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Reviews

Thermal ablation of biological tissues in disease treatment: A review of computational models and future directions

ORCID Icon & ORCID Icon
Pages 49-88 | Received 17 Oct 2019, Accepted 01 Mar 2020, Published online: 01 Apr 2020

References

  • Abraham, J., and E. Sparrow. 2007. A thermal-ablation bioheat model including liquid-to-vapor phase change, pressure-and necrosis-dependent perfusion, and moisture-dependent properties. Int. J. Heat Mass Transfer 50:2537–44. doi:10.1016/j.ijheatmasstransfer.2006.11.045.
  • Ahmed, M., C. L. Brace, F. T. Lee Jr, and S. N. Goldberg. 2011. Principles of and advances in percutaneous ablation. Radiology 258:351–69. doi:10.1148/radiol.10081634.
  • Ahmed, M., Z. Liu, S. Humphries, and S. Nahum Goldberg. 2008. Computer modeling of the combined effects of perfusion, electrical conductivity, and thermal conductivity on tissue heating patterns in radiofrequency tumor ablation. Int. J. Hyperthermia 24:577–88. doi:10.1080/02656730802192661.
  • Alber, M., A. B. Tepole, W. R. Cannon, S. De, S. Dura-Bernal, K. Garikipati, G. Karniadakis, W. W. Lytton, P. Perdikaris, and L. Petzold. 2019. Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences. Npj Digital Med. 2:1–11. doi:10.1038/s41746-019-0193-y.
  • Almekkawy, M., J. Chen, M. Ellis, D. Haemmerich, D. Holmes, C. Linte, D. Panescu, J. Pearce, P. Prakash, and V. Zderic. 2020. Therapeutic systems and technologies: State-of-the-art, applications, opportunities and challenges. IEEE Rev. Biomed. Eng 13: 325–39. doi:10.1109/RBME.2019.2908940.
  • Altrogge, I., T. Preusser, T. Kröger, C. Büskens, P. L. Pereira, D. Schmidt, and H.-O. Peitgen. 2007. Multiscale optimization of the probe placement for radiofr ablation. Acad. Radiol. 14:1310–24. doi:10.1016/j.acra.2007.07.016.
  • Amabile, C., L. Farina, V. Lopresto, R. Pinto, S. Cassarino, N. Tosoratti, S. N. Goldberg, and M. CAVAGNARO. 2017. Tissue shrinkage in microwave ablation of liver: An ex vivo predictive model. Int. J. Hyperthermia 33:101–09. doi:10.1080/02656736.2016.1208292.
  • Andreozzi, A., L. Brunese, M. Iasiello, C. Tucci, and G. P. Vanoli. 2019. Modeling heat transfer in tumors: A review of thermal therapies. Ann. Biomed. Eng. 47:676–93. doi:10.1007/s10439-018-02177-x.
  • Argüello, E. J., R. J. Silva, M. K. Huerta, and R. S. Avila. 2015. Computational modeling of peripheral pain: A commentary. Biomed. Eng. Online 14:56. doi:10.1186/s12938-015-0049-x.
  • Ashraf, O., N. V. Patel, S. Hanft, and S. F. Danish. 2018. Laser-induced thermal therapy in neuro-oncology: A review. World Neurosurg. 112:166–77. doi:10.1016/j.wneu.2018.01.123.
  • Askarizadeh, H., and H. Ahmadikia. 2014. Analytical analysis of the dual-phase-lag model of bioheat transfer equation during transient heating of skin tissue. Heat Mass Transfer 50:1673–84. doi:10.1007/s00231-014-1373-6.
  • Attaluri, A., R. Ma, Y. Qiu, W. Li, and L. Zhu. 2011. Nanoparticle distribution and temperature elevations in prostatic tumours in mice during magnetic nanoparticle hyperthermia. Int. J. Hyperthermia 27:491–502. doi:10.3109/02656736.2011.584856.
  • Audigier, C., T. Mansi, H. Delingette, S. Rapaka, T. Passerini, V. Mihalef, M.-P. Jolly, R. Pop, M. Diana, and L. Soler. 2017. Comprehensive preclinical evaluation of a multi-physics model of liver tumor radiofrequency ablation. Int. J. Comput Assist Radiol. Surg. 12:1543–59. doi:10.1007/s11548-016-1517-x.
  • Audigier, C., T. Mansi, H. Delingette, S. Rapaka, V. Mihalef, D. Carnegie, E. Boctor, M. Choti, A. Kamen, and N. Ayache. 2015. Efficient lattice boltzmann solver for patient-specific radiofrequency ablation of hepatic tumors. IEEE Trans. Med. Imaging 34:1576–89. doi:10.1109/TMI.2015.2406575.
  • Audigier, C., T. Mansi, H. Delingette, S. Rapaka, V. Mihalef, P. Sharma, D. Carnegie, E. Boctor, M. Choti, and A. Kamen. 2013. Lattice Boltzmann method for fast patient-specific simulation of liver tumor ablation from CT images. International Conference on Medical Image Computing and Computer-Assisted Intervention, 323–30, Springer, Nagoya, Japan. doi:10.1007/978-3-642-40760-4_41
  • Barauskas, R., A. Gulbinas, T. Vanagas, and G. Barauskas. 2008. Finite element modeling of cooled-tip probe radiofrequency ablation processes in liver tissue. Comput. Biol. Med. 38:694–708. doi:10.1016/j.compbiomed.2008.03.007.
  • Berjano, E. J. 2006. Theoretical modeling for radiofrequency ablation: State-of-the-art and challenges for the future. Biomed. Eng. Online 5:24. doi:10.1186/1475-925X-5-24.
  • Besler, E., Y. Curtis Wang, T. C. Chan, and A. V. Sahakian. 2019a. Real-time monitoring radiofrequency ablation using tree-based ensemble learning models. Int. J. Hyperthermia 36:428–37. doi:10.1080/02656736.2019.1587008.
  • Besler, E., Y. C. Wang, and A. V. Sahakian. 2019b. Early and late fusion machine learning on multi-frequency electrical impedance data to improve radiofrequency ablation monitoring. IEEE J. Biomed. Health. Inf.. doi:10.1109/JBHI.2019.2952922.
  • Bhowmik, A., R. Repaka, S. C. Mishra, and K. Mitra. 2014. Analysis of radiative signals from normal and malignant human skins subjected to a short-pulse laser. Int. J. Heat Mass Transfer 68:278–94. doi:10.1016/j.ijheatmasstransfer.2013.09.032.
  • Bhowmik, A., R. Repaka, S. C. Mishra, and K. Mitra. 2016. Thermal assessment of ablation limit of subsurface tumor during focused ultrasound and laser heating. J. Therm. Sci. Eng. Appl. 8:011012. doi:10.1115/1.4030731.
  • Bhowmik, A., R. Singh, R. Repaka, and S. C. Mishra. 2013. Conventional and newly developed bioheat transport models in vascularized tissues: A review. J. Therm. Biol. 38:107–25. doi:10.1016/j.jtherbio.2012.12.003.
  • Brace, C. 2011. Thermal tumor ablation in clinical use. IEEE Pulse 2:28–38. doi:10.1109/MPUL.2011.942603.
  • Brace, C. L., T. A. Diaz, J. L. Hinshaw, and F. T. Lee Jr. 2010. Tissue contraction caused by radiofrequency and microwave ablation: A laboratory study in liver and lung. J. Vasc. Int. Radiol. 21:1280–86. doi:10.1016/j.jvir.2010.02.038.
  • Calodney, A., R. Rosenthal, A. Gordon, and R. E. Wright. 2016. Targeted radiofrequency techniques. In Techniques of neurolysis Springer edited by Gabor B. Racz and Carl Edward Noe, pp. 33-73, Springer International Publishing Switzerland. doi:10.1007/978-3-319-27607-6
  • Cardinal, J., J. R. Klune, E. Chory, G. Jeyabalan, J. S. Kanzius, M. Nalesnik, and D. A. Geller. 2008. Noninvasive radiofrequency ablation of cancer targeted by gold nanoparticles. Surgery 144:125–32. doi:10.1016/j.surg.2008.03.036.
  • Cattaneo, C. 1958. A form of heat-conduction equations which eliminates the paradox of instantaneous propagation. Comptes Rendus 247:431.
  • Cavagnaro, M., C. Amabile, S. Cassarino, N. Tosoratti, R. Pinto, and V. Lopresto. 2015a. Influence of the target tissue size on the shape of ex vivo microwave ablation zones. Int. J. Hyperthermia 31:48–57. doi:10.3109/02656736.2014.997312.
  • Cavagnaro, M., R. Pinto, and V. Lopresto. 2015b. Numerical models to evaluate the temperature increase induced by ex vivo microwave thermal ablation. Phys. Med. Biol. 60:3287. doi:10.1088/0031-9155/60/8/3287.
  • Chaichanyut, M., and S. Tungjitkusolmun. 2016. Microwave ablation using four-tine antenna: Effects of blood flow velocity, vessel location, and total displacement on porous hepatic cancer tissue. Comput. Math. Methods Med. 2016: doi: 10.1155/2016/4846738.
  • Chang, M. C. 2018. Efficacy of pulsed radiofrequency stimulation in patients with peripheral neuropathic pain: A narrative review. Pain Physician 21:E225–E234. doi:10.36076/ppj.2018.3.E225.
  • Chen, J., C. Ning, Z. Zhou, P. Yu, Y. ZHU, G. Tan, and C. Mao. 2019. Nanomaterials as photothermal therapeutic agents. Prog. Mater Sci. 99:1–26. doi:10.1016/j.pmatsci.2018.07.005.
  • Chen, R., F. Lu, F. Wu, L. Xie, and D. Kong. 2018. An analytical solution for temperature distributions in hepatic radiofrequency ablation incorporating the heat-sink effect of large vessels. Phys. Med. Biol. 63:235026. doi:10.1088/1361-6560/aaeef9.
  • Cheong, J. K., S. Yap, E. T. Ooi, and E. H. Ooi. 2019. A computational model to investigate the influence of electrode lengths on the single probe bipolar radiofrequency ablation of the liver. Comput. Methods Programs Biomed. 176:17–32. doi:10.1016/j.cmpb.2019.04.028.
  • Cherukuri, P., and S. A. Curley. 2010. Use of nanoparticles for targeted, noninvasive thermal destruction of malignant cells. In Cancer nanotechnology edited by Stephen R. Grobmyer and Brij M. Moudgil, pp. 359-73. Springer,  Humana Press, United States. doi:10.1007/978-1-60761-609-2_24.
