Design by stochastic simulations of the thermal ablation treatment of tumors with high intensity focused ultrasound

References

• J. E. Kennedy, G. R. Ter Haar and D. Cranston, “High intensity focused ultrasound: surgery of the future?,” Br. J. Radiol., vol. 76, no. 909, pp. 590–599, Sep. 2003. DOI: 10.1259/bjr/17150274.
   PubMed Web of Science ®Google Scholar
• F. A. Jolesz, “MRI-guided focused ultrasound surgery,” Annu. Rev. Med., vol. 60, pp. 417–430, Feb. 2009. DOI: 10.1146/annurev.med.60.041707.170303.
   PubMed Web of Science ®Google Scholar
• C. R. Hill and G. R. Ter Haar, “High intensity focused ultrasound—potential for cancer treatment,” Br. J. Radiol., vol. 68, no. 816, pp. 1296–1303, Dec. 1995. DOI: 10.1259/0007-1285-68-816-1296.
   PubMed Web of Science ®Google Scholar
• P. Wust, et al., “Hyperthermia in combined treatment of cancer,” Lancet Oncol., vol. 3, no. 8, pp. 487–497, 2002. Aug DOI: 10.1016/S1470-2045(02)00818-5.
   PubMed Web of Science ®Google Scholar
• R. W. Habash, R. Bansal, D. Krewski and H. T. Alhafid, “Thermal therapy, part 1: an introduction to thermal therapy,” Crit. Rev. Biomed. Eng., vol. 34, no. 6, pp. 459–489, 2006. DOI: 10.1615/CritRevBiomedEng.v34.i6.20.
   PubMedGoogle Scholar
• R. W. Habash, R. Bansal, D. Krewski and H. T. Alhafid, “Thermal therapy, part 2: hyperthermia techniques,” Crit. Rev. Biomed. Eng., vol. 34, no. 6, pp. 491–542, 2006. DOI: 10.1615/CritRevBiomedEng.v34.i6.30.
   PubMedGoogle Scholar
• R. W. Habash, R. Bansal, D. Krewski and H. T. Alhafid, “Thermal therapy, Part III: ablation techniques,” Crit. Rev. Biomed. Eng., vol. 35, no. 1–2, pp. 37–121, 2007. DOI: 10.1615/CritRevBiomedEng.v35.i1-2.20.
   PubMedGoogle Scholar
• M. Dewhirst, J. Abraham and B. Viglianti, “Evolution of thermal dosimetry for application of hyperthermia to treat cancer,” in Advances in Heat Transfer, vol. 47. Cambridge, Massachusetts: Elsevier, 2015, pp. 397–421.
   Google Scholar
• X. Liu, J. Li, X. Gong and D. Zhang, “Nonlinear absorption in biological tissue for high intensity focused ultrasound,” Ultrasonics, vol. 44, pp. e27–e30, Dec. 2006. DOI: 10.1016/j.ultras.2006.06.035.
   PubMed Web of Science ®Google Scholar
• V. Suomi, J. Jaros, B. Treeby and R. O. Cleveland, “Full modeling of high-intensity focused ultrasound and thermal heating in the kidney using realistic patient models,” IEEE Trans. Biomed. Eng., vol. 65, no. 5, pp. 969–979, Jul. 2018. DOI: 10.1109/TBME.2017.2732684.
   PubMed Web of Science ®Google Scholar
• H. E. Cline, et al., “MR-guided focused ultrasound surgery,” J. Comput. Assist. Tomogr., vol. 16, no. 6, pp. 956–965, Nov. 1992. DOI: 10.1097/00004728-199211000-00024.
   PubMed Web of Science ®Google Scholar
• V. A. Khokhlova, et al., “Effects of nonlinear propagation, cavitation, and boiling in lesion formation by high intensity focused ultrasound in a gel phantom,” J. Acoust. Soc. Am., vol. 119, no. 3, pp. 1834–1848, Feb. 2006. DOI: 10.1121/1.2161440.
