Literature DB >> 21096131

Mathematical modeling of impedance controlled radiofrequency tumor ablation and ex-vivo validation.

Dieter Haemmerich1.   

Abstract

Radiofrequency (RF) ablation uses RF current to heat and kill cancer applied via an electrode inserted under image-guidance, and is in clinical use for tumors in liver, lung kidney, and bone. Mathematical models are frequently used to determine tissue temperature during RF ablation, but most prior models do not include accurate implementation of power control algorithms as are used in clinical devices. We created a computer model employing the Finite Element Method, and implemented a clinically used impedance control algorithm. We assumed a rapid increase in tissue electrical conductivity upon vaporization to approximate tissue vapor formation and allow impedance control. We performed ex vivo tissue experiments where we measured the tissue temperature and impedance to validate the computer models. Impedance and temperature time course were comparable between model and experiments, and deviations are likely due to inaccurate data on temperature dependence of tissue properties. Ablation zone diameter was 33 mm in the computer model, and 29 ± 3 mm in the experiments. Our computer model may more accurately allow tissue temperature calculation via including power control algorithms as used in clinical devices.

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Mesh:

Year:  2010        PMID: 21096131      PMCID: PMC3108073          DOI: 10.1109/IEMBS.2010.5626659

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  15 in total

Review 1.  Dielectric properties of tissues and biological materials: a critical review.

Authors:  K R Foster; H P Schwan
Journal:  Crit Rev Biomed Eng       Date:  1989

2.  Multiscale optimization of the probe placement for radiofrequency ablation.

Authors:  Inga Altrogge; Tobias Preusser; Tim Kröger; Christof Büskens; Philippe L Pereira; Diethard Schmidt; Heinz-Otto Peitgen
Journal:  Acad Radiol       Date:  2007-11       Impact factor: 3.173

3.  Optimizing electrode placement using finite-element models in radiofrequency ablation treatment planning.

Authors:  Chun-Cheng R Chen; Michael I Miga; Robert L Galloway
Journal:  IEEE Trans Biomed Eng       Date:  2008-12-02       Impact factor: 4.538

4.  Computer modeling of the effect of perfusion on heating patterns in radiofrequency tumor ablation.

Authors:  Z Liu; M Ahmed; A Sabir; S Humphries; S N Goldberg
Journal:  Int J Hyperthermia       Date:  2007-02       Impact factor: 3.914

5.  Hepatic radiofrequency ablation at low frequencies preferentially heats tumour tissue.

Authors:  Dieter Haemmerich; Bradford J Wood
Journal:  Int J Hyperthermia       Date:  2006-11       Impact factor: 3.914

6.  Osteoid osteoma: percutaneous treatment with radiofrequency energy.

Authors:  Daniel I Rosenthal; Francis J Hornicek; Martin Torriani; Mark C Gebhardt; Henry J Mankin
Journal:  Radiology       Date:  2003-08-27       Impact factor: 11.105

7.  Investigation of the thermal and tissue injury behaviour in microwave thermal therapy using a porcine kidney model.

Authors:  X He; S McGee; J E Coad; F Schmidlin; P A Iaizzo; D J Swanlund; S Kluge; E Rudie; J C Bischof
Journal:  Int J Hyperthermia       Date:  2004-09       Impact factor: 3.914

8.  Imaging-guided radiofrequency ablation of solid renal tumors.

Authors:  M A Farrell; W J Charboneau; D S DiMarco; G K Chow; H Zincke; M R Callstrom; B D Lewis; R A Lee; C C Reading
Journal:  AJR Am J Roentgenol       Date:  2003-06       Impact factor: 3.959

9.  Adrenal neoplasms: CT-guided radiofrequency ablation--preliminary results.

Authors:  William W Mayo-Smith; Damian E Dupuy
Journal:  Radiology       Date:  2004-02-27       Impact factor: 11.105

Review 10.  Theoretical modeling for radiofrequency ablation: state-of-the-art and challenges for the future.

Authors:  Enrique J Berjano
Journal:  Biomed Eng Online       Date:  2006-04-18       Impact factor: 2.819

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  2 in total

1.  Radiofrequency and microwave ablation in a porcine liver model: non-contrast CT and ultrasound radiologic-pathologic correlation.

Authors:  Timothy J Ziemlewicz; J Louis Hinshaw; Meghan G Lubner; Emily A Knott; Bridgett J Willey; Fred T Lee; Christopher L Brace
Journal:  Int J Hyperthermia       Date:  2020       Impact factor: 3.914

2.  RF ablation thermal simulation model: Parameter sensitivity analysis.

Authors:  Xiaoru Wang; Hongjian Gao; Shuicai Wu; Yanping Bai; Zhuhuang Zhou
Journal:  Technol Health Care       Date:  2018       Impact factor: 1.285

  2 in total

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