  • Chiang, J., P. Wang, and C. L. Brace. 2013. Computational modelling of microwave tumour ablations. Int. J. Hyperthermia 29:308–17. doi:10.3109/02656736.2013.799295.
  • Christ, A., W. Kainz, E. G. Hahn, K. Honegger, M. Zefferer, E. Neufeld, W. Rascher, R. Janka, W. Bautz, and J. Chen. 2009. The virtual family—development of surface-based anatomical models of two adults and two children for dosimetric simulations. Phys. Med. Biol. 55:N23. doi:10.1088/0031-9155/55/2/N01.
  • Chu, K. F., and D. E. Dupuy. 2014. Thermal ablation of tumours: Biological mechanisms and advances in therapy. Nat. Rev. Cancer 14:199. doi:10.1038/nrc3672.
  • Chua, N. H., K. C. Vissers, and M. E. Sluijter. 2011. Pulsed radiofrequency treatment in interventional pain management: Mechanisms and potential indications—a review. Acta Neurochir (Wien) 153:763–71. doi:10.1007/s00701-010-0881-5.
  • Cinelli, I., M. Destrade, M. Duffy, and P. Mchugh. 2017. Electrothermal equivalent three-dimensional finite-element model of a single neuron. IEEE Trans. Biomed. Eng. 65:1373–81. doi:10.1109/TBME.2017.2752258.
  • Corr, S. J., B. T. Cisneros, L. Green, M. Raoof, and S. A. Curley. 2013. Protocols for assessing radiofrequency interactions with gold nanoparticles and biological systems for non-invasive hyperthermia cancer therapy. JoVE (Journal of Visualized Experiments) 78:e50480. doi:10.3791/50480
  • Cosman, E. R., Jr, and E. R. Cosman Sr. 2005. Electric and thermal field effects in tissue around radiofrequency electrodes. Pain Med. 6:405–24. doi:10.1111/j.1526-4637.2005.00076.x.
  • Cosman, E. R., Jr, J. R. Dolensky, and R. A. Hoffman. 2014. Factors that affect radiofrequency heat lesion size. Pain Med. 15:2020–36. doi:10.1111/pme.12566.
  • Curley, S., F. Palalon, K. Sanders, and N. Koshkina. 2014a. The effects of non-invasive radiofrequency treatment and hyperthermia on malignant and nonmalignant cells. Int. J. Environ. Res. Public Health 11:9142–53. doi:10.3390/ijerph110909142.
  • Curley, S. A., F. Palalon, X. Lu, and N. V. Koshkina. 2014b. Noninvasive radiofrequency treatment effect on mitochondria in pancreatic cancer cells. Cancer 120:3418–25. doi:10.1002/cncr.28895.
  • Deatsch, A. E., and B. A. Evans. 2014. Heating efficiency in magnetic nanoparticle hyperthermia. J. Magn. Magn. Mater 354:163–72. doi:10.1016/j.jmmm.2013.11.006.
  • Dennis, C. L., and R. Ivkov. 2013. Physics of heat generation using magnetic nanoparticles for hyperthermia. Int. J. Hyperthermia 29:715–29. doi:10.3109/02656736.2013.836758.
  • Dezhdar, T., R. A. Moshourab, I. Fründ, G. R. Lewin, and M. Schmuker. 2015. A probabilistic model for estimating the depth and threshold temperature of C-fiber nociceptors. Sci. Rep. 5:17670. doi:10.1038/srep17670.
  • Erdine, S., A. Bilir, E. R. Cosman, and E. R. Cosman Jr. 2009. Ultrastructural changes in axons following exposure to pulsed radiofrequency fields. Pain Pract. 9:407–17. doi:10.1111/j.1533-2500.2009.00317.x.
  • Evans, B. A., M. D. Bausch, K. D. Sienerth, and M. J. Davern. 2018. Non-monotonicity in the influence of nanoparticle concentration on SAR in magnetic nanoparticle hyperthermia. J. Magn. Magn. Mater 465:559–65. doi:10.1016/j.jmmm.2018.06.051.
  • Ewertowska, E., B. Mercadal, V. Muñoz, A. Ivorra, M. Trujillo, and E. Berjano. 2018a. Effect of applied voltage, duration and repetition frequency of RF pulses for pain relief on temperature spikes and electrical field: A computer modelling study. Int. J. Hyperthermia 34:112–21. doi:10.1080/02656736.2017.1323122.
  • Ewertowska, E., R. Quesada, A. Radosevic, A. Andaluz, X. Moll, F. G. Arnas, E. Berjano, F. Burdío, and M. Trujillo. 2018b. A clinically oriented computer model for radiofrequency ablation of hepatic tissue with internally cooled wet electrode. Int. J. Hyperthermia 35:194–204. doi:10.1080/02656736.2018.1489071.
  • Eyerly, S. A., M. Vejdani‐Jahromi, D. M. Dumont, G. E. Trahey, and P. D. Wolf. 2015. The evolution of tissue stiffness at radiofrequency ablation sites during lesion formation and in the peri‐ablation period. J. Cardiovasc. Electrophysiol. 26:1009–18. doi:10.1111/jce.12709.
  • Fahrenholtz, S. J., R. Madankan, S. Danish, J. D. Hazle, R. J. Stafford, and D. Fuentes. 2018. Theoretical model for laser ablation outcome predictions in brain: Calibration and validation on clinical MR thermometry images. Int. J. Hyperthermia 34:101–11. doi:10.1080/02656736.2017.1319974.
  • Fang, Z., B. Zhang, and W. Zhang. 2017. Current solutions for the heat-sink effect of blood vessels with radiofrequency ablation: A review and future work. In Advanced computational methods in life system modeling and simulation edited by Minrui Fei, Shiwei Ma, Xin Li, Xin Sun, Li Jia, Zhou Su, pp. 113–22. Springer Nature Singapore. doi:10.1007/978-981-10-6370-1_12.
  • Farina, L., N. Weiss, Y. Nissenbaum, M. Cavagnaro, V. Lopresto, R. Pinto, N. Tosoratti, C. Amabile, S. Cassarino, and S. N. Goldberg. 2014. Characterisation of tissue shrinkage during microwave thermal ablation. Int. J. Hyperthermia 30:419–28. doi:10.3109/02656736.2014.957250.
  • Farina, L., Y. Nissenbaum, M. Cavagnaro, and S. N. Goldberg. 2018. Tissue shrinkage in microwave thermal ablation: Comparison of three commercial devices. Int. J. Hyperthermia 34:382–91. doi:10.1080/02656736.2017.1362115.
  • Feng, W., W. Nie, Y. Cheng, X. Zhou, L. Chen, K. Qiu, Z. Chen, M. Zhu, and C. He. 2015. In vitro and in vivo toxicity studies of copper sulfide nanoplates for potential photothermal applications. Nanomed. Nanotechnol. Biol. Med. 11:901–12. doi:10.1016/j.nano.2014.12.015.
  • Ganguly, S., S. Sikdar, and S. Basu. 2009. Experimental investigation of the effective electrical conductivity of aluminum oxide nanofluids. Powder Technol. 196:326–30. doi:10.1016/j.powtec.2009.08.010.
  • Gannon, C. J., C. R. Patra, R. Bhattacharya, P. Mukherjee, and S. A. Curley. 2008. Intracellular gold nanoparticles enhance non-invasive radiofrequency thermal destruction of human gastrointestinal cancer cells. J. Nanobiotechnol. 6:2. doi:10.1186/1477-3155-6-2.
  • Gannon, C. J., P. Cherukuri, B. I. Yakobson, L. Cognet, J. S. Kanzius, C. Kittrell, R. B. Weisman, M. Pasquali, H. K. Schmidt, and R. E. Smalley. 2007. Carbon nanotube‐enhanced thermal destruction of cancer cells in a noninvasive radiofrequency field. Cancer 110:2654–65. doi:10.1002/cncr.23155.
  • Gao, H., X. Wang, S. Wu, Z. Zhou, and Y. Bai. 2019a. 2450‐MHz microwave ablation temperature simulation using temperature‐dependence feedback of characteristic parameters. Int. J. of RF Microwave Comput.‐Aided Eng. 29:e21488. doi:10.1002/mmce.21488.
  • Gao, H., X. Wang, S. Wu, Z. Zhou, Y. Bai, and H. Ai. 2019b. Characterization of 2450‐MHz microwave thermal coagulation zone based on characteristic length growth model and shape variation factor. Int. J. of RF Microwave Comput.‐Aided Eng. 29:e21705. doi:10.1002/mmce.21705.
  • Gao, H., X. Wang, S. Wu, Z. Zhou, Y. Bai, and W. Wu. 2019c. Conformal coverage of liver tumors by the thermal coagulation zone in 2450-MHz microwave ablation. Int. J. Hyperthermia 36:591–605. doi:10.1080/02656736.2019.1617437.
  • Gerardo-Giorda, L., and J. M. Kroos. 2017. A computational multiscale model of cortical spreading depression propagation. Comput. Math. Appl. 74:1076–90. doi:10.1016/j.camwa.2017.05.013.
  • Glazer, E. S., C. Zhu, K. L. Massey, C. S. Thompson, W. D. Kaluarachchi, A. N. Hamir, and S. A. Curley. 2010b. Noninvasive radiofrequency field destruction of pancreatic adenocarcinoma xenografts treated with targeted gold nanoparticles. Clin. Cancer Res. 16:5712–21. doi:10.1158/1078-0432.CCR-10-2055.
  • Glazer, E. S., K. L. Massey, C. Zhu, and S. A. Curley. 2010a. Pancreatic carcinoma cells are susceptible to noninvasive radio frequency fields after treatment with targeted gold nanoparticles. Surgery 148:319–24. doi:10.1016/j.surg.2010.04.025.
  • Glazer, E. S., and S. A. Curley. 2011. Non-invasive radiofrequency ablation of malignancies mediated by quantum dots, gold nanoparticles and carbon nanotubes. Ther. Deliv. 2:1325–30. doi:10.4155/tde.11.102.
  • Glory, J., M. Bonetti, M. Helezen, M. MAYNE-L’HERMITE, and C. Reynaud. 2008. Thermal and electrical conductivities of water-based nanofluids prepared with long multiwalled carbon nanotubes. J. Appl. Phys. 103:094309. doi:10.1063/1.2908229.