   PubMed Web of Science ®Google Scholar
• Z. Izadifar, Z. Izadifar, D. Chapman and P. Babyn, “An introduction to high intensity focused ultrasound: systematic review on principles, devices, and clinical applications,” J. Clin. Med., vol. 9, no. 2, p. 460, Feb. 2020. DOI: 10.3390/jcm9020460.
   PubMed Web of Science ®Google Scholar
• J. R. McLaughlan, “An investigation into the use of cavitation for the optimisation of high intensity focused ultrasound (HIFU) treatments,” Ph.D. dissertation, Institute of Cancer Research, University of London, London, UK, 2008.
   Google Scholar
• J. K. Enholm, et al., “Improved volumetric MR-HIFU ablation by robust binary feedback control,” IEEE Trans. Biomed. Eng., vol. 57, no. 1, pp. 103–113, Jan. 2010. DOI: 10.1109/TBME.2009.2034636.
   PubMed Web of Science ®Google Scholar
• F. C. Vimeux, et al., “Real-time control of focused ultrasound heating based on rapid MR thermometry,” Invest. Radiol., vol. 34, no. 3, pp. 190–193, Mar. 1999. DOI: 10.1097/00004424-199903000-00006.
   PubMed Web of Science ®Google Scholar
• R. Salomir, et al., “Hyperthermia by MR‐guided focused ultrasound: accurate temperature control based on fast MRI and a physical model of local energy deposition and heat conduction,” Magn. Reson. Med., vol. 43, no. 3, pp. 342–347, Mar. 2000. DOI: 10.1002/(SICI)1522-2594(200003)43:3 < 342::AID-MRM4 > 3.0.CO;2-6.
   PubMed Web of Science ®Google Scholar
• D. De Senneville, C. Mougenot and C. T. Moonen, “Real‐time adaptive methods for treatment of mobile organs by MRI‐controlled high‐intensity focused ultrasound,” Magn. Reson. Med., vol. 57, no. 2, pp. 319–330, 2007. DOI: 10.1002/mrm.21124.
   PubMed Web of Science ®Google Scholar
• C. Mougenot, et al., “Three‐dimensional spatial and temporal temperature control with MR thermometry‐guided focused ultrasound (MRgHIFU),” Magn. Reson. Med., vol. 61, no. 3, pp. 603–614, 2009. DOI: 10.1002/mrm.21887.
   PubMed Web of Science ®Google Scholar
• M. Köhler, et al., “Volumetric HIFU ablation under 3D guidance of rapid MRI thermometry,” Med. Phys., vol. 36, no. 8, pp. 3521–3535, 2009. DOI: 10.1118/1.3152112.
   PubMed Web of Science ®Google Scholar
• I. Dragonu, et al., “Non‐invasive determination of tissue thermal parameters from high intensity focused ultrasound treatment monitored by volumetric MRI thermometry,” NMR Biomed., vol. 22, no. 8, pp. 843–851, 2009. DOI: 10.1002/nbm.1397.
   PubMed Web of Science ®Google Scholar
• B. Quesson, et al., “Real‐time volumetric MRI thermometry of focused ultrasound ablation in vivo: a feasibility study in pig liver and kidney,” NMR Biomed., vol. 24, no. 2, pp. 145–153, 2011. DOI: 10.1002/nbm.1563.
   PubMed Web of Science ®Google Scholar
• C. Mougenot, et al., “MR‐HIFU enhanced volumetric ablations,” in AIP Conference Proceedings, vol. 1359. American Institute of Physics, 2011.
   Google Scholar
• J. Zhang, et al., “Volumetric MRI‐guided high‐intensity focused ultrasound for noninvasive, in vivo determination of tissue thermal conductivity: initial experience in a pig model,” J. Magn. Reson. Imaging, vol. 37, no. 4, pp. 950–957, 2013. DOI: 10.1002/jmri.23878.
