An overview of mathematical models and modulated-heating protocols for thermal ablation

Andreozzi, Assunta; Iasiello, Marcello; Tucci, Claudio

doi:10.1016/bs.aiht.2020.07.003

Cited by 21 publications

(12 citation statements)

References 117 publications

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“…Simply put, Pennes’ bioheat equation belongs to the first group, reducing the complete tissue model to a single heat transport equation with an additional term describing heat removal by blood perfusion. Models based on porous-media theory [ 67 , 68 , 69 ] are more complex, usually containing at least two equations: one for tissue and one for blood temperature. Of course, more subtle aspects can be included (thermo-mechanical, microscopic, etc.…”

Section: Discussionmentioning

confidence: 99%

An Analysis of Microwave Ablation Parameters for Treatment of Liver Tumors from the 3D-IRCADb-01 Database

Radmilović-Radjenović

Bošković

Sabo

et al. 2022

Biomedicines

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Simulation techniques are powerful tools for determining the optimal conditions necessary for microwave ablation to be efficient and safe for treating liver tumors. Owing to the complexity and computational resource consumption, most of the existing numerical models are two-dimensional axisymmetric models that emulate actual three-dimensional cancers and the surrounding tissue, which is often far from reality. Different tumor shapes and sizes require different input powers and ablation times to ensure the preservation of healthy tissues that can be determined only by the full three-dimensional simulations. This study aimed to tailor microwave ablation therapeutic conditions for complete tumor ablation with an adequate safety margin, while avoiding injury to the surrounding healthy tissue. Three-dimensional simulations were performed for a multi-slot microwave antenna immersed in two tumors obtained from the 3D-IRCADb-01 liver tumors database. The temperature dependence of the dielectric and thermal properties of healthy and tumoral liver tissues, blood perfusion, and water content are crucial for calculating the correct ablation time and, thereby, the correct ablation process. The developed three-dimensional simulation model may help practitioners in planning patient-individual procedures by determining the optimal input power and duration of the ablation process for the actual shape of the tumor. With proper input power, necrotic tissue is placed mainly in the tumor, and only a small amount of surrounding tissue is damaged.

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Section: Discussionmentioning

confidence: 99%

An Analysis of Microwave Ablation Parameters for Treatment of Liver Tumors from the 3D-IRCADb-01 Database

Radmilović-Radjenović

Bošković

Sabo

et al. 2022

Biomedicines

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“…Penne’s theory has been extended in numerous papers [ 89 , 90 , 91 , 92 ]. An extensive review of the different bioheat models can be found in Andreozzi et al [ 14 ].…”

Section: Mathematical Models Of Tissue and Heat Transportmentioning

confidence: 99%

“…According to the literature, MWA treatment completely eliminates small liver tumors, with a success rate greater than 85% [ 13 ]. During MWA, ablation can be accomplished by either implicitly controlling the power or temperature, resulting in a modulating heat procedure [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

Computational Modeling of Microwave Tumor Ablation

Radmilović-Radjenović

Bošković

Radjenović

2022

Bioengineering

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Microwave ablation is recognized as a minimally invasive, fast-recovery treatment for destroying cancer cells using the heat generated by microwave energy. Despite the unquestionable benefits of microwave ablation, the interaction of the microwave applicator with the tissue may result in localized heating and damage to the surrounding tissue. The majority of the tissue damage can be removed by clarifying the conditions for their development. In addition to experimental methods, computer modeling has proven to be an effective tool for optimizing the performance of microwave ablation. Furthermore, because the thermal spread in biological tissue is difficult to measure, developing a predictive model from procedural planning to execution may have a substantial influence on patient care. The comprehension of heat transport in biological tissues plays a significant role in gaining insight into the mechanisms underlying microwave ablation. Numerical methods that enable ablation size control are required to guarantee tumor destruction and minimize damage to healthy tissues. Various values of input power and ablation time correspond to different tumor shapes ensuring the preservation of healthy tissues. The optimal conditions can be estimated by performing full three-dimensional simulations. This topical review recapitulates numerous computational studies on microwave tumor ablation. Novel areas emerging in treatment planning that exploit the advantages of numerical methods are also discussed. As an illustration, the results of the three-dimensional simulations of real liver tumors in the 3D-IRCADb-01 database are presented and analyzed. The simulation results confirm that numerical methods are very useful tools for modeling microwave tumor ablation with minimal invasiveness and collateral damage.

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“…Pennes bioheat equation has a few limitations (Nakayama and Kuwahara, 2008;Andreozzi et al, 2020) such as constant and uniform temperature instead of three temperature equations for three media (liver, vessels and tumour), other models are also used by researchers. This study uses only the Pennes bioheat equation.…”

Section: Limitationsmentioning

confidence: 99%

A point source model to represent heat distribution without calculating the Joule heat during radiofrequency ablation

Mariappan

B²,

Flanagan³

2022

Front. Therm. Eng.

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Numerous liver cancer oncologists suggest bridging therapies to limit cancer growth until donors are available. Interventional radiology including radiofrequency ablation (RFA) is one such bridging therapy. This locoregional therapy aims to produce an optimal amount of heat to kill cancer cells, where the heat is produced by a radiofrequency (RF) needle. Less experienced Interventional Radiologists (IRs) require a software-assisted smart solution to predict the optimal heat distribution as both overkilling and untreated cancer cells are problematic treatments. Therefore, two of the big three partial differential equations, 1) heat equation (Pennes, Journal of Applied Physiology, 1948, 1, 93–122) to predict the heat distribution and 2) Laplace equation (Prakash, Open Biomed. Eng. J., 2010, 4, 27–38) for electric potential along with different cell death models (O’Neill et al., Ann. Biomed. Eng., 2011, 39, 570–579) are widely used in the last three decades. However, solving two differential equations and a cell death model is computationally expensive when the number of finite compact coverings of a liver topological structure increases in millions. Since the heat source from the Joule losses Qr = σ|∇V|2 is obtained from Laplace equation σΔV = 0, it is called the Joule heat model. The traditional Joule heat model can be replaced by a point source model to obtain the heat source term. The idea behind this model is to solve σΔV = δ0 where δ0 is a Dirac-delta function. Therefore, using the fundamental solution of the Laplace equation (Evans, Partial Differential Equations, 2010) we represent the solution of the Joule heat model using an alternative model called the point source model which is given by the Gaussian distribution.Qrx=∑xi∈Ω1K∑icie−|x−xi|22σ2where K and ci are obtained by using needle parameters. This model is employed in one of our software solutions called RFA Guardian (Voglreiter et al., Sci. Rep., 2018, 8, 787) which predicted the treatment outcome very well for more than 100 patients.

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An overview of mathematical models and modulated-heating protocols for thermal ablation

Cited by 21 publications

References 117 publications

An Analysis of Microwave Ablation Parameters for Treatment of Liver Tumors from the 3D-IRCADb-01 Database

An Analysis of Microwave Ablation Parameters for Treatment of Liver Tumors from the 3D-IRCADb-01 Database

Computational Modeling of Microwave Tumor Ablation

A point source model to represent heat distribution without calculating the Joule heat during radiofrequency ablation

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