{"title":"Temperature and state-dependent electrical conductivity of soft biological tissue at hyperthermic temperatures.","authors":"Junren Ran, Martin Ostoja-Starzewski","doi":"10.1080/02656736.2024.2422509","DOIUrl":null,"url":null,"abstract":"<p><p><b>Objective:</b> We present a physics-based, temperature and state-dependent electrical conductivity model for soft biological tissue under thermal therapies with a quantified damage parameter that represents the state of soft biological tissue (degree of denaturation). Most existing models consider electrical conductivity to be only temperature-dependent and evaluate tissue damage during post-processing after temperature calculation. Our model allows tissue damage to be coupled into the thermal model for a more accurate description of both RF ablation and electrosurgery. <b>Methods:</b> We model the denaturation process with an Arrhenius-type differential equation for chemical kinetics and a modified Stogryn equation for electrical conductivity under state transition. We present experimental data from two types of heating procedures at 128 kHz to validate and showcase the capability of our model. <b>Results:</b> Our model is able to capture the change in electrical conductivity during heating, cooling, and reheating procedures, which distinguishes different states and shows the irreversibility of denaturation. The model also accurately captures tissue change during slow cooking at a constant temperature, highlighting a state dependence. <b>Conclusion:</b> By incorporating state dependence into the model for electrical properties, we are able to capture the denaturation process more accurately and distinguish different degrees of damage. Our model allows the modeling of procedures involving repeated heating or cooling, which is impossible for models without a state dependence. While being able to adapt to patient-specific needs, the model can be used to improve planning and control in future robot-assisted surgeries to reduce unnecessary damage.</p>","PeriodicalId":14137,"journal":{"name":"International Journal of Hyperthermia","volume":"41 1","pages":"2422509"},"PeriodicalIF":3.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Hyperthermia","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/02656736.2024.2422509","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/11/10 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: We present a physics-based, temperature and state-dependent electrical conductivity model for soft biological tissue under thermal therapies with a quantified damage parameter that represents the state of soft biological tissue (degree of denaturation). Most existing models consider electrical conductivity to be only temperature-dependent and evaluate tissue damage during post-processing after temperature calculation. Our model allows tissue damage to be coupled into the thermal model for a more accurate description of both RF ablation and electrosurgery. Methods: We model the denaturation process with an Arrhenius-type differential equation for chemical kinetics and a modified Stogryn equation for electrical conductivity under state transition. We present experimental data from two types of heating procedures at 128 kHz to validate and showcase the capability of our model. Results: Our model is able to capture the change in electrical conductivity during heating, cooling, and reheating procedures, which distinguishes different states and shows the irreversibility of denaturation. The model also accurately captures tissue change during slow cooking at a constant temperature, highlighting a state dependence. Conclusion: By incorporating state dependence into the model for electrical properties, we are able to capture the denaturation process more accurately and distinguish different degrees of damage. Our model allows the modeling of procedures involving repeated heating or cooling, which is impossible for models without a state dependence. While being able to adapt to patient-specific needs, the model can be used to improve planning and control in future robot-assisted surgeries to reduce unnecessary damage.