A computational theoretical model for radiofrequency ablation of tumor with complex vascularization

Shao, Yunlin; Arjun, B.; Leo, Hwa Liang; Chua, K.J.

doi:10.1016/j.compbiomed.2017.08.025

Cited by 15 publications

(11 citation statements)

References 29 publications

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“…The nonlinear decreasing model derived from the in vivo study in renal tissue, in which the blood perfusion initially increases due to hyperaemia and later decreases with coagulation due to damage to the microvasculature, was able to more accurately and realistically quantify the damage dependent variation in the blood perfusion rate during RFA. Thus, most of the recent studies reported in the literature have utilized a non-linear piecewise decreasing model of blood perfusion rate in the computational models of thermal ablation (Abraham and Sparrow, 2007, Shao et al, 2017a, Singh and Repaka, 2017c, Singh and Repaka, 2017a, Singh and Repaka, 2018c, as given by…”

Section: Modelling Of Bio-physical Parametersmentioning

confidence: 99%

“…Several computational studies have been reported in the literature for evaluating the influence of heat sink effect caused by large blood vessels by coupling the additional fluid flow model (i.e. Navier-Stokes equations) to the existing bio-electromagnetic and bioheat transfer models of thermal ablation (Chaichanyut and Tungjitkusolmun, 2016, Haemmerich et al, 2003, Horng et al, 2007, Huang, 2013, Jain and Wolf, 2000, Rossmann et al, 2012, Wang et al, 2016, Zorbas and Samaras, 2015, Khademi et al, 2019, Shao et al, 2017a, Shao et al, 2017c. Importantly, in these studies, the blood vessel is incorporated by including a cylinder or a vascular tree within the computational domain, either derived from the patient image data or selected arbitrarily.…”

Section: Solid-fluid Interaction Blood Vessel Models and Biological mentioning

confidence: 99%

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Thermal ablation of biological tissues in disease treatment: A review of computational models and future directions

Singh

Melnik

2020

Electromagnetic Biology and Medicine

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Percutaneous thermal ablation has proved to be an effective modality for treating both benign and malignant tumors in various tissues. Among these modalities, radiofrequency ablation (RFA) is the most promising and widely adopted approach that has been extensively studied in the past decades. Microwave ablation (MWA) is a newly emerging modality that is gaining rapid momentum due to its capability of inducing rapid heating and attaining larger ablation volumes, and its lesser susceptibility to the heat sink effects as compared to RFA. Although the goal of both these therapies is to attain cell death in the target tissue by virtue of heating above 50 o C, their underlying mechanism of action and principles greatly differs. Computational modelling is a powerful tool for studying the effect of electromagnetic interactions within the biological tissues and predicting the treatment outcomes during thermal ablative therapies. Such a priori estimation can assist the clinical practitioners during treatment planning with the goal of attaining successful tumor destruction and preservation of the surrounding healthy tissue and critical structures. This review provides current state-ofthe-art developments and associated challenges in the computational modelling of thermal ablative techniques, viz., RFA and MWA, as well as touch upon several promising avenues in the modelling of laser ablation, nanoparticles assisted magnetic hyperthermia and noninvasive RFA. The application of RFA in pain relief has been extensively reviewed from modelling point of view. Additionally, future directions have also been provided to improve these models for their successful translation and integration into the hospital work flow.

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Section: Modelling Of Bio-physical Parametersmentioning

confidence: 99%

Section: Solid-fluid Interaction Blood Vessel Models and Biological mentioning

confidence: 99%

Thermal ablation of biological tissues in disease treatment: A review of computational models and future directions

Singh

Melnik

2020

Electromagnetic Biology and Medicine

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“…Several studies have been reported in the literature for modeling blood perfusion within biological tissues, at both micro- and macro-vascular levels [ 78 , 113 , 114 , 115 , 116 , 117 , 118 , 119 ]. Notably, micro-vascular perfusion refers to the perfusion at a capillary (or small-scale) level while macro-vascular perfusion is associated with the heat-sink effect caused by large blood vessels [ 120 ].…”

Section: Clinical Applications Future Outlook and Model Developmementioning

confidence: 99%

“…The blood flow at a micro-vascular level within the biological tissue is typically modeled by utilizing the porous media theory, whereby the tissue is assumed to be comprised of two phases: the solid phase comprising of cells and the extracellular space, and the fluid phase comprising of capillary size blood vessels [ 94 , 95 , 118 , 119 , 121 , 122 , 123 ]. The blood flow within the large blood vessels ( 2 mm in diameter) is modeled by additional coupling of the fluid flow model with the proposed thermo-electric model presented in this study, whereby the geometry of the blood vessel within the computational domain can be incorporated either by including a cylinder or a vascular tree [ 113 , 114 , 115 , 116 , 117 , 124 , 125 ]. It is expected that further refinement of the model can be done by deriving the computational domain from actual patient-specific data, which will provide more rigorous analysis and would help medical practitioners to obtain more accurate and precise predictions of the treatment outcomes during the RF application in pain management.…”

Section: Clinical Applications Future Outlook and Model Developmementioning

confidence: 99%

Domain Heterogeneity in Radiofrequency Therapies for Pain Relief: A Computational Study with Coupled Models

Singh

Melnik

2020

Bioengineering

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The objective of the current research work is to study the differences between the predicted ablation volume in homogeneous and heterogeneous models of typical radiofrequency (RF) procedures for pain relief. A three-dimensional computational domain comprising of the realistic anatomy of the target tissue was considered in the present study. A comparative analysis was conducted for three different scenarios: (a) a completely homogeneous domain comprising of only muscle tissue, (b) a heterogeneous domain comprising of nerve and muscle tissues, and (c) a heterogeneous domain comprising of bone, nerve and muscle tissues. Finite-element-based simulations were performed to compute the temperature and electrical field distribution during conventional RF procedures for treating pain, and exemplified here for the continuous case. The predicted results reveal that the consideration of heterogeneity within the computational domain results in distorted electric field distribution and leads to a significant reduction in the attained ablation volume during the continuous RF application for pain relief. The findings of this study could provide first-hand quantitative information to clinical practitioners about the impact of such heterogeneities on the efficacy of RF procedures, thereby assisting them in developing standardized optimal protocols for different cases of interest.

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“…The knowledge of the location of the blood vessels in the vicinity of tumorous tissue (and, thus, close to the applicator) is crucial for the performance of the therapy as well as for the reliability of a simulation model as e.g. discussed in [1][2][3][4][5]. Unfortunately, the location relative to the applicator varies for each patient and treatment.…”

Section: Introductionmentioning

confidence: 99%

Identification of the blood perfusion rate for laser-induced thermotherapy in the liver

et al. 2020

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Using PDE-constrained optimization we introduce a parameter identification approach which can identify the blood perfusion rate from MR thermometry data obtained during the treatment with laser-induced thermotherapy (LITT). The blood perfusion rate, i.e., the cooling effect induced by blood vessels, can be identified during the first stage of the treatment. This information can then be used by a simulation to monitor and predict the ongoing treatment. The approach is tested with synthetic measurements with and without artificial noise as input data.

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A computational theoretical model for radiofrequency ablation of tumor with complex