   PubMed Web of Science ®Google Scholar
• B. Zaporzan, et al., “MatMRI and MatHIFU: software toolboxes for real-time monitoring and control of MR-guided HIFU,” J. Ther. Ultrasound, vol. 1, no. 1, p. 12, 2013. DOI: 10.1186/2050-5736-1-7.
   PubMedGoogle Scholar
• Mougenot, C., “L'asservissement par IRM d‘un réseau matriciel ultrasonore et ses applications thérapeutiques,” Doctoral dissertation, Bordeaux 1, 2005.
   Google Scholar
• D. Elbes, et al., “Pre-clinical study of in vivo magnetic resonance-guided bubble-enhanced heating in pig liver,” Ultrasound. Med. Biol., vol. 39, no. 8, pp. 1388–1397, 2013. DOI: 10.1016/j.ultrasmedbio.2013.01.014.
   PubMed Web of Science ®Google Scholar
• D. Elbes, et al., “Magnetic resonance imaging for the exploitation of bubble-enhanced heating by high-intensity focused ultrasound: a feasibility study in ex vivo liver,” Ultrasound. Med. Biol., vol. 40, no. 5, pp. 956–964, 2014. DOI: 10.1016/j.ultrasmedbio.2013.11.019.
   PubMed Web of Science ®Google Scholar
• D. Elbes, “Thermothérapies par ultrasons focalisés et radiofréquences guidées par imagerie de résonance magnétique,” Doctoral dissertation, Bordeaux 1, 2012.
   Google Scholar
• H. Wan, J. Aarsvold, M. O'Donnell and C. Cain, “Thermal dose optimization for ultrasound tissue ablation,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 46, no. 4, pp. 913–928, Jul. 1999. DOI: 10.1109/58.775658.
   PubMed Web of Science ®Google Scholar
• X. Liu and M. Almekkawy, “An optimized control approach for HIFU tissue ablation using pde constrained optimization method,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 68, no. 5, pp. 1555–1568, Nov. 2021. DOI: 10.1109/TUFFC.2020.3040362.
   PubMed Web of Science ®Google Scholar
• T. Loulou and E. Scott, “Thermal dose optimization in hyperthermia treatments by using the conjugate gradient method,” Numer. Heat Transfer: Part A: Appl., vol. 42, no. 7, pp. 661–683, 2002. DOI: 10.1080/10407780290059756.
   Web of Science ®Google Scholar
• J. Zhang, et al., “Fast computation of desired thermal dose: application to focused ultrasound-induced lesion planning,” Numer. Heat Transfer Part A: Appl., vol. 77, no. 6, pp. 666–682, 2020. DOI: 10.1080/10407782.2020.1714325.
   Web of Science ®Google Scholar
• J. Kaipio and E. Somersalo, Statistical and Computational Inverse Problems, vol. 160. New York, USA: Springer Science & Business Media, 2006.
   Google Scholar
• J. P. Kaipio and C. Fox, “The Bayesian framework for inverse problems in heat transfer,” Heat Transfer Eng., vol. 32, no. 9, pp. 718–753, Apr. 2011. DOI: 10.1080/01457632.2011.525137.
   Web of Science ®Google Scholar
• M. N. Özişik and H. R. B. Orlande, Inverse Heat Transfer: Fundamentals and Applications, 2nd ed., Boca Raton, FL: CRC Press, 2021.
   Google Scholar
• F. C. Henriques, Jrand A. R. Moritz, “Studies of thermal injury: i. The conduction of heat to and through skin and the temperatures attained therein. A theoretical and an experimental investigation,” Am. J. Pathol., vol. 23, no. 4, pp. 530, Jul. 1947.
   PubMed Web of Science ®Google Scholar
• A. R. Moritz and F. Henriques, Jr. “Studies of thermal injury: II. The relative importance of time and surface temperature in the causation of cutaneous burns,” Am. J. Pathol., vol. 23, no. 5, p. 695, 1947.
