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Numerical Heat Transfer, Part A: Applications
An International Journal of Computation and Methodology
Volume 80, 2021 - Issue 5
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Original Articles

Monte Carlo parameter estimation and direct simulation of in vitro hyperthermia-chemotherapy experiment

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Pages 185-209 | Received 18 Jan 2021, Accepted 01 Jun 2021, Published online: 02 Jul 2021

References

  • R. W. Y. 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.
  • M. Mallory, E. Gogineni, G. C. Jones, L. Greer, and C. B. Simone, II, “Therapeutic hyperthermia: The old, the new, and the upcoming,” Crit. Rev. Oncol./Hematol., vol. 97, pp. 56–64, 2016. DOI: 10.1016/j.critrevonc.2015.08.003.
  • B. Hidelbrandt et al., “The cellular and molecular basis of hyperthermia,” Crit. Rev. Oncol./Hematol., vol. 43, no. 1, pp. 33–56, 2002. DOI: 10.1016/s1040-8428(01)00179-2.
  • Y. Tang and A. J. McGoron, “Combined effects of laser-ICG photothermotherapy and doxorubicin chemotherapy on ovarian cancer cells,” J. Photochem. Photobiol. B, vol. 97, no. 3, pp. 138–144, 2009. DOI: 10.1016/j.jphotobiol.2009.09.001.
  • Y. Tang and A. J. McGoron, “Increasing the rate of heating: A potential therapeutic approach for achieving synergistic tumour killing in combined hyperthermia and chemotherapy,” Int. J. Hyperthermia, vol. 29, no. 2, pp. 145–145, 2013. DOI: 10.3109/02656736.2012.760757.
  • D. C. Phung et al., “Combined hyperthermia and chemotherapy as a synergistic anticancer treatment,” J. Pharm. Investig., vol. 49, no. 5, pp. 519–526, 2019. DOI: 10.1007/s40005-019-00431-5.
  • R. W. Y. 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.
  • V. Quaranta, A. M. Weaver, P. T. Cummings, and A. R. A. Anderson, “Mathematical modeling of cancer: The future of prognosis and treatment,” Clin. Chim. Acta, vol. 357, no. 2, pp. 173–179, 2005. DOI: 10.1016/j.cccn.2005.03.023.
  • J. M. J. Costa et al., “Simultaneous model selection and model calibration for the tumor and normal cells during in vitro chemotherapy experiments,” J. Comput. Biol., vol. 25, no. 12, pp. 1216–1285, 2018. DOI: 10.1089/cmb.2017.0130.
  • L. A. B. Varon, H. R. B. Orlande, and G. E. Eliçabe, “Combined parameter and state estimation in the radio frequency hyperthermia treatment of cancer,” Numer. Heat Transfer Part A, vol. 70, no. 6, pp. 581–594, 2016. DOI: 10.1080/10407782.2016.1193342.
  • B. Lamien, H. R. B. Orlande, and G. E. Eliçabe, “Particle filter and approximation error model for state estimation in hyperthermia,” J. Heat Transfer, vol. 139, no. 1, pp. 012001, 2017. DOI: 10.1115/1.4034064.
  • B. Lamien et al., “Estimation of the temperature field in laser-induced hyperthermia experiments with a phantom,” Int. J. Hyperthermia, vol. 35, no. 1, pp. 279–290, 2018. DOI: 10.1080/02656736.2018.1496283.
  • M. Alaeian, H. R. B. Orlande, and B. Lamien, “Application of the photoacoustic technique for temperature measurements during hyperthermia,” Inverse Probl. Sci. Eng., vol. 27, no. 12, pp. 1651–1671, 2018. DOI: 10.1080/17415977.2018.1516767.
  • C. C. Pacheco et al., “Real-time temperature estimation with enhanced spatial resolution during MR-guided hyperthermia therapy,” Numer. Heat Transfer Part A: Appl., vol. 77, no. 8, pp. 782–806, 2020. DOI: 10.1080/10407782.2020.1720409.
