{"title":"[肿瘤治疗场模拟模型]。","authors":"Liping Qin, Xu Xie, Minmin Wang, Mingwei Ma, Yun Pan, Guangdi Chen, Shaomin Zhang","doi":"10.7507/1001-5515.202306074","DOIUrl":null,"url":null,"abstract":"<p><p>Tumor-treating fields (TTFields) is a novel treatment modality for malignant solid tumors, often employing electric field simulations to analyze the distribution of electric fields on the tumor under different parameters of TTFields. Due to the present difficulties and high costs associated with reproducing or implementing the simulation model construction techniques, this study used readily available open-source software tools to construct a highly accurate, easily implementable finite element simulation model for TTFields. The accuracy of the model is at a level of 1 mm <sup>3</sup>. Using this simulation model, the study carried out analyses of different factors, such as tissue electrical parameters and electrode configurations. The results show that factors influncing the distribution of the internal electric field of the tumor include changes in scalp and skull conductivity (with a maximum variation of 21.0% in the treatment field of the tumor), changes in tumor conductivity (with a maximum variation of 157.8% in the treatment field of the tumor), and different electrode positions and combinations (with a maximum variation of 74.2% in the treatment field of the tumor). In summary, the results of this study validate the feasibility and effectiveness of the proposed modeling method, which can provide an important reference for future simulation analyses of TTFields and clinical applications.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 2","pages":"360-367"},"PeriodicalIF":0.0000,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11058494/pdf/","citationCount":"0","resultStr":"{\"title\":\"[Simulation model of tumor-treating fields].\",\"authors\":\"Liping Qin, Xu Xie, Minmin Wang, Mingwei Ma, Yun Pan, Guangdi Chen, Shaomin Zhang\",\"doi\":\"10.7507/1001-5515.202306074\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Tumor-treating fields (TTFields) is a novel treatment modality for malignant solid tumors, often employing electric field simulations to analyze the distribution of electric fields on the tumor under different parameters of TTFields. Due to the present difficulties and high costs associated with reproducing or implementing the simulation model construction techniques, this study used readily available open-source software tools to construct a highly accurate, easily implementable finite element simulation model for TTFields. The accuracy of the model is at a level of 1 mm <sup>3</sup>. Using this simulation model, the study carried out analyses of different factors, such as tissue electrical parameters and electrode configurations. The results show that factors influncing the distribution of the internal electric field of the tumor include changes in scalp and skull conductivity (with a maximum variation of 21.0% in the treatment field of the tumor), changes in tumor conductivity (with a maximum variation of 157.8% in the treatment field of the tumor), and different electrode positions and combinations (with a maximum variation of 74.2% in the treatment field of the tumor). In summary, the results of this study validate the feasibility and effectiveness of the proposed modeling method, which can provide an important reference for future simulation analyses of TTFields and clinical applications.</p>\",\"PeriodicalId\":39324,\"journal\":{\"name\":\"生物医学工程学杂志\",\"volume\":\"41 2\",\"pages\":\"360-367\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11058494/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"生物医学工程学杂志\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://doi.org/10.7507/1001-5515.202306074\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"生物医学工程学杂志","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.7507/1001-5515.202306074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
Tumor-treating fields (TTFields) is a novel treatment modality for malignant solid tumors, often employing electric field simulations to analyze the distribution of electric fields on the tumor under different parameters of TTFields. Due to the present difficulties and high costs associated with reproducing or implementing the simulation model construction techniques, this study used readily available open-source software tools to construct a highly accurate, easily implementable finite element simulation model for TTFields. The accuracy of the model is at a level of 1 mm 3. Using this simulation model, the study carried out analyses of different factors, such as tissue electrical parameters and electrode configurations. The results show that factors influncing the distribution of the internal electric field of the tumor include changes in scalp and skull conductivity (with a maximum variation of 21.0% in the treatment field of the tumor), changes in tumor conductivity (with a maximum variation of 157.8% in the treatment field of the tumor), and different electrode positions and combinations (with a maximum variation of 74.2% in the treatment field of the tumor). In summary, the results of this study validate the feasibility and effectiveness of the proposed modeling method, which can provide an important reference for future simulation analyses of TTFields and clinical applications.