2450‐MHz microwave ablation temperature simulation using temperature‐dependence feedback of characteristic parameters. Issue 1 (15th November 2018)

• Record Type: Journal Article
• Authors: Gao, Hongjian; Wang, Xiaoru; Wu, Shuicai; Zhou, Zhuhuang; Bai, Yanping
• Other Names: Palandoken Merih guestEditor.; Nasimuddin N. guestEditor.
• Is Part Of: International journal of RF and microwave computer-aided engineering. Volume 29:Issue 1(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-11-15
• Subjects: characteristic parameters -- microwave ablation -- parameter feedback -- temperature distribution simulation; Microwave devices -- Computer-aided design -- Periodicals; Computer-aided engineering -- Periodicals; 621.3813
• DOI: 10.1002/mmce.21488
• Languages: English
• ISSNs: 1096-4290

Abstract

Abstract: Temperature predictions of microwave ablation (MWA) are currently restricted by the specific temperature‐dependent data of tissue characteristic parameters. To address this issue, a new parameter feedback method based on temperature simulations and single‐thermometry measurements was presented. Experimental data of 2450‐MHz microwave antenna was obtained from ex vivo porcine livers. A temperature distribution model was constructed, and the contributions of characteristic parameters were acquired by the sensitivity analysis method. Subsequently, parameter feedbacks were conducted based on a minimization of the errors between numerical data and single‐thermometry measurements. The temperature distribution model was then optimized using the feedback parameters. Finally, temperature measurements were compared with simulation data to validate the accuracy of the model. According to the temperature distribution model with parameter feedback, the averages of maximum error, average error, as well as SD between the simulation temperatures and the measurements were 2.952, 1.323, and 0.852°C, respectively. The simulated and measured temperature changes were generally in good agreement. The proposed method can be useful in MWA temperature simulations to improve temperature prediction accuracy.