  • González‐Suárez, A., E. Gutierrez‐Herrera, E. Berjano, J. N. Jimenez Lozano, and W. Franco. 2015. Thermal and elastic response of subcutaneous tissue with different fibrous septa architectures to RF heating: Numerical study. Lasers Surg. Med. 47:183–95. doi:10.1002/lsm.22301.
  • González-Suárez, A., J. J. Pérez, and E. Berjano. 2018. Should fluid dynamics be included in computer models of RF cardiac ablation by irrigated-tip electrodes? Biomed. Eng. Online 17:43. doi:10.1186/s12938-018-0475-7.
  • Haemmerich, D., A. Wright, D. Mahvi, F. Lee, and J. Webster. 2003. Hepatic bipolar radiofrequency ablation creates coagulation zones close to blood vessels: A finite element study. Med. Biol Eng. Comput. 41:317–23. doi:10.1007/BF02348437.
  • Hajimolahoseini, H., J. Hashemi, S. Gazor, and D. Redfearn. 2018. Inflection point analysis: A machine learning approach for extraction of IEGM active intervals during atrial fibrillation. Artif. Intell. Med. 85:7–15. doi:10.1016/j.artmed.2018.02.003.
  • Hall, S. K., E. H. Ooi, and S. J. Payne. 2014. A mathematical framework for minimally invasive tumor ablation therapies. Crit. Rev.™ Biomed. Eng. 42: 383-417. doi:10.1615/CritRevBiomedEng.2014011825.
  • Hall, S. K., E. H. Ooi, and S. J. Payne. 2015. Cell death, perfusion and electrical parameters are critical in models of hepatic radiofrequency ablation. Int. J. Hyperthermia 31:538–50. doi:10.3109/02656736.2015.1032370.
  • Hasgall, P., F. Di Gennaro, C. Baumgartner, E. Neufeld, M. Gosselin, D. Payne, A. Klingenböck, and N. Kuster. 2015. IT’IS database for thermal and electromagnetic parameters of biological tissues. Version 3. itis.swiss/database, doi:10.13099/VIP21000-04-0
  • Hassanpour, S., and A. Saboonchi. 2016. Modeling of heat transfer in a vascular tissue-like medium during an interstitial hyperthermia process. J. Therm. Biol. 62:150–58. doi:10.1016/j.jtherbio.2016.06.022.
  • He, Z. Z., X. Xue, and J. Liu. 2013. An effective finite difference method for simulation of bioheat transfer in irregular tissues. J. Heat Transfer 135:071003. doi:10.1115/1.4024064.
  • Holt, A. B., and T. I. Netoff. 2013. Computational modeling of epilepsy for an experimental neurologist. Exp. Neurol. 244:75–86. doi:10.1016/j.expneurol.2012.05.003.
  • Horng, T. L., W. L. Lin, C. T. Liauh, and T. C. Shih. 2007. Effects of pulsatile blood flow in large vessels on thermal dose distribution during thermal therapy. Med. Phys. 34:1312–20. doi:10.1118/1.2712415.
  • Huang, H. W. 2013. Influence of blood vessel on the thermal lesion formation during radiofrequency ablation for liver tumors. Med. Phys. 40:073303. doi:10.1118/1.4811135.
  • Huang, H.-W., and T.-L. Horng. 2015. Bioheat transfer and thermal heating for tumor treatment. In Heat transfer and fluid flow in biological processes, edited by Sid M. Becker and Andrey V. Kuznetsov, pp. 1–42. Academic Press United States. doi:10.1016/B978-0-12-408077-5.00001-8.
  • Jain, M. K., and P. D. Wolf. 2000. A three-dimensional finite element model of radiofrequency ablation with blood flow and its experimental validation. Ann. Biomed. Eng. 28:1075–84. doi:10.1114/1.1310219.
  • Jaunich, M., S. Raje, K. Kim, K. Mitra, and Z. Guo. 2008. Bio-heat transfer analysis during short pulse laser irradiation of tissues. Int. J. Heat Mass Transfer 51:5511–21. doi:10.1016/j.ijheatmasstransfer.2008.04.033.
  • Ji, Z., and C. L. Brace. 2011. Expanded modeling of temperature-dependent dielectric properties for microwave thermal ablation. Phys. Med. Biol. 56:5249. doi:10.1088/0031-9155/56/16/011.
  • Jiang, C.-P., M.-C. Wu, and Y.-S. Wu. 2012. Inducing occlusion effect in Y-shaped vessels using high-intensity focused ultrasound: Finite element analysis and phantom validation. Comput. Methods Biomech. Biomed. Eng. 15:323–32. doi:10.1080/10255842.2010.535521.
  • Jin, C., Z. He, and J. Liu. 2014. MRI-based finite element simulation on radiofrequency ablation of thyroid cancer. Comput. Methods Programs Biomed. 113:529–38. doi:10.1016/j.cmpb.2013.12.007.
  • Jirsa, V. K., T. Proix, D. Perdikis, M. M. Woodman, H. Wang, J. Gonzalez-Martinez, C. Bernard, C. Bénar, M. Guye, and P. Chauvel. 2017. The virtual epileptic patient: Individualized whole-brain models of epilepsy spread. Neuroimage 145:377–88. doi:10.1016/j.neuroimage.2016.04.049.
  • Kabiri, A., and M. R. Talaee. 2019. Theoretical investigation of thermal wave model of microwave ablation applied in prostate cancer therapy. Heat and Mass Transfer 55:2199-2208. doi:10.1007/s00231-019-02562-9.
  • Kaminski, W. 1990. Hyperbolic heat conduction equation for materials with a nonhomogeneous inner structure. J. Heat Transfer 112:555–60. doi:10.1115/1.2910422.
  • Karaki, W., C. A. Lopez, D.-A. Borca-Tasciuc, and S. De. 2018. A continuum thermomechanical model of in vivo electrosurgical heating of hydrated soft biological tissues. Int. J. Heat. Mass. Transfer 127:961–74. doi:10.1016/j.ijheatmasstransfer.2018.07.006.
  • Keangin, P., and P. Rattanadecho. 2013. Analysis of heat transport on local thermal non-equilibrium in porous liver during microwave ablation. Int. J. Heat Mass Transfer 67:46–60. doi:10.1016/j.ijheatmasstransfer.2013.07.064.
  • Keangin, P., and P. Rattanadecho. 2018. A numerical investigation of microwave ablation on porous liver tissue. Adv. Mech. Eng. 10:1687814017734133. doi:10.1177/1687814017734133.
  • Keangin, P., T. Wessapan, and P. Rattanadecho. 2011. Analysis of heat transfer in deformed liver cancer modeling treated using a microwave coaxial antenna. Appl. Therm. Eng. 31:3243–54. doi:10.1016/j.applthermaleng.2011.06.005.
  • Kessentini, S., and D. Barchiesi. 2012. Quantitative comparison of optimized nanorods, nanoshells and hollow nanospheres for photothermal therapy. Biomed. Opt. Express 3:590–604. doi:10.1364/BOE.3.000590.
  • Khademi, R., D. Mohebbi-Kalhori, and A. Razminia. 2019. Thermal analysis of a tumorous vascular tissue during pulsed-cryosurgery and nano-hyperthermia therapy: Finite element approach. Int. J. Heat Mass Transfer 137:1001–13. doi:10.1016/j.ijheatmasstransfer.2019.03.123.
  • Khaled, A.-R., and K. Vafai. 2003. The role of porous media in modeling flow and heat transfer in biological tissues. Int. J. Heat Mass Transfer 46:4989–5003. doi:10.1016/S0017-9310(03)00301-6.
  • Khanafer, T. K., and K. Vafai. 2009. Synthesis of mathematical models representing bioheat transport. In Advances in numerical heat transfer, edited by W. J. Minkowycz, Volume 3, pp.13-40. CRC Press, Boca Raton.
  • Khlebtsov, N., and L. Dykman. 2011. Biodistribution and toxicity of engineered gold nanoparticles: A review of in vitro and in vivo studies. Chem. Soc. Rev. 40:1647–71. doi:10.1039/C0CS00018C.
  • Kim, C. 2018. Understanding the nuances of microwave ablation for more accurate post-treatment assessment. Future Oncol. 14:1755–64. doi:10.2217/fon-2017-0736.
  • Kosik-Bogacka, D. I., N. LANOCHA-Arendarczyk, K. Kot, P. Zietek, M. Karaczun, A. Prokopowicz, P. Kupnicka, and Z. Ciosek. 2018. Calcium, magnesium, zinc and lead concentrations in the structures forming knee joint in patients with osteoarthritis‬. J. Trace Elem. Med. Biol. 50:409–14. doi:10.1016/j.jtemb.2018.08.007.
  • Kröger, T., S. Pannier, M. Kaliske, I. Altrogge, W. Graf, and T. Preusser. 2010. Optimal applicator placement in hepatic radiofrequency ablation on the basis of rare data. Comput. Methods Biomech. Biomed. Eng. 13:431–40. doi:10.1080/10255840903317394.
  • Kroos, J. M., I. Marinelli, I. Diez, J. M. Cortes, S. Stramaglia, and L. Gerardo‐Giorda. 2017. Patient‐specific computational modeling of cortical spreading depression via diffusion tensor imaging. Int. J. Numer. Method Biomed. Eng. 33:e2874. doi:10.1002/cnm.2874.
  • Kucyi, A., and K. D. Davis. 2015. The dynamic pain connectome. Trends Neurosci. 38:86–95. doi:10.1016/j.tins.2014.11.006.
  • Kumar, C. S., and F. Mohammad. 2011. Magnetic nanomaterials for hyperthermia-based therapy and controlled drug delivery. Adv. Drug Deliv. Rev. 63:789–808. doi:10.1016/j.addr.2011.03.008.
  • Kumar, D., S. Singh, N. Sharma, and K. Rai. 2018. Verified non-linear DPL model with experimental data for analyzing heat transfer in tissue during thermal therapy. Int. J. Therm. Sci. 133:320–29. doi:10.1016/j.ijthermalsci.2018.07.031.
  • Kumar, P., D. Kumar, and K. Rai. 2015. A numerical study on dual-phase-lag model of bio-heat transfer during hyperthermia treatment. J. Therm. Biol. 49:98–105. doi:10.1016/j.jtherbio.2015.02.008.
  • Kumar, P., D. Kumar, and K. Rai. 2016. Non-linear dual-phase-lag model for analyzing heat transfer phenomena in living tissues during thermal ablation. J. Therm. Biol. 60:204–12. doi:10.1016/j.jtherbio.2016.07.017.
