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自動控制的有限元模型對溫控射頻消融術(shù)外文翻譯-資料下載頁

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【正文】 geometry etc. are changed. Otherwise there will be changes in the dynamic behavior of the closedloop system. Fig. 5 shows the temperature and voltage of the FEM model controlled by the same PI controller for two cases. The light graphs show the behavior without incorporating perfusion in the FEM model, the dark graphs show the behavior of the same FEM model with perfusion (as in Fig. 4). Both the overshoot and the settling time of tip temperature for the case with perfusion were higher. Also, the voltage required to keep the tip temperature at the set temperature value was higher because the perfusion carried heat away. To obtain the same performance during the initial period in both cases, different controllers had to be used, . the parameters of the PI controller had to be modified. Our model only included a quarter of the actual electrode. In models where nonuniform heating due to vessels occurs, the electrodes will obtain different temperatures [6]. In this case, the temperature of the hottest electrode should be used for control to avoid tissue overheating. 23 Temporal behavior of tip temperature and applied voltage of the closed loop system. The upper curves show the tip temperature, the lower curves show the applied voltage. The light curves show the results of the controlled FEM model without perfusion. The dark curves show the results of the controlled FEM model incorporating perfusion. In hepatic RF ablation, ablation times clinically used go up to 35 min. Since the heatup period is parably much smaller (1 to 2 min.), it is not of essential importance that the temporal behavior of the control algorithm reproduces the control algorithm used in clinical devices during the heatup period. From our experience, the temperature distribution in the FEM model reaches close to steady state at the end of the simulation due to the long simulation times. As long as the tip temperature is kept within a small range around the target temperature after the initial heatup period, the model results (. final temperature distribution) should not differ significantly. However, with knowledge of the actual control parameters and algorithms of mercial devices (. obtained from measurements), accurate simulations of these devices is possible using our methods. Conclusion We implemented a closed loop control system to a FEM model, to automate simulation of temperaturecontrolled RF ablation. We further used a closed loop control system 24 simulation to optimize control parameters. Previously, researchers often applied constant power, or used timeconsuming trialanderror methods to determine required voltage. Furthermore, if control parameters and algorithms of mercial devices are known or can be measured, an accurate simulation of mercial devices is possible. Authors39。 contributions DH carried out puter simulations. JG participated in design of the study. All authors read and approved the final manuscript. Acknowledgements This work was supported by NIH Grant HL56413. References 1. Bosch FX, Ribes J, Borras J: Epidemiology of primary liver cancer. Semin Liver Dis 1999, 19:27185. PubMed Abstract 2. Curley SA, Cusack JC Jr, Tanabe KK, Stoelzing O, Ellis LM: Advances in the treatment of liver tumors. Curr Probl Surg 2022, 39:449571. PubMed Abstract | Publisher Full Text 3. Haemmerich D, Staelin ST, Tungjitkusolmun S, Lee FT Jr, Mahvi DM, Webster JG:Hepatic bipolar radiofrequency ablation between separated multiprong electrodes. IEEE Trans Biomed Eng 2022, 48:114552. PubMed Abstract | Publisher Full Text 4. Tungjitkusolmun S, Woo EJ, Cao H, Tsai JZ, Vorperian VR, Webster JG: Finite element analyses of uniform current density electrodes for radiofrequency cardiac ablation. IEEE Trans Biomed Eng 2022, 47:3240. PubMed Abstract | Publisher Full Text 5. 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Chang I: Finite element analysis of hepatic radiofrequency ablation probes using temperaturedependent electrical conductivity. Biomed Eng Online 2022, 2:12. PubMed Abstract | BioMed Central Full Text |PubMed Central Full Text 10. Liu Z, Lobo SM, Humphries S, Horkan C, Solazzo SA, HinesPeralta AU, Lenkinski RE, Goldberg SN: Radiofrequency tumor ablation: insight into improved efficacy using puter modeling. AJR Am J Roentgenol 2022, 184:134752. PubMed Abstract | Publisher Full Text 11. Gopalakrishnan J: A mathematical model for irrigated epicardial radiofrequency ablation. Ann Biomed Eng 2022, 30:88493. PubMed Abstract | Publisher Full Text 12. Graham SJ, Chen L, Leitch M, Peters RD, Bronskill MJ, Foster FS, Henkelman RM, Plewes DB: Quantifying tissue damage due to focused ultrasound heating observed by MRI. Magn Reson Med 1999, 41:3218. PubMed Abstract | Publisher Full Text 26 13. Chato JC: Heat transfer to blood vessels. J Biomech Eng 1980, 102:1108. PubMed Abstract 14. 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