  • J. Kaipio and E. Somersalo, Statistical and Computational Inverse Problems, Applied Mathematical Sciences 160. New York, NY: Springer-Verlag, 2004.
  • H. R. B. Orlande, O. Fudym, D. Maillet, and R. M. Cotta, Thermal Measurements and Inverse Techniques. Boca Raton, Fl, USA: CRC Press, 2011.
  • S. M. Tan and C. Fox, Inverse Problems, Course Notes for Physics 707, USA: University of Auckland, 2006.
  • 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, 2011. DOI: 10.1080/01457632.2011.525137.
  • H. R. B. Orlande, “Inverse problems in heat transfer: New trends on solution methodologies and applications,” J. Heat Transfer, vol. 134, no. 3, pp. 031011, 2012. DOI: 10.1115/1.4005131.
  • D. Gamerman and H. F. Lopes, Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, 2nd ed. Boca Raton, FL, USA: Chapman & Hall/CRC, 2006.
  • S. Brooks, A. Gelman, G. L. Jones, and X. Meng, Handbook of Markov Chain Monte Carlo. Boca Raton, FL, USA: Chapman & Hall/CRC, 2011.
  • J. M. J. Huttunen and J. P. Kaipio, “Approximation error analysis in nonlinear state estimation with an application to state-space identification,” Inverse Probl., vol. 23, no. 5, pp. 2141–2157, 2007. DOI: 10.1088/0266-5611/23/5/019.
  • J. P. Kaipio, T. Huttunem, T. Luostari, T. Lähivaara, and P. Monk, “A Bayesian approach to improving the Born approximation for inverse scattering with high contrast materials,” Inverse Probl., vol. 35, no. 8, pp. 084001, 2019. DOI: 10.1088/1361-6420/ab15f3.
  • T. Tarvainen, V. Kolehmainen, J. Kaipio, and S. R. Arridge, “Corrections to linear methods for diffuse optical tomography using approximation error modelling,” Biomed. Opt. Express, vol. 1, no. 1, pp. 209–222, 2010. DOI: 10.1364/BOE.1.000209.
  • M. Mozumder, T. Tarvainen, S. R. Arridge, J. Kaipio, and V. Kolehmainen, “Compensation of optode sensitivity and position errors in diffuse optical tomography using the approximation error approach,” Biomed. Opt. Express, vol. 4, no. 10, pp. 2015–2031, 2013. DOI: 10.1364/BOE.4.002015.
  • L. A. Bermeo, et al. “Thermal effect by applysing laser heating in iron oxide nanoparticles dissolved in distilled water," in J. Henriques, N. Neves N and P. de Carvalho, Eds. XV Mediterranean conference on medical and biological engineering and computing–MEDICON 2019. IFMBE Proceedings, Vol. 76, Switzerland: Springer International Publishing, 2019, pp. 1239–1245. DOI: 10.1007/978-3-030-31635-8_151.
  • L. Preziosi, Cancer Modelling and Simulation, Boca Raton, FL, USA: CRC Press LLC, 2003.
  • J. M. J. Costa, H. R. B. Orlande, and W. B. Silva, “Model selection and parameter estimation in tumor growth model using approximate Bayesian computation-ABC,” Comp. Appl. Math., vol. 37, no. 3, pp. 2795–2815, 2018. DOI: 10.1007/s40314-017-0479-0.
  • J. M. J. Costa et al., “Estimation of tumor size evolution using particle filters,” J. Comput. Biol., vol. 22, no. 7, pp. 649–665, 2015. DOI: 10.1089/cmb.2014.0003.
  • B. R. Loiola, H. R. B. Orlande, and G. S. Dulikravich, “Approximate Bayesian computation applied to the identification of thermal damage of biological tissues due to laser irradiation,” Int. J. Therm. Sci., vol. 151, pp. 106243, 2020. DOI: 10.1016/j.ijthermalsci.2019.106243.
  • ATCC, Thawing, Propagating, and Cryopreserving Protocol NCI-PBCF-HTB81 (DU 145) Proste Carcinoma (ATCC®HTB-81TM), Manassas: American Type Culture Collection, Version 1.6, 2012. Available: https://physics.cancer.gov/docs/bioresource/prostate/NCI-PBCF-HTB81_DU-145_SOP-508.pdf. Accessed: Nov. 11, 2020.