  • Kumar, S., and A. Srivastava. 2015. Thermal analysis of laser-irradiated tissue phantoms using dual phase lag model coupled with transient radiative transfer equation. Int. J. Heat Mass Transfer 90:466–79. doi:10.1016/j.ijheatmasstransfer.2015.06.077.
  • Lagman, C., L. K. Chung, P. E. Pelargos, N. Ung, T. T. BUI, S. J. Lee, B. L. Voth, and I. Yang. 2017. Laser neurosurgery: A systematic analysis of magnetic resonance-guided laser interstitial thermal therapies. J. Clin. Neurosci. 36:20–26. doi:10.1016/j.jocn.2016.10.019.
  • Lebre, M.-A., A. Vacavant, M. Grand-Brochier, H. Rositi, A. Abergel, P. Chabrot, and B. Magnin. 2019. Automatic segmentation methods for liver and hepatic vessels from CT and MRI volumes, applied to the Couinaud scheme. Comput. Biol. Med. 110:42–51. doi:10.1016/j.compbiomed.2019.04.014.
  • Lebrun, A., and L. Zhu. 2018. Magnetic nanoparticle hyperthermia in cancer treatment: History, mechanism, imaging‐assisted protocol design, and challenges. Theory Appl. Heat Transfer Humans 2:631–67.
  • Lebrun, A., R. Ma, and L. Zhu. 2016b. MicroCT image based simulation to design heating protocols in magnetic nanoparticle hyperthermia for cancer treatment. J. Therm. Biol. 62:129–37. doi:10.1016/j.jtherbio.2016.06.025.
  • Lebrun, A., T. Joglekar, C. Bieberich, R. Ma, and L. Zhu. 2016a. Identification of infusion strategy for achieving repeatable nanoparticle distribution and quantification of thermal dosage using micro-CT Hounsfield unit in magnetic nanoparticle hyperthermia. Int. J. Hyperthermia 32:132–43. doi:10.3109/02656736.2015.1119316.
  • Lee, W., F. Guilak, and W. Liedtke. 2017. Role of piezo channels in joint health and injury. In Current topics in membranes edited by Philip A. Gottlieb, Volume 79, pp. 263–73 . Academic Press United States. doi: 10.1016/bs.ctm.2016.10.003
  • Leong, K., C. Yang, and S. Murshed. 2006. A model for the thermal conductivity of nanofluids–the effect of interfacial layer. J. Nanopart. Res. 8:245–54. doi:10.1007/s11051-005-9018-9.
  • Li, K., V. N. Vakharia, R. Sparks, L. G. França, A. Granados, A. W. Mcevoy, A. Miserocchi, M. Wang, S. Ourselin, and J. S. Duncan. 2019. Optimizing trajectories for cranial laser interstitial thermal therapy using computer-assisted planning: A machine learning approach. Neurotherapeutics 16:182–91. doi:10.1007/s13311-018-00693-1.
  • Li, X., Q.-H. Qin, and X. Tian. 2020. Thermo-viscoelastic analysis of biological tissue during hyperthermia treatment. Appl. Math. Model. 79:881–95. doi:10.1016/j.apm.2019.11.007.
  • Li, X., Y. Zhong, J. Smith, and C. Gu. 2017. Non-Fourier based thermal-mechanical tissue damage prediction for thermal ablation. Bioengineered 8:71–77. doi:10.1080/21655979.2016.1227609.
  • Li, X., Y. Zhong, R. Jazar, and A. Subic. 2014. Thermal-mechanical deformation modelling of soft tissues for thermal ablation. Biomed. Mater. Eng. 24:2299–310. doi:10.3233/BME-141043.
  • Li, Y., J. Yue, and C. Yang. 2016. Unraveling the role of Mg++ in osteoarthritis. Life Sci. 147:24–29. doi:10.1016/j.lfs.2016.01.029.
  • Lin, M., S. B. Liu, G. M. Genin, Y. Zhu, M. Shi, C. Ji, A. Li, T. J. Lu, and F. Xu. 2017. Melting away pain: Decay of thermal nociceptor transduction during heat-induced irreversible desensitization of ion channels. ACS Biomater. Sci. Eng. 3:3029–35. doi:10.1021/acsbiomaterials.6b00789.
  • Liu, C., C. S. Park, S. K. Hall, and S. J. Payne. 2017. Mathematical model of the post-ablation enhancement zone as a tissue-level oedematic response. Int. J. Hyperthermia 33:111–21. doi:10.1080/02656736.2016.1198832.
  • Liu, D., and C. L. Brace. 2014. CT imaging during microwave ablation: Analysis of spatial and temporal tissue contraction. Med. Phys. 41:113303. doi:10.1118/1.4897381.
  • Liu, D., and C. L. Brace. 2017. Numerical simulation of microwave ablation incorporating tissue contraction based on thermal dose. Phys. Med. Biol. 62:2070. doi:10.1088/1361-6560/aa5de4.
  • Liu, D., and C. L. Brace. 2019. Evaluation of tissue deformation during radiofrequency and microwave ablation procedures: Influence of output energy delivery. Med. Phys. 46:4127–34. doi:10.1002/mp.13688.
  • Liu, K.-C., and H.-T. Chen. 2010. Investigation for the dual phase lag behavior of bio-heat transfer. Int. J. Therm. Sci. 49:1138–46. doi:10.1016/j.ijthermalsci.2010.02.007.
  • López-Molina, J. A., M. J. Rivera, M. Trujillo, F. Burdío, J. L. Lequerica, F. Hornero, and E. J. Berjano. 2008. Assessment of hyperbolic heat transfer equation in theoretical modeling for radiofrequency heating techniques. Open Biomed. Eng. J. 2:22. doi:10.2174/1874120700802010022.
  • Lopresto, V., R. Pinto, L. Farina, and M. Cavagnaro. 2017a. Microwave thermal ablation: Effects of tissue properties variations on predictive models for treatment planning. Med. Eng. Phys. 46:63–70. doi:10.1016/j.medengphy.2017.06.008.
  • Lopresto, V., R. Pinto, L. Farina, and M. Cavagnaro. 2017b. Treatment planning in microwave thermal ablation: Clinical gaps and recent research advances. Int. J. Hyperthermia 33:83–100. doi:10.1080/02656736.2016.1214883.
  • Lopresto, V., R. Pinto, and M. Cavagnaro. 2014. Experimental characterisation of the thermal lesion induced by microwave ablation. Int. J. Hyperthermia 30:110–18. doi:10.3109/02656736.2013.879744.
  • Lötsch, J., and A. Ultsch. 2018. Machine learning in pain research. Pain 159:623. doi:10.1097/j.pain.0000000000001118.
  • Luyen, H., F. Gao, S. C. Hagness, and N. Behdad. 2014. Microwave ablation at 10.0 GHz achieves comparable ablation zones to 1.9 GHz in ex vivo bovine liver. IEEE Trans. Biomed. Eng. 61:1702–10. doi:10.1109/TBME.2014.2300692.
  • Lytton, W. W., J. Arle, G. Bobashev, S. Ji, T. L. Klassen, V. Z. Marmarelis, J. Schwaber, M. A. Sherif, and T. D. Sanger. 2017. Multiscale modeling in the clinic: Diseases of the brain and nervous system. Brain Inf. 4:219. doi:10.1007/s40708-017-0067-5.
  • Ma, M., Y. Zhang, and N. Gu. 2018. Estimation the tumor temperature in magnetic nanoparticle hyperthermia by infrared thermography: Phantom and numerical studies. J. Therm. Biol. 76:89–94. doi:10.1016/j.jtherbio.2018.07.004.
  • Mahapatra, D. R., and R. Melnik. 2006. Modelling and analysis of collagen piezoelectricity in human cornea. Dyn. Continuous Discrete Impulsive Syst-series A-math. Anal. 13:377–84.
  • Maillet, D. 2019. A review of the models using the Cattaneo and Vernotte hyperbolic heat equation and their experimental validation. Int. J. Therm. Sci. 139:424–32. doi:10.1016/j.ijthermalsci.2019.02.021.
  • Makropoulou, M., G. Kareliotis, E. Spyratou, E. Drakaki, A. Serafetinides, and E. Efstathopoulos. 2019. Non-ionizing, laser radiation in Theranostics: The need for dosimetry and the role of medical physics. Physica Medica 63:7–18. doi:10.1016/j.ejmp.2019.05.016.
  • Mariappan, P., P. Weir, R. Flanagan, P. Voglreiter, T. Alhonnoro, M. Pollari, M. Moche, H. Busse, J. Futterer, and H. R. Portugaller. 2017. GPU-based RFA simulation for minimally invasive cancer treatment of liver tumours. Int. J. Comput Assist Radiol. Surg. 12:59–68. doi:10.1007/s11548-016-1469-1.
  • Medvid, R., A. Ruiz, R. J. Komotar, J. Jagid, M. Ivan, R. Quencer, and M. Desai. 2015. Current applications of MRI-guided laser interstitial thermal therapy in the treatment of brain neoplasms and epilepsy: A radiologic and neurosurgical overview. Am. J. Neuroradiol. 36:1998–2006. doi:10.3174/ajnr.A4362.
  • Melnik, R., and K. Melnik. 1998. A note on the class of weakly coupled problems of non‐stationary piezoelectricity. Commun. Numer. Methods Eng. 14:839–47. doi:10.1002/(SICI)1099-0887(199809)14:9<839::AID-CNM192>3.0.CO;2-W.
  • Melnik, R. V. 2000. Generalised solutions, discrete models and energy estimates for a 2D problem of coupled field theory. Appl. Math. Comput. 107:27–55. doi:10.1016/S0096-3003(98)10143-1.
  • Mercadal, B., R. Vicente, and A. Ivorra. 2018. Pulsed radiofrequency for chronic pain: An electroporation mediated calcium signaling process? Biophys. J. 114:287a. doi:10.1016/j.bpj.2017.11.1646.
  • Miga, M. I. 2016. Computational modeling for enhancing soft tissue image guided surgery: An application in neurosurgery. Ann. Biomed. Eng. 44:128–38. doi:10.1007/s10439-015-1433-1.
  • Missios, S., K. Bekelis, and G. H. Barnett. 2015. Renaissance of laser interstitial thermal ablation. Neurosurg. Focus 38:E13. doi:10.3171/2014.12.FOCUS14762.
  • Mitchell, D., S. Fahrenholtz, C. Maclellan, D. Bastos, G. Rao, S. Prabhu, J. Weinberg, J. Hazle, J. Stafford, and D. Fuentes. 2018. A heterogeneous tissue model for treatment planning for magnetic resonance-guided laser interstitial thermal therapy. Int. J. Hyperthermia 34:943–52. doi:10.1080/02656736.2018.1429679.
