【正文】 for the tip temperature to reach a target temperature of 100176。 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. Panescu D, Whayne JG, Fleischman SD, Mirotznik MS, Swanson DK, Webster JG:Threedimensional finite element analysis of current density and temperature distributions during radiofrequency ablation. IEEE Trans Biomed Eng 1995, 42:879890. PubMed Abstract | Publisher Full Text 25 6. Tungjitkusolmun S, Staelin ST, Haemmerich D, Tsai JZ, Cao H, Webster JG, Lee FT, Mahvi DM, Vorperian VR: Threedimensional finiteelement analyses for radiofrequency hepatic tumor ablation. IEEE Trans Biomed Eng 2022, 49:39. PubMed Abstract | Publisher Full Text 7. Jain MK, Wolf PD: Temperaturecontrolled and constantpower radiofrequency ablation: what affects lesion growth? IEEE Trans Biomed Eng 1999, 46:14051412. PubMed Abstract | Publisher Full Text 8. Chang IA, Nguyen UD: Thermal modeling of lesion growth with radiofrequency ablation devices. Biomed Eng Online 2022, 3:27. PubMed Abstract | BioMed Central Full Text |PubMed Central Full Text 9. 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. Pennes HH: Analysis of tissue and arterial blood tempera。t have exact data of the tip temperature over time. We empirically chose parameters for the PI controller to minimize overshoot and obtain similar temporal behavior as in the invivo experiments. 19 The parameters we used for the PI controller were Kp = , Ki = . Fig. 4 shows the results of the closedloop control system simulation. The target tip temperature of 100176。 the model consisted of ~35,000 tetrahedral elements and ~7,000 nodes. The node spacing was small next to the electrode ( 16 mm) and larger at the model boundary (2 mm). Perfusion was included in the model according to the Pennes model [14]. The blood perfusion wbl used in this model was K)). J is the current density (A/m2) and E is the electric field intensity (V/m). Tbl is the temperature of blood, ρbl is the blood density (kg/m3), cbl is the specific heat of the blood (J/(kg at 50176。 radiofrequency ablation。t support automating temperature control. Most researchers manually control the applied power by trial and error to keep the tip temperature of the electrodes constant. Methods We implemented a PI controller in a control program written in C++. The program checks the tip temperature after each step and controls the applied voltage to keep temperature constant. We created a closed loop system consisting of a FEM model and the software controlling the applied voltage. The control parameters for the controller were optimized using a closed loop system simulation. Results We present results of a temperature controlled 3D FEM model of a RITA model 30 electrode. The control software effectively controlled applied voltage in the FEM model to obtain, and keep electrodes at target temperature of 100176。詹參與設(shè)計(jì)的研究。我們進(jìn)一步用閉環(huán)控制系統(tǒng)仿真優(yōu)化控制參數(shù)。從我們的經(jīng)驗(yàn)中溫度分布的有限元模型達(dá)到接近穩(wěn)態(tài)仿真結(jié)束時(shí)由于長(zhǎng)期模擬次數(shù)。黑暗的曲線顯示結(jié)果的控制有限元模型將灌注。在這種情況下 ,溫度最熱的電極應(yīng)該用于控制以避免組織過(guò)熱。兩個(gè)超和沉降時(shí)間的提示溫度較高的情況 ,灌注同時(shí) ,電壓要求保持提示溫度高于設(shè)定溫度價(jià)值因?yàn)楣嘧⑦M(jìn)行熱了。否則會(huì)有變化的閉環(huán)系統(tǒng)的動(dòng)態(tài)行為。在控制系統(tǒng)仿真一個(gè)常數(shù)采樣時(shí)間 (即步驟時(shí)間 )的 10年代被使用。沒(méi)有結(jié)果顯示在 200年代以來(lái)幾乎沒(méi)有改變一旦設(shè)置提示溫度了。單個(gè)步驟 6和 11分鐘之間了運(yùn)行在有限元分析。隨后 ,步長(zhǎng)增加一旦提示溫度變化的步驟之間減少低于一定值。同時(shí) ,有限元解算器進(jìn)行收斂測(cè)試來(lái)確保增量尺寸足夠小。然后 ,確定了外加電壓和步長(zhǎng)為下一步 ,和有限元分析是重啟與修改輸入文件。 軟件控制程序確定了外加電壓和步驟時(shí)間。上面的曲線顯示提示溫度 ,較低的曲線顯示了外加電壓。 C的咀溫度達(dá)到 100年代后開(kāi)始消融。實(shí)證性地選擇參數(shù) PI控制器來(lái)減少超調(diào) ,獲得類似的時(shí)間行為在體內(nèi)實(shí)驗(yàn)。 PI控制器的行為是由這兩個(gè)參數(shù) Kp和接近。 PI控制器的輸入 e = Ts Tt。5 有不同的方法控制提示溫度如 PID控制、自適應(yīng)控制、神經(jīng)網(wǎng)絡(luò)預(yù)測(cè)控制和模糊邏輯控制。采樣時(shí)間的近似系統(tǒng) 10年代 ,因?yàn)槟且彩且院蟮牟蓸訒r(shí)間使用在數(shù)字 PI控制器。維也納 /奧地利 )來(lái)分析控制系統(tǒng)。輸出變量是溫度測(cè)量電極的尖端。因4 此我們使用閉環(huán)仿真調(diào)整控制器的參數(shù) ,然后用這些參數(shù)的有限元模型。我們創(chuàng)建了一個(gè) c++程序 ,讀取溫度電極頭從結(jié)果文件并創(chuàng)建一個(gè)新的輸入文件 ,應(yīng)用電壓設(shè)置根據(jù)控制算法 。血液灌注 wbl用于該模型 ?打出 1 / s[15]。我們使用相同的模型在之前的一項(xiàng)研究 [3]。外表面缸被設(shè)置為 37176。索倫森 ,Inc .的波塔基特 ,國(guó)際扶輪 )解決耦合 熱電氣分析。 Qm(W / m3)是由代謝過(guò)程產(chǎn)生的電能 ,是被忽視的 ,因?yàn)樗切〉谋绕渌麠l款 [13]。 加熱的組織在射頻消融治療是由 bioheat方程 : 哪里是密度 ρ (公斤 /立方米 ),c是比熱 (J /(公斤 ?K)),K是熱導(dǎo)率 (W /(m?K))。我們使用一個(gè)封閉的循環(huán)系統(tǒng)仿真優(yōu)化控制參數(shù) PI控制器。以前 ,大多數(shù)研究人員使用手動(dòng)調(diào)節(jié)外加電壓和試錯(cuò)的