smoothed finite element methods with explicit method for transient heat transfer problems,” Int. j. Comput. Methods, 1845005, 2018. DOI:10.1142/S0219876218450056.
  • E. Li, Z. C. He, Q. Tang, and G. Y. Zhang, “Large time steps in the explicit formulation of transient heat transfer,” Int. J. Heat Mass Transf., vol. 108, pp. 2040–2052, 2017. DOI:10.1016/j.ijheatmasstransfer.2017.01.065.
  • X.-G. Li, L.-P. Yi, Z.-Z. Yang, Y.-T. Chen, and J. Sun, “Coupling model for calculation of transient temperature and pressure during coiled tubing drilling with supercritical carbon dioxide,” Int. J. Heat Mass Transf., vol. 125, pp. 400–412, 2018. DOI:10.1016/j.ijheatmasstransfer.2018.04.095.
  • R. Courant, K. Friedrichs, and H. Lewy, “On the partial difference equations of mathematical physics,” IBM J. Res. Develop., vol. 11, no. 2, pp. 215–234, 1967. DOI:10.1147/rd.112.0215.
  • K.-J. Bathe, Finite Element Procedures. Klaus-Jurgen Bathe, 2006.
  • E. Li, Z. C. He, Z. Zhang, G. R. Liu, and Q. Li, “Stability analysis of generalized mass formulation in dynamic heat transfer,” Numer. Heat Transf. Part B Fund., vol. 69, no. 4, pp. 287–311, 2016. DOI:10.1080/10407790.2015.1104215.
  • S. Haddadi, and M. T. Ahmadian, “Numerical and experimental evaluation of high-intensity focused ultrasound-induced lesions in liver tissue ex vivo,” J. Ultrasound Med., vol. 37, no. 6, pp. 1481–1491, 2018. DOI:10.1002/jum.14491.
  • P. Rattanadecho, and P. Keangin, “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., vol. 58, no. 1–2, pp. 457–470, 2013. DOI:10.1016/j.ijheatmasstransfer.2012.10.043.
  • W. Karaki, Rahul, C. A. Lopez, D. A. Borca-Tasciuc, and S. De, “A continuum thermomechanical model of in vivo electrosurgical heating of hydrated soft biological tissues,” Int. J. Heat Mass Transf., vol. 127, no. Pt A, pp. 961–974, 2018.
  • J. Zhang, Y. Zhong, J. Smith, and C. Gu, “Cellular neural network modelling of soft tissue dynamics for surgical simulation,” Technol Health Care, vol. 25, S1, pp. 337–344, 2017. DOI:10.3233/THC-171337.
  • J. Zhang, Y. Zhong, and C. Gu, “Neural network modelling of soft tissue deformation for surgical simulation,” Artif. Intell. Med., 2018.

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