  • Mitra, K., S. Kumar, A. Vedevarz, and M. Moallemi. 1995. Experimental evidence of hyperbolic heat conduction in processed meat. J Heat Transfer 117:568–73. doi:10.1115/1.2822615.
  • Moayedi, M., and K. D. Davis. 2012. Theories of pain: From specificity to gate control. J. Neurophysiol. 109:5–12. doi:10.1152/jn.00457.2012.
  • Moche, M., H. Busse, J. J. Futterer, C. A. Hinestrosa, D. Seider, P. Brandmaier, M. Kolesnik, S. Jenniskens, R. B. Sequeiros, and G. Komar. 2020. Clinical evaluation of in silico planning and real-time simulation of hepatic radiofrequency ablation (ClinicIMPPACT Trial). Eur. Radiol. 30:934–42. doi:10.1007/s00330-019-06411-5.
  • Mooney, R., E. Schena, P. Saccomandi, A. Zhumkhawala, K. Aboody, and J. M. Berlin. 2017. Gold nanorod-mediated near-infrared laser ablation: In vivo experiments on mice and theoretical analysis at different settings. Int. J. Hyperthermia 33:150–59. doi:10.1080/02656736.2016.1230682.
  • Mooney, R., L. Roma, D. Zhao, D. Van Haute, E. Garcia, S. U. Kim, A. J. Annala, K. S. Aboody, and J. M. Berlin. 2014. Neural stem cell-mediated intratumoral delivery of gold nanorods improves photothermal therapy. ACS Nano 8:12450–60. doi:10.1021/nn505147w.
  • Moreland, A. J., T. J. Ziemlewicz, S. L. Best, J. L. Hinshaw, M. G. Lubner, M. L. Alexander, C. L. Brace, D. R. Kitchin, S. P. Hedican, and S. Y. Nakada. 2014. High-powered microwave ablation of t1a renal cell carcinoma: Safety and initial clinical evaluation. J. Endourology 28:1046–52. doi:10.1089/end.2014.0190.
  • Mosgaard, L. D., K. A. Zecchi, and T. Heimburg. 2015. Mechano-capacitive properties of polarized membranes. Soft Matter 11:7899–910. doi:10.1039/C5SM01519G.
  • Muhieddine, M., E. Canot, and R. March. 2009. Various approaches for solving problems in heat conduction with phase change.
  • National Cancer Institute. Lasers in cancer treatment. [Online]. Accessed June 11, 2019. https://www.cancer.gov/about-cancer/treatment/types/surgery/lasers-fact-sheet.
  • Neal, M. L., and R. Kerckhoffs. 2009. Current progress in patient-specific modeling. Brief. Bioinf. 11:111–26. doi:10.1093/bib/bbp049.
  • Negro, R., M. Rucco, A. Creanza, A. Mormile, P. P. Limone, R. Garberoglio, S. Spiezia, S. Monti, C. Cugini, and G. El Dalati. 2019. Machine learning prediction of radiofrequency thermal ablation efficacy: A new option to optimize thyroid nodule selection. Eur. Thyroid J. 1–8. doi:10.1159/000504882.
  • Nield, D. A., and A. Bejan. 2017. Heat transfer through a porous medium. In Convection in porous media edited by Donald A. Nield and Adrian Bejan, pp. 31-46. Springer New York. doi:10.1007/978-1-4614-5541-7_2
  • Nirgudkar, H., S. Kumar, and A. Srivastava. 2017. Thermal analysis of laser-irradiated tissue phantoms using a novel separation of the variables-based discrete transfer method. Numer. Heat Transfer Part A 71:575–89. doi:10.1080/10407782.2016.1277925.
  • O’neill, D. P., T. Peng, P. Stiegler, U. Mayrhauser, S. Koestenbauer, K. Tscheliessnigg, and S. J. Payne. 2011. A three-state mathematical model of hyperthermic cell death. Ann. Biomed. Eng. 39:570–79. doi:10.1007/s10439-010-0177-1.
  • Okuno, T., S. Kato, Y. Hatakeyama, J. Okajima, S. Maruyama, M. Sakamoto, S. Mori, and T. Kodama. 2013. Photothermal therapy of tumors in lymph nodes using gold nanorods and near-infrared laser light. J. Controlled Release 172:879–84. doi:10.1016/j.jconrel.2013.10.014.
  • Ooi, E. H., K. W. Lee, S. Yap, M. A. Khattab, I. Y. Liao, E. T. Ooi, J. J. Foo, S. R. Nair, and A. F. M. Ali. 2019. The effects of electrical and thermal boundary condition on the simulation of radiofrequency ablation of liver cancer for tumours located near to the liver boundary. Comput. Biol. Med. 106:12–23. doi:10.1016/j.compbiomed.2019.01.003.
  • Ooi, E. H., N. Jy Chia, E. T. Ooi, J. J. Foo, I. Y. Liao, S. R. Nair, and A. F. Mohd Ali. 2018. Comparison between single-and dual-porosity models for fluid transport in predicting lesion volume following saline-infused radiofrequency ablation. Int. J. Hyperthermia 34:1142–56. doi:10.1080/02656736.2018.1437282.
  • Ortiz-Catalan, M. 2018. The stochastic entanglement and phantom motor execution hypotheses: A theoretical framework for the origin and treatment of PLP. Front Neurol. 9:748. doi:10.3389/fneur.2018.00748.
  • Park, C. S., C. Liu, S. K. Hall, and S. J. Payne. 2018. A thermoelastic deformation model of tissue contraction during thermal ablation. Int. J. Hyperthermia 34:221–28. doi:10.1080/02656736.2017.1335441.
  • Park, C. S., S. K. Hall, C. Liu, and S. J. Payne. 2016. A model of tissue contraction during thermal ablation. Physiol. Meas. 37:1474. doi:10.1088/0967-3334/37/9/1474.
  • Paul, A., A. Narasimhan, F. J. Kahlen, and S. K. Das. 2014. Temperature evolution in tissues embedded with large blood vessels during photo-thermal heating. J. Therm. Biol. 41:77–87. doi:10.1016/j.jtherbio.2014.02.010.
  • Paul, A., A. Narasimhan, S. K. Das, S. Sengupta, and T. Pradeep. 2016. Subsurface thermal behaviour of tissue mimics embedded with large blood vessels during plasmonic photo-thermal therapy. Int. J. Hyperthermia 32:765–77. doi:10.1080/02656736.2016.1196831.
  • Paul, A., and A. Paul. 2018. Computational study of photo-thermal ablation of large blood vessel embedded tumor using localized injection of gold nanoshells. J. Therm. Biol. 78:329–42. doi:10.1016/j.jtherbio.2018.10.021.
  • Paulides, M. M., P. R. Stauffer, E. Neufeld, P. F. Maccarini, A. Kyriakou, R. A. Canters, C. J. Diederich, J. F. Bakker, and G. C. Rvan Rhoon. 2013. Simulation techniques in hyperthermia treatment planning. Int. J. Hyperthermia 29:346–57. doi:10.3109/02656736.2013.790092.
  • Payne, S., R. Flanagan, M. Pollari, T. Alhonnoro, C. Bost, D. O’neill, T. Peng, and P. Stiegler. 2011. Image-based multi-scale modelling and validation of radio-frequency ablation in liver tumours. Philos. Trans. Royal Soc. A 369:4233–54. doi:10.1098/rsta.2011.0240.
  • Payne, S. J., T. Peng, and D. O’neill. 2010. Mathematical modeling of thermal ablation. Crit. Rev.™ Biomed. Eng. 38: 21-30. doi:10.1615/CritRevBiomedEng.v38.i1.30.
  • Pearce, J. A. 2013. Comparative analysis of mathematical models of cell death and thermal damage processes. Int. J. Hyperthermia 29:262–80. doi:10.3109/02656736.2013.786140.
  • Pennes, H. H. 1948. Analysis of tissue and arterial blood temperatures in the resting human forearm. J. Appl. Physiol. 1:93–122. doi:10.1152/jappl.1948.1.2.93.
  • Pérez, J. J., J. J. Pérez‐Cajaraville, V. Muñoz, and E. Berjano. 2014. Computer modeling of electrical and thermal performance during bipolar pulsed radiofrequency for pain relief. Med. Phys. 41:071708. doi:10.1118/1.4883776.
  • Pillai, K., J. Akhter, T. C. Chua, M. Shehata, N. Alzahrani, I. Al-Alem, and D. L. Morris. 2015. Heat sink effect on tumor ablation characteristics as observed in monopolar radiofrequency, bipolar radiofrequency, and microwave, using ex vivo calf liver model. Medicine 94: e580. doi:10.1097/MD.0000000000000580.
  • Prakash, P. 2010. Theoretical modeling for hepatic microwave ablation. Open Biomed. Eng. J. 4:27.
  • Prakash, P., and C. J. Diederich. 2012. Considerations for theoretical modelling of thermal ablation with catheter-based ultrasonic sources: Implications for treatment planning, monitoring and control. Int. J. Hyperthermia 28:69–86. doi:10.3109/02656736.2011.630337.
  • Prakash, P., V. A. Salgaonkar, E. Clif Burdette, and C. J. Diederich. 2012. Multiple applicator hepatic ablation with interstitial ultrasound devices: Theoretical and experimental investigation. Med. Phys. 39:7338–49. doi:10.1118/1.4765459.
  • Qadri, A. M., N. J. Chia, and E. H. Ooi. 2017. Effects of saline volume on lesion formation during saline-infused radiofrequency ablation. Appl. Math. Model. 43:360–71. doi:10.1016/j.apm.2016.11.032.
  • Quirk, M. T., and D. S. Lu. 2019. Noninvasive assessment of hepatocellular carcinoma tumor thrombus: Is it all in vein? Liver Transplant. 25:201–02. doi:10.1002/lt.25403.
  • Raaymakers, B., A. Kotte, and J. Lagendijk. 2009. Discrete vasculature (DIVA) model simulating the thermal impact of individual blood vessels for in vivo heat transfer. In Advances in numerical heat transfer, edited by W. J. Minkowycz, Volume 3, pp. 133–60. CRC Press, Boca Raton.
  • Rahmathulla, G., P. F. Recinos, K. Kamian, A. M. Mohammadi, M. S. Ahluwalia, and G. H. Barnett. 2014. MRI-guided laser interstitial thermal therapy in neuro-oncology: A review of its current clinical applications. Oncology 87:67–82. doi:10.1159/000362817.