   PubMed Web of Science ®Google Scholar
• J. A. Pearce, “Relationship between Arrhenius models of thermal damage and the CEM 43 thermal dose,” in Energy-Based Treatment of Tissue and Assessment, vol. 7181, Feb. 2009, pp. 35–49, DOI: 10.1117/12.807999.
   Google Scholar
• J. A. Pearce, “Thermal Dose Models: Irreversible Alterations in Tissues,” in Physics of Thermal Therapy, M. H. Levitt and C. L. Charles, Eds. Boca Raton, FL, USA: CRC Press, 2016, pp. 40–57.
   Google Scholar
• S. Beacher, et al., “Theory and numerical simulation of thermochemical ablation,” Numer. Heat Transfer Part A: Appl., vol. 66, no. 2,pp. 131–143, 2014. DOI: 10.1080/10407782.2013.869092.
   Web of Science ®Google Scholar
• D. Gamerman and H. F. Lopes, Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference. Boca Raton, FL, USA: CRC Press, 2006.
   Google Scholar
• T. Cui, “Bayesian calibration of geothermal reservoir models via Markov Chain Monte Carlo,” Ph.D. thesis, The University of Auckland, Auckland, New Zealand, 2010.
   Google Scholar
• L. F. S. Ferreira, L. A. Bermeo Varon, H. R. B. Orlande and B. Lamien, “Design Under Uncertainties of the Thermal Ablation Treatment of Skin Cancer,” ASME J. Heat Mass Transfer, vol. 145, no. 3, p. 031202, Dec. 2023. DOI: 10.1115/1.4055821.
   Web of Science ®Google Scholar
• L. E. Kinsler, A. R. Frey, A. B. Coppens and J. V. Sanders, Fundamentals of Acoustics. New York, USA: John Wiley & Sons, 2000.
   Google Scholar
• A. D. Pierce, Acoustics: An Introduction to Its Physical Principles and Applications. Berlin, Germany: Springer, 2019.
   Google Scholar
• B. E. Treeby and B. T. Cox, “k-Wave: MATLAB toolbox for the simulation and reconstruction of photoacoustic wave fields,” J. Biomed. Opt., vol. 15, no. 2, p. 021314, Mar. 2010. DOI: 10.1117/1.3360308.
   PubMed Web of Science ®Google Scholar
• K. Wang, E. Teoh, J. Jaros and B. E. Treeby, “Modelling nonlinear ultrasound propagation in absorbing media using the k-Wave toolbox: experimental validation,” in 2012 IEEE International Ultrasonics Symposium, Oct. 2012, pp. 523–526. DOI: 10.1109/ULTSYM.2012.0130.
   Google Scholar
• B. E. Treeby, J. Jaros, D. Rohrbach and B. Cox, “Modelling elastic wave propagation using the k-wave MATLAB toolbox,” in 2014 IEEE International Ultrasonics Symposium, Sep. 2014, pp. 146–149. DOI: 10.1109/ULTSYM.2014.0037.
   Google Scholar
• E. Martin, J. Jaros and B. E. Treeby, “Experimental validation of k-wave: nonlinear wave propagation in layered, absorbing fluid media,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 67, no. 1, pp. 81–91, Sep. 2020. DOI: 10.1109/TUFFC.2019.2941795.
   PubMed Web of Science ®Google Scholar
• E. Martin, Y. T. Ling and B. E. Treeby, “Simulating focused ultrasound transducers using discrete sources on regular Cartesian grids,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 63, no. 10, pp. 1535–1542, Aug. 2016. DOI: 10.1109/TUFFC.2016.2600862.
   PubMed Web of Science ®Google Scholar
• B. E. Treeby, J. Jaros, A. P. Rendell and B. Cox, “Modelling nonlinear ultrasound propagation in heterogeneous media with power law absorption using a k-space pseudo spectral method,” J. Acoust. Soc. Am., vol. 131, no. 6, pp. 4324–4336, Apr. 2012. DOI: 10.1121/1.4712021.