  • J. Geweke, Evaluating the Accuracy of Sampling-Based Approaches to the Calculation of Posterior Moments. Minneapolis, MN, USA: Fedeal Reserve Bank of Minneapolis, Research Department, 1991.
  • M. N. Ozisik and H. R. B. Orlande, Inverse Heat Transfer: Fundamental and Applications, 1st ed. New York: Wiley & Sons, 2000.
  • D. R. Lide, Handbook of Chemistry and Physics, 85th ed. Boca Raton, FL, USA: CRC Press, 2005.
  • Y. Vermahmoudi, S. M. Peyghambarzadeh, S. H. Hasshembadi, and M. Nakari, “Experimenrtal investigation on heat transfer performance of Fe2O3/water nanofluid in na air-finned heat exchanger,” Eur. J. Mech. B/Fluids, vol. 44, pp. 32–41, 2014. DOI: 10.1016/j.euromechflu.2013.10.002.
  • M. Takeda, T. Onishi, S. Nakakubo, and S. Fujimoto, “Physical properties of iron-oxide scales on si-containing steels at high temperature,” Mater. Trans., vol. 50, no. 9, pp. 2242–2246, 2009. DOI: 10.2320/matertrans.M2009097.
  • L. Goto-Silva et al., “Computational fluid dynamic analysis of physical forces playing a role in brain organoid sultures in two different multiplex platforms,” BMC Dev. Biol., vol. 19, no. 1, pp. 1–10, 2019. DOI: 10.1186/s12861-019-0183-y.
  • J. D. Brown, H. E. Dillon, D. V. Kaweesa, and A. M. Harada, “The impact of transient heat transfer on tissue culture cell distribution,” Biosyst. Eng., vol. 163, pp. 28–36, 2017. DOI: 10.1016/j.biosystemseng.2017.08.009.
  • I. Dinçer and M. A. Rosen, Thermal Energy Storage – Systems and Applications. USA: John Wiley & Sons Ltd, 2002.
  • K. Khanafer, K. Vafai, and M. Lightstone, “Buoyancy-driven heat transfer enhancement in a two-dimensional enclosure utilizing nanofluids,” Int. J. Heat Mass Transfer, vol. 46, no. 19, pp. 3639–3653, 2003. DOI: 10.1016/S0017-9310(03)00156-X.
  • K. Khanafer and K. Vafai, “A critical synthesis of thermophysical characteristics of nanofluids,” Int. J. Heat Mass Transfer, vol. 54, no. 19–20, pp. 4410–4428, 2011. DOI: 10.1016/j.ijheatmasstransfer.2011.04.048.
  • C-Therm Technologies, TCi Operator Manual, Thermal Conductivity Analyzer. USA: C-Thermn Technologies, 2008.
  • Netzsch Thermal Analysis, Differential Scanning Calorimetry (DSC), Accurate Determination of the Specific Heat Capacity of Polystyrene. Available: https://www.netzsch-thermal-analysis.com/en/materials-applications/polymers/polymers-polystyrene-with-narrow-molar-mass-distribution/. Accessed: Nov. 14, 2020.
  • J. Pearce, “Mathematical models of laser-induced tissue thermal damage,” Int. J. Hyperthermia, vol. 27, no. 8, pp. 741–750, 2011. DOI: 10.3109/02656736.2011.580822.
  • BIPM, IEC, IFCC, ISO, IUPAC, IUPAP and OIML, Guide to the Expression of Uncertainty in Measurement, 3rd Brazilian ed. Rio de Janeiro: ABNT and INMETRO, 2003.
  • G. E. P. Box and D. R. Cox, “An analysis of transformations,” J. R. Stat. Soc. Edinburgh, vol. 26, no. 2, pp. 211–252, 1964. DOI: 10.1111/j.2517-6161.1964.tb00553.x.
  • B. Efron, “Transformation theory: How normal is a family of distributions?” Ann. Stat., vol. 10, no. 2, pp. 323–339, 1982. DOI: 10.1214/aos/1176345777.
  • D. Moore and G. MacCabe, Introduction to the Practice of Statistics. New York, USA: W.H. Freeman and Company, 1993.
  • D. C. Montgomery, Design and Analysis of Experiments. USA: John Wiley and Sons, 1976.
  • H. Scheffé, The Analysis of Variance, 1st ed., New York, USA: John Wiley & Sons, 1959.

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