  • Rao, W., and Z.-S. Deng. 2010. A review of hyperthermia combined with radiotherapy/chemotherapy on malignant tumors. Crit. Rev.™ Biomed. Eng. 38:101–16. doi:10.1615/CritRevBiomedEng.v38.i1.80.
  • Raoof, M., and S. A. Curley. 2011. Non-invasive radiofrequency-induced targeted hyperthermia for the treatment of hepatocellular carcinoma. Int. J. Hepatol. 2011:1-6. doi:10.4061/2011/676957
  • Raoof, M., S. J. Corr, C. Zhu, B. T. Cisneros, W. D. Kaluarachchi, S. Phounsavath, L. J. wilson, and S. A. CURLEY. 2014. Gold nanoparticles and radiofrequency in experimental models for hepatocellular carcinoma. Nanomed. Nanotechnol. Biol. Med. 10:1121–30. doi:10.1016/j.nano.2014.03.004.
  • Raoof, M., S. J. Corr, W. D. Kaluarachchi, K. L. Massey, K. Briggs, C. Zhu, M. A. Cheney, L. J. Wilson, and S. A. Curley. 2012. Stability of antibody-conjugated gold nanoparticles in the endolysosomal nanoenvironment: Implications for noninvasive radiofrequency-based cancer therapy. Nanomed. Nanotechnol. Biol. Med. 8:1096–105. doi:10.1016/j.nano.2012.02.001.
  • Rattanadecho, P., and P. Keangin. 2013. 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 Transfer 58:457–70. doi:10.1016/j.ijheatmasstransfer.2012.10.043.
  • Reddy, G., M. R. Dreher, C. Rossmann, B. J. Wood, and D. Haemmerich. 2013. Cytotoxicity of hepatocellular carcinoma cells to hyperthermic and ablative temperature exposures: In vitro studies and mathematical modelling. Int. J. Hyperthermia 29:318–23. doi:10.3109/02656736.2013.792125.
  • Reinhardt, M., P. Brandmaier, D. Seider, M. Kolesnik, S. Jenniskens, R. B. Sequeiros, M. Eibisberger, P. Voglreiter, R. Flanagan, and P. Mariappan. 2017. A prospective development study of software-guided radio-frequency ablation of primary and secondary liver tumors: Clinical intervention modelling, planning and proof for ablation cancer treatment (clinicimppact). Contemp. Clin Trials Commun. 8:25–32. doi:10.1016/j.conctc.2017.08.004.
  • Rejinold, N. S., R. Jayakumar, and Y.-C. Kim. 2015. Radio frequency responsive nano-biomaterials for cancer therapy. J. Controlled Release 204:85–97. doi:10.1016/j.jconrel.2015.02.036.
  • Rejinold, N. S., R. Ranjusha, A. Balakrishnan, N. Mohammed, and R. Jayakumar. 2014a. Gold–chitin–manganese dioxide ternary composite nanogels for radio frequency assisted cancer therapy. RSC Adv. 4:5819–25. doi:10.1039/c3ra45338c.
  • Rejinold, N. S., R. G. Thomas, M. Muthiah, H. J. Lee, Y. Y. Jeong, I.-K. Park, and R. Jayakumar. 2016. Breast tumor targetable Fe3O4 embedded thermo-responsive nanoparticles for radiofrequency assisted drug delivery. J. Biomed. Nanotechnol. 12:43–55. doi:10.1166/jbn.2016.2135.
  • Rejinold, N. S., R. G. Thomas, M. Muthiah, K. Chennazhi, I.-K. Park, Y. Y. Jeong, K. Manzoor, and R. Jayakumar. 2014b. Radio frequency triggered curcumin delivery from thermo and pH responsive nanoparticles containing gold nanoparticles and its in vivo localization studies in an orthotopic breast tumor model. RSC Adv. 4:39408–27. doi:10.1039/C4RA05727A.
  • Ren, Y., H. Qi, Q. Chen, and L. Ruan. 2017. Thermal dosage investigation for optimal temperature distribution in gold nanoparticle enhanced photothermal therapy. Int. J. Heat Mass Transfer 106:212–21. doi:10.1016/j.ijheatmasstransfer.2016.10.067.
  • Rieder, C., T. Kroeger, C. Schumann, and H. K. Hahn. 2011. GPU-based real-time approximation of the ablation zone for radiofrequency ablation. IEEE Trans. Vis. Comput. Graph. 17:1812–21. doi:10.1109/TVCG.2011.207.
  • Roetzel, W., N. Putra, and S. K. Das. 2003. Experiment and analysis for non-Fourier conduction in materials with non-homogeneous inner structure. Int. J. Therm. Sci. 42:541–52. doi:10.1016/S1290-0729(03)00020-6.
  • Rossmann, C., E. Garrett-Mayer, F. Rattay, and D. Haemmerich. 2013. Dynamics of tissue shrinkage during ablative temperature exposures. Physiol. Meas. 35:55. doi:10.1088/0967-3334/35/1/55.
  • Rossmann, C., F. Rattay, and D. Haemmerich. 2012. Platform for patient-specific finite-element modeling and application for radiofrequency ablation. Visual Image Process. Comput. Biomed. 1. doi:10.1615/VisualizImageProcComputatBiomed.2012004898.
  • Sahoo, N., A. Narasimhan, P. Dhar, and S. K. Das. 2018. Non-Fourier thermal transport induced structural hierarchy and damage to collagen ultrastructure subjected to laser irradiation. Int. J. Hyperthermia 34:229–42. doi:10.1080/02656736.2017.1342873.
  • Sahoo, N., S. Ghosh, A. Narasimhan, and S. K. Das. 2014. Investigation of non-Fourier effects in bio-tissues during laser assisted photothermal therapy. Int. J. Therm. Sci. 76:208–20. doi:10.1016/j.ijthermalsci.2013.08.014.
  • Salimpour, M. R., and E. Shirani. 2017. Heat transfer analysis of skin during thermal therapy using thermal wave equation. J. Therm. Biol. 64:7–18. doi:10.1016/j.jtherbio.2016.12.007.
  • Salloum, M., R. Ma, D. Weeks, and L. Zhu. 2008a. Controlling nanoparticle delivery in magnetic nanoparticle hyperthermia for cancer treatment: Experimental study in agarose gel. Int. J. Hyperthermia 24:337–45. doi:10.1080/02656730801907937.
  • Salloum, M., R. Ma, and L. Zhu. 2008b. An in-vivo experimental study of temperature elevations in animal tissue during magnetic nanoparticle hyperthermia. Int. J. Hyperthermia 24:589–601. doi:10.1080/02656730802203377.
  • Sawicki, J. F., H. Luyen, Y. Mohtashami, J. D. Shea, N. Behdad, and S. C. Hagness. 2018. The performance of higher frequency microwave ablation in the presence of perfusion. IEEE Trans. Biomed. Eng. 66:257–62. doi:10.1109/TBME.2018.2836317.
  • Sawicki, J. F., J. D. Shea, N. Behdad, and S. C. Hagness. 2017. The impact of frequency on the performance of microwave ablation. Int. J. Hyperthermia 33:61–68. doi:10.1080/02656736.2016.1207254.
  • Schena, E., P. Saccomandi, and Y. Fong. 2017. Laser ablation for cancer: Past, present and future. J. Funct. Biomater. 8:19. doi:10.3390/jfb8020019.
  • Schumann, C., C. Rieder, J. Bieberstein, A. Weihusen, S. Zidowitz, J. H. Moltz, and T. Preusser. 2010. State of the art in computer-assisted planning, intervention, and assessment of liver-tumor ablation. Crit. Rev.™ Biomed. Eng. 38: 31–52. doi:10.1615/CritRevBiomedEng.v38.i1.40.
  • Schutt, D. J., and D. Haemmerich. 2008. Effects of variation in perfusion rates and of perfusion models in computational models of radio frequency tumor ablation. Med. Phys. 35:3462–70. doi:10.1118/1.2948388.
  • Scott, S. J., V. Salgaonkar, P. Prakash, E. C. Burdette, and C. J. Diederich. 2014. Interstitial ultrasound ablation of vertebral and paraspinal tumours: Parametric and patient-specific simulations. Int. J. Hyperthermia 30:228–44. doi:10.3109/02656736.2014.915992.
  • Sebek, J., N. Albin, R. Bortel, B. Natarajan, and P. Prakash. 2016. Sensitivity of microwave ablation models to tissue biophysical properties: A first step toward probabilistic modeling and treatment planning. Med. Phys. 43:2649–61. doi:10.1118/1.4947482.
  • Seitel, A., M. Engel, C. M. Sommer, B. A. Radeleff, C. Essert‐Villard, C. Baegert, M. Fangerau, K. H. Fritzsche, K. Yung, and H. P. Meinzer. 2011. Computer‐assisted trajectory planning for percutaneous needle insertions. Med. Phys. 38:3246–59. doi:10.1118/1.3590374.
  • Seth, B., and L. De Gray. 2016. Genesis of chronic pain. Anaesth. Intensive Care Med. 17:431–35. doi:10.1016/j.mpaic.2016.06.011.
  • Shao, Y., B. Arjun, H. Leo, and K. Chua. 2017a. A computational theoretical model for radiofrequency ablation of tumor with complex vascularization. Comput. Biol. Med. 89:282–92. doi:10.1016/j.compbiomed.2017.08.025.
  • Shao, Y., B. Arjun, H. Leo, and K. Chua. 2017b. Nano-assisted radiofrequency ablation of clinically extracted irregularly-shaped liver tumors. J. Therm. Biol. 66:101–13. doi:10.1016/j.jtherbio.2017.04.005.
  • Shao, Y., H. Leo, and K. Chua. 2017c. Studying the thermal performance of a bipolar radiofrequency ablation with an improved electrode matrix system: In vitro experiments and modelling. Appl. Therm. Eng. 116:623–35. doi:10.1016/j.applthermaleng.2017.01.073.
  • Sheng, W., S. He, W. J. Seare, and A. Almutairi. 2017. Review of the progress toward achieving heat confinement—the holy grail of photothermal therapy. J. Biomed. Opt. 22:080901. doi:10.1117/1.JBO.22.8.080901.
  • Shih, T.-C., H.-L. Liu, and A. T.-L. Horng. 2006. Cooling effect of thermally significant blood vessels in perfused tumor tissue during thermal therapy. Int. Commun. Heat Mass Transfer 33:135–41. doi:10.1016/j.icheatmasstransfer.2005.08.003.