   PubMed Web of Science ®Google Scholar
• H. H. Pennes, “Analysis of tissue and arterial blood temperatures in the resting human forearm,” J. Appl. Physiol., vol. 1, no. 2, pp. 93–122, Aug. 1948. DOI: 10.1152/jappl.1948.1.2.93.
   PubMed Web of Science ®Google Scholar
• Y. F. Zhou, “High intensity focused ultrasound in clinical tumor ablation,” World J. Clin. Oncol., vol. 2, no. 1, pp. 8–27, Jan. 2011. DOI: 10.5306/wjco.v2.i1.8.
   PubMedGoogle Scholar
• C. Rossmann and D. Haemmerich, “Review of temperature dependence of thermal properties, dielectric properties, and perfusion of biological tissues at hyperthermic and ablation temperatures,” Crit. Rev. ™ Biomed. Eng., vol. 42, no. 6, pp. 787-800, 2014. DOI: 10.1615/CritRevBiomedEng.2015012486.
   Google Scholar
• S. A. Sapareto and W. C. Dewey, “Thermal dose determination in cancer therapy,” Int. J. Radiat. Oncol. Biol. Phys., vol. 10, no. 6, pp. 787–800, Apr. 1984. DOI: 10.1016/0360-3016(84)90379-1.
   PubMed Web of Science ®Google Scholar
• G. C. Van Rhoon, T. Samaras, P. S. Yarmolenko, M. W. Dewhirst, E. Neufeld and N. Kuster, “CEM43° C thermal dose thresholds: a potential guide for magnetic resonance radiofrequency exposure levels?,” Eur. Radiol., vol. 23, no. 8, pp. 2215–2227, Apr. 2013. DOI: 10.1007/s00330-013-2825-y.
   PubMed Web of Science ®Google Scholar
• B. R. Loiola, H. R. Orlande and G. S. Dulikravich, “Thermal damage during ablation of biological tissues,” Numer. Heat Transfer, Part A: Appl., vol. 73, no. 10, pp. 685–701, Jun. 2018. DOI: 10.1080/10407782.2018.1464794.
   Web of Science ®Google Scholar
• G. R. Harris, B. A. Herman and M. R. Myers, “A comparison of the thermal-dose equation and the intensity-time product for predicting tissue damage thresholds,” Ultrasound Med. Biol., vol. 37, no. 4, pp. 580–586, Apr. 2011. DOI: 10.1016/j.ultrasmedbio.2011.01.005.
   PubMed Web of Science ®Google Scholar
• G. C. van Rhoon, “Is CEM43 still a relevant thermal dose parameter for hyperthermia treatment monitoring?,” Int. J. Hyperthermia, vol. 32, no. 1, pp. 50–62, Jan. 2016. DOI: 10.3109/02656736.2015.1114153.
   PubMed Web of Science ®Google Scholar
• R. L. Silva, M. Alaeian and H. R. Orlande, “Design under uncertainties of the thermal ablation of tumors with high intensity focused ultrasound,” in ICHMT Digital Library Online, 2021. pp. 167–181, DOI: 10.1615/ICHMT.2021.CHT-21.130.
   Google Scholar
• F. A. Duck, Physical Properties of Tissues: A Comprehensive Reference Book. New York, USA: Academic Press, 2013.
   Google Scholar
• M. N. Özişik, H. R. Orlande, M. J. Colaco and R. M. Cotta, Finite Difference Methods in Heat Transfer. Boca Raton, FL, USA: CRC Press, 2017.
   Google Scholar
• J. A. Weaver and A. M. Stoll, “Mathematical Model of Skin Exposed to Thermal Radiation,” Naval Air Development Center, Aerospace Medical Research Department, Warminster, PA, 1967.
   Google Scholar
• C. J. Geyer, “Introduction to Markov Chain Monte Carlo,” in Handbook Markov Chain Monte Carlo, vol. 20116022, p. 45, 2011.
   Google Scholar