Evaluation of Developed Thermal Distribution Prediction Algorithm Using Mass Density Distribution with CT Image
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Prior to the hyperthermia, the amount of heat energy delivered to the tumors must be confirmed. If it cannot be confirmed before hyperthermia, normal tissues may also be heated, leading to possible necrosis. In a previous study, the thermal distribution was calculated using mass density distribution with CT image. The previous study was not performed various evaluations of accuracy for the developed thermal distribution prediction algorithm. In this study, the developed thermal distribution prediction algorithm was evaluated by comparing the phantom with the measured temperature and a commercial simulation software (Sim4Life) has been used as a reference data for hyperthermia studies. The difference between the measured temperature and the commercial simulation software (Sim4Life) was within 3%, and the difference between the measured temperature and the developed thermal distribution algorithm was also within 2%. The difference between the developed thermal distribution algorithm and the commercial simulation software was also within 3%. The thermal distribution algorithm developed in this study could predict the internal temperature of the patient before hyperthermia and increase the treatment accuracy by preventing necrosis from occurring in normal organs. In addition, it could easily predict the temperatures for hyperthermia without modeling CT images taken for the diagnosis of lesions.
KeywordsThermal prediction program Hyperthermia therapy SAR (specific absorption rate) Mass density BHE (Bio Heat Equation) Sim4Life
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This research was supported by Advanced Institute for Radiation Medical Technology (AIRFMT) at Catholic University of Korea. This research is supported by AdipoLABs Co., Ltd. Thanks to ZMT for providing free license of Sim4Life used in this study.
- P. F. Maccarini, H-O. Rolfsnes, D. Neuman and P. Stauffer, in The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (2004), Vol. 1, p. 2518.Google Scholar
- D. Stalling, M. Seebass, M. Zöckler and H-C. Hege (2000).Google Scholar
- Sim4Life by ZMT, https://www.zmt.swiss
- S. H. Lee et al., J. Korean Soc. Radiother. Technol. 27, 97 (2015).Google Scholar
- J. K. Kim, B. Prasad and S. Kim, in Optical Methods for Tumor Treatment and Detection: Mechanisms and Techniques in Photodynamic Therapy XXVI (2017), Vol. 10047, p. 1004718.Google Scholar