  • Shukla, N. D., A. L. Ho, A. V. Pendharkar, E. S. Sussman, and C. H. Halpern. 2017. Laser interstitial thermal therapy for the treatment of epilepsy: Evidence to date. Neuropsychiatr. Dis. Treat. 13:2469. doi:10.2147/NDT.S139544.
  • Silva, D., M. Sharma, and G. H. Barnett. 2016. Laser ablation vs open resection for deep-seated tumors: Evidence for laser ablation. Neurosurgery 63:15–26. doi:10.1227/NEU.0000000000001289.
  • Silva, D., M. Sharma, R. Juthani, A. Meola, and G. H. Barnett. 2017. Magnetic resonance thermometry and laser interstitial thermal therapy for brain tumors. Neurosurgery Clinics 28:525–33. doi:10.1016/j.nec.2017.05.015.
  • Singh, S. 2018. Thermal analysis of temperature-controlled radiofrequency ablation of cancerous tissue. Doctoral Dissertation, Indian Institute of Technology Ropar.
  • Singh, S., A. Bhowmik, and R. Repaka. 2015. Radiofrequency ablation of malignant breast tumor: A numerical study. Proc. 23rd National Heat and Mass Transfer Conference and 1st International ISHMT-ASTFE Heat and Mass Transfer Conference, Thiruvananthapuram, India, 17–20.
  • Singh, S., A. Bhowmik, and R. Repaka. 2016. Thermal analysis of induced damage to the healthy cell during RFA of breast tumor. J. Therm. Biol. 58:80–90. doi:10.1016/j.jtherbio.2016.04.002.
  • Singh, S., and R. Melnik. 2019a. Computational analysis of pulsed radiofrequency ablation in treating chronic pain. International Conference on Computational Science, 436–50, Springer. doi:10.1007/978-3-030-22747-0_33.
  • Singh, S., and R. Melnik. 2019b. Coupled thermo-electro-mechanical models for thermal ablation of biological tissues and heat relaxation time effects. Phys. Med. Biol. 64:245008. doi:10.1088/1361-6560/ab4cc5.
  • Singh, S., and R. Melnik. 2019c. Effects of heterogeneous surrondings on the efficacy of continuous radiofrequency for pain relief. International Conference on Bioinformatics and Neurosciences (ICoBN 2019), Vancouver, Canada, August 26-28.
  • Singh, S., and R. Melnik. 2019d. Radiofrequency ablation for treating chronic pain of bones: Effects of nerve locations. International Work-Conference on Bioinformatics and Biomedical Engineering, 418–29, Springer. doi:10.1007/978-3-030-17935-9_38.
  • Singh, S., and R. Repaka. 2015. Pre-clinical modelling and simulation of hepatic radiofrequency ablation. Proceeding COMSOL Conference 2015, Pune, India, October 29-30.
  • Singh, S., and R. Repaka. 2016. Effects of target temperature on ablation volume during temperature-controlled RFA of breast tumor. Proceeding COMSOL Conference 2016, Bangalore, India, October 20-21.
  • Singh, S., and R. Repaka. 2017a. Effect of different breast density compositions on thermal damage of breast tumor during radiofrequency ablation. Appl. Therm. Eng. 125:443–51. doi:10.1016/j.applthermaleng.2017.07.057.
  • Singh, S., and R. Repaka. 2017b. Effect of heterogeneous blood perfusion during RFA of breast tumor. ISHMT Digital Library. Begel House Inc.
  • Singh, S., and R. Repaka. 2017c. Temperature-controlled radiofrequency ablation of different tissues using two-compartment models. Int. J. Hyperthermia 33:122–34. doi:10.1080/02656736.2016.1223890.
  • Singh, S., and R. Repaka. 2018a. Numerical investigation of convective cooling in minimizing skin burns during radiofrequency ablation of breast tumor. Sādhanā 43:90. doi:10.1007/s12046-018-0872-4.
  • Singh, S., and R. Repaka. 2018b. Numerical study to establish relationship between coagulation volume and target tip temperature during temperature-controlled radiofrequency ablation. Electromagn. Biol. Med. 37:13–22. doi:10.1080/15368378.2017.1422262.
  • Singh, S., and R. Repaka. 2018c. Parametric sensitivity analysis of critical factors affecting the thermal damage during RFA of breast tumor. Int. J. Therm. Sci. 124:366–74. doi:10.1016/j.ijthermalsci.2017.10.032.
  • Singh, S., and R. Repaka. 2018d. Quantification of thermal injury to the healthy tissue due to imperfect electrode placements during radiofrequency ablation of breast tumor. J. Eng. Sci. Med. Diagn. Ther. 1:011002. doi:10.1115/1.4038237.
  • Singh, S., and R. Repaka. 2018e. Thermal characterization using fourier and non-Fourier conduction during radiofrequency ablation of breast tumor. Multiphase Sci. Technol. 30: doi: 10.1615/MultScienTechn.2018021352.
  • Singh, S., R. Repaka, and A. Al‐Jumaily. 2019. Sensitivity analysis of critical parameters affecting the efficacy of microwave ablation using Taguchi method. Int. J. of RF Microwave Comput.‐Aided Eng. 29:e21581. doi:10.1002/mmce.21581.
  • Soler, L., S. Nicolau, P. Pessaux, D. Mutter, and J. Marescaux. 2014. Real-time 3D image reconstruction guidance in liver resection surgery. Hepatobiliary Surg. Nutr. 3:73.
  • Soloman, M., M. N. Mekhail, and N. Mekhail. 2010. Radiofrequency treatment in chronic pain. Expert Rev. Neurother. 10:469–74. doi:10.1586/ern.09.153.
  • Sommer, C. M., S. A. Sommer, T. Mokry, T. Gockner, D. Gnutzmann, N. Bellemann, A. Schmitz, B. A. Radeleff, H. U. Kauczor, and U. Stampfl. 2013. Quantification of tissue shrinkage and dehydration caused by microwave ablation: Experimental study in kidneys for the estimation of effective coagulation volume. J. Vas. Interventional Radiol 24:1241–48. doi:10.1016/j.jvir.2013.04.008.
  • Soni, S., H. Tyagi, R. A. Taylor, and A. Kumar. 2015a. Experimental and numerical investigation of heat confinement during nanoparticle-assisted thermal therapy. Int. Commun. Heat Mass Transfer 69:11–17. doi:10.1016/j.icheatmasstransfer.2015.10.001.
  • Soni, S., H. Tyagi, R. A. Taylor, and A. Kumar. 2015b. The influence of tumour blood perfusion variability on thermal damage during nanoparticle-assisted thermal therapy. Int. J. Hyperthermia 31:615–25. doi:10.3109/02656736.2015.1040470.
  • Srebro, D., S. Vuckovic, A. Milovanovic, J. Kosutic, K. Savic Vujovic, and M. Prostran. 2017. Magnesium in pain research: State of the art. Curr. Med. Chem. 24:424–34. doi:10.2174/0929867323666161213101744.
  • Stafford, R. J., D. Fuentes, A. A. Elliott, J. S. Weinberg, and K. Ahrar. 2010. Laser-induced thermal therapy for tumor ablation. Crit. Rev.™ Biomed. Eng. 38:79–100, doi:10.1615/CritRevBiomedEng.v38.i1.70.
  • Strunin, D., R. Melnik, and A. Roberts. 2001. Coupled thermomechanical waves in hyperbolic thermoelasticity. J. Therm. Stresses 24:121–40. doi:10.1080/01495730150500433.
  • Surleraux, A., R. Lepert, J.-P. Pernot, P. Kerfriden, and S. Bigot. 2020. Machine learning-based reverse modeling approach for rapid tool shape optimization in die-sinking micro electro discharge machining. J. Comput. Inf. Sci. Eng. 20: 031002. doi:10.1115/1.4045956.
  • Tiemann, L., V. D. Hohn, S. T. Dinh, E. S. May, M. M. Nickel, J. Gross, and M. Ploner. 2018. Distinct patterns of brain activity mediate perceptual and motor and autonomic responses to noxious stimuli. Nat. Commun. 9:4487. doi:10.1038/s41467-018-06875-x.
  • Trujillo, M., and E. Berjano. 2013. Review of the mathematical functions used to model the temperature dependence of electrical and thermal conductivities of biological tissue in radiofrequency ablation. Int. J. Hyperthermia 29:590–97. doi:10.3109/02656736.2013.807438.
  • Trujillo, M., J. Bon, and E. Berjano. 2017. Computational modelling of internally cooled wet (ICW) electrodes for radiofrequency ablation: Impact of rehydration, thermal convection and electrical conductivity. Int. J. Hyperthermia 33:624–34. doi:10.1080/02656736.2017.1303751.
  • Trujillo, M., J. Bon, M. José Rivera, F. Burdío, and E. Berjano. 2016. Computer modelling of an impedance-controlled pulsing protocol for RF tumour ablation with a cooled electrode. Int. J. Hyperthermia 32:931–39. doi:10.1080/02656736.2016.1190868.
  • Truong, V. G., S. Jeong, and H. W. Kang. 2018. Computational analysis of linear energy modulation for laser thermal coagulation. Biomed. Opt. Express 9:2575–87. doi:10.1364/BOE.9.002575.
  • Tzou, D. Y. 1995. The generalized lagging response in small-scale and high-rate heating. Int. J. Heat Mass Transfer 38:3231–40. doi:10.1016/0017-9310(95)00052-B.
  • Van Rhoon, G. C. 2016. Is CEM43 still a relevant thermal dose parameter for hyperthermia treatment monitoring? Int. J. Hyperthermia 32:50–62. doi:10.3109/02656736.2015.1114153.
  • Vedavarz, A., S. Kumar, and M. K. Moallemi. 1994. Significance of non-Fourier heat waves in conduction. J. Heat Transfer 116:221–26. doi:10.1115/1.2910859.
  • Verhaart, R. F., G. M. Verduijn, V. Fortunati, Z. Rijnen, T. Van Walsum, J. F. Veenland, and M. M. Paulides. 2015. Accurate 3D temperature dosimetry during hyperthermia therapy by combining invasive measurements and patient-specific simulations. Int. J. Hyperthermia 31:686–92. doi:10.3109/02656736.2015.1052855.
  • Vernotte, P. 1958. Les paradoxes de la theorie continue de l’equation de la chaleur. Compt. Rendu 246:3154–55.
