Numerical Modeling of Locoregional Hyperthermia in Human Pelvic Cancers Applied with Capacitive System: Experimental and Simulation Study

Zahra Galian  Moradian; Fereidoun  Nowshiravan Rahatabad; Majid  Pouladian

doi:10.18502/fbt.v12i4.19823

Zahra Galian Moradian Department of Biomedical Engineering, SR.C., Islamic Azad University, Tehran, Iran
Fereidoun Nowshiravan Rahatabad Department of Biomedical Engineering, SR.C., Islamic Azad University, Tehran, Iran
Majid Pouladian Department of Biomedical Engineering, SR.C., Islamic Azad University, Tehran, Iran

DOI: https://doi.org/10.18502/fbt.v12i4.19823

Keywords: Locoregional Hyperthermia; Capacitive Hyperthermia; Finite Element Method; Numerical Modeling; COMSOL Multiphysics.

Abstract

Purpose: This study aimed to estimate the rate of temperature rise during the radiofrequency capacitive heating (13.56 MHz, 300 watts) to defined geometries including 6 simple geometric models, a virtual phantom, and a real section of the human pelvis obtained by CT-scan. The importance of this study is in the process of Hyperthermia Treatment Planning (HTP).

Materials and Methods: In this research, COMSOL software has been used to numerical model and simulate the three-dimensional (3D). First, six models with simple cylindrical geometry were developed to simulate the Radiofrequency (RF) capacitive hyperthermia treatment sessions. The diameter of the capacitor plates used was 25 cm, which was placed on a layer of water. To perform hyperthermia treatment planning with real geometry based on CT images, the pelvic area was downloaded from the slicer software and the generated mesh was transferred to COMSOL. Finally, a virtual phantom was used to validate the simulation, which means that the results of this simulation have been confirmed by experimental studies in the literature.

Results: The findings of this study indicated that capacitive hyperthermia is an effective deep treatment method especially for lean patients, so that for all models, an increase in temperature to a depth of 12 cm was observed. The thermometric data obtained from the simulation method showed a good agreement with the results obtained from the clinical and tissue equivalent phantom thermometry. The results showed that the simulation can predict temperature changes during capacitive hyperthermia for lean patients with greater accuracy than obese patients.

Conclusion: The results of comparing temperature profiles of the models taken from the platform provided with the experimental studies, showed relatively good simulation accuracy, that can be used to develop software for capacitive heating treatment planning.