  • Vogel, A., and V. Venugopalan. 2003. Mechanisms of pulsed laser ablation of biological tissues. Chem. Rev. 103:577–644. doi:10.1021/cr010379n.
  • Voglreiter, P., P. Mariappan, M. Pollari, R. Flanagan, R. B. Sequeiros, R. H. Portugaller, J. Fütterer, D. Schmalstieg, M. Kolesnik, and M. Moche. 2018. RFA guardian: Comprehensive simulation of radiofrequency ablation treatment of liver tumors. Sci. Rep. 8:787. doi:10.1038/s41598-017-18899-2.
  • Wang, H., W. Dai, and R. Melnik. 2006a. A finite difference method for studying thermal deformation in a double-layered thin film exposed to ultrashort pulsed lasers. Int. J. Therm. Sci. 45:1179–96. doi:10.1016/j.ijthermalsci.2006.03.001.
  • Wang, H., W. Dai, R. Nassar, and R. Melnik. 2006b. A finite difference method for studying thermal deformation in a thin film exposed to ultrashort-pulsed lasers. Int. J. Heat Mass Transfer 49:2712–23. doi:10.1016/j.ijheatmasstransfer.2006.01.013.
  • Wang, K., F. Tavakkoli, S. Wang, and K. Vafai. 2015. Analysis and analytical characterization of bioheat transfer during radiofrequency ablation. J. Biomech. 48:930–40. doi:10.1016/j.jbiomech.2015.02.023.
  • Wang, S.-L., H. Qi, Y.-T. Ren, Q. Chen, and L.-M. Ruan. 2018a. Optimal temperature control of tissue embedded with gold nanoparticles for enhanced thermal therapy based on two-energy equation model. J. Therm. Biol. 74:264–74. doi:10.1016/j.jtherbio.2018.04.011.
  • Wang, Y. C., T. C.-H. Chan, and A. V. Sahakian. 2018b. Real-time estimation of lesion depth and control of radiofrequency ablation within ex vivo animal tissues using a neural network. Int. J. Hyperthermia 34:1104–13. doi:10.1080/02656736.2017.1416495.
  • Wang, Z., H. Luo, S. Coleman, and A. Cuschieri. 2016. Bicomponent conformal electrode for radiofrequency sequential ablation and circumferential separation of large tumors in solid organs: Development and in vitro evaluation. IEEE Trans. Biomed. Eng. 64:699–705. doi:10.1109/TBME.2016.2573043.
  • Ward, R. C., T. T. Healey, and D. E. Dupuy. 2013. Microwave ablation devices for interventional oncology. Expert Rev. Med. Devices 10:225–38. doi:10.1586/erd.12.77.
  • Widmer, L. A., and J. Stelling. 2018. Bridging intracellular scales by mechanistic computational models. Curr. Opin. Biotechnol. 52:17–24. doi:10.1016/j.copbio.2018.02.005.
  • Woeppel, K., Q. Yang, and X. T. Cui. 2017. Recent advances in neural electrode–tissue interfaces. Curr. Opin. Biomed. Eng. 4:21–31. doi:10.1016/j.cobme.2017.09.003.
  • Won, S. M., E. Song, J. Zhao, J. Li, J. Rivnay, and J. A. Rogers. 2018. Recent advances in materials, devices, and systems for neural interfaces. Ad. Mater. 30:1800534. doi:10.1002/adma.201800534.
  • Wongchadakul, P., P. Rattanadecho, and T. Wessapan. 2018. Implementation of a thermomechanical model to simulate laser heating in shrinkage tissue (effects of wavelength, laser irradiation intensity, and irradiation beam area). Int. J. Therm. Sci. 134:321–36. doi:10.1016/j.ijthermalsci.2018.08.008.
  • Wright, N. T. 2015. Quantitative models of thermal damage to cells and tissues. In Heat transfer and fluid flow in biological processes, edited by Sid M. Becker and Andrey V. Kuznetsov, pp. 59–76. Academic Press United States. doi:10.1016/B978-0-12-408077-5.00003-1
  • Wu, W., S. Wu, Z. Zhou, R. Zhang, and Y. Zhang. 2017. 3D liver tumor segmentation in CT images using improved fuzzy C-means and graph cuts. BioMed Res. Int. 2017: doi: 10.1155/2017/5207685.
  • Wu, W., Z. Zhou, S. Wu, and Y. Zhang. 2016. Automatic liver segmentation on volumetric CT images using supervoxel-based graph cuts. Comput. Math. Methods Med. 2016: doi: 10.1155/2016/9093721.
  • Xu, F., M. Lin, and T. Lu. 2010. Modeling skin thermal pain sensation: Role of non-Fourier thermal behavior in transduction process of nociceptor. Comput. Biol. Med. 40:478–86. doi:10.1016/j.compbiomed.2010.03.002.
  • Xu, F., T. Wen, T. LU, and K. Seffen. 2008. Modeling of nociceptor transduction in skin thermal pain sensation. J. Biomech. Eng. 130:041013. doi:10.1115/1.2939370.
  • Xu, Y., M. A. Moser, E. Zhang, W. Zhang, and B. Zhang. 2019. Large and round ablation zones with microwave ablation: A preliminary study of an optimal aperiodic tri-slot coaxial antenna with the π-matching network section. Int. J. Therm. Sci. 140:539–48. doi:10.1016/j.ijthermalsci.2019.03.022.
  • Yang, D., M. C. Converse, D. M. Mahvi, and J. G. Webster. 2006. Measurement and analysis of tissue temperature during microwave liver ablation. IEEE Trans. Biomed. Eng. 54:150–55. doi:10.1109/TBME.2006.884647.
  • Yang, D., M. C. Converse, D. M. Mahvi, and J. G. Webster. 2007. Expanding the bioheat equation to include tissue internal water evaporation during heating. IEEE Trans. Biomed. Eng. 54:1382–88. doi:10.1109/TBME.2007.890740.
  • Yildiz, F., and A. T. Özdemir. 2019. Prediction of laser-induced thermal damage with artificial neural networks. Laser Phys. 29:075205. doi:10.1088/1555-6611/ab183b.
  • Yoon, J., J. Cho, N. Kim, D. D. Kim, E. Lee, C. Cheon, and Y. Kwon. 2011. High‐frequency microwave ablation method for enhanced cancer treatment with minimized collateral damage. Int. J. Cancer 129:1970–78. doi:10.1002/ijc.25845.
  • Zhang, B., M. A. Moser, E. M. Zhang, Y. Luo, C. Liu, and W. Zhang. 2016. A review of radiofrequency ablation: Large target tissue necrosis and mathematical modelling. Physica Medica 32:961–71. doi:10.1016/j.ejmp.2016.07.092.
  • Zhang, B., M. A. Moser, E. M. Zhang, Y. Luo, and W. Zhang. 2017. A new approach to feedback control of radiofrequency ablation systems for large coagulation zones. Int. J. Hyperthermia 33:367–77. doi:10.1080/02656736.2016.1263365.
  • Zhang, J., and S. Chauhan. 2019. Neural network methodology for real-time modelling of bio-heat transfer during thermo-therapeutic applications. Artif. Intell. Med. 101:101728. doi:10.1016/j.artmed.2019.101728.
  • Zhang, J., Y. Zhong, and C. GU. 2019a. Neural network modelling of soft tissue deformation for surgical simulation. Artif. Intell. Med. 97:61–70. doi:10.1016/j.artmed.2018.11.001.
  • Zhang, M., Z. Zhou, S. Wu, L. Lin, H. Gao, and Y. Feng. 2015. Simulation of temperature field for temperature-controlled radio frequency ablation using a hyperbolic bioheat equation and temperature-varied voltage calibration: A liver-mimicking phantom study. Phys. Med. Biol. 60:9455. doi:10.1088/0031-9155/60/24/9455.
  • Zhang, R., S. Wu, W. Wu, H. Gao, and Z. Zhou. 2019b. Computer-assisted needle trajectory planning and mathematical modeling for liver tumor thermal ablation: A review. Math. Biosci. Eng. 16:4846–72. doi:10.3934/mbe.2019244.
  • Zhang, R., Z. Zhou, W. Wu, -C.-C. Lin, P.-H. Tsui, and S. Wu. 2018. An improved fuzzy connectedness method for automatic three-dimensional liver vessel segmentation in CT images. J. Healthc. Eng. 2018: doi: 10.1155/2018/2376317.
  • Zhang, S., W. Dai, H. Wang, and R. V. Melnik. 2008. A finite difference method for studying thermal deformation in a 3D thin film exposed to ultrashort pulsed lasers. Int. J. Heat Mass Transfer 51:1979–95. doi:10.1016/j.ijheatmasstransfer.2007.06.040.
  • Zhao, J., P. Lee, M. J Wallace, and M. P Melancon. 2015. Gold nanoparticles in cancer therapy: Efficacy, biodistribution, and toxicity. Curr. Pharm. Des. 21:4240–51. doi:10.2174/1381612821666150901103032.
  • Zhu, L. 2009. Heat transfer applications in biological systems. Biomed. Eng. Des. Handb. 1:2.33–2.67.
  • Zhu, Y., and T. Lu. 2010. A multi-scale view of skin thermal pain: From nociception to pain sensation. Philos. Trans. Royal Soci. A 368:521–59. doi:10.1098/rsta.2009.0234.
  • Ziemlewicz, T. J., S. A. Wells, M. A. Lubner, A. I. Musat, J. L. Hinshaw, A. R. Cohn, and F. T. Lee. 2014. Microwave ablation of giant hepatic cavernous hemangiomas. Cardiovasc. Intervent. Radiol. 37:1299–305. doi:10.1007/s00270-014-0934-x.
  • Zorbas, G., and T. Samaras. 2013. Parametric study of radiofrequency ablation in the clinical practice with the use of two-compartment numerical models. Electromagn. Biol. Med. 32:236–43. doi:10.3109/15368378.2013.776435.
  • Zorbas, G., and T. Samaras. 2014. Simulation of radiofrequency ablation in real human anatomy. Int. J. Hyperthermia 30:570–78. doi:10.3109/02656736.2014.968639.
  • Zorbas, G., and T. Samaras. 2015. A study of the sink effect by blood vessels in radiofrequency ablation. Comput. Biol. Med. 57:182–86. doi:10.1016/j.compbiomed.2014.12.014.
  • Zygomalas, A., and I. Kehagias. 2019. Up-to-date intraoperative computer assisted solutions for liver surgery. World J. Gastrointest Surg. 11:1. doi:10.4240/wjgs.v11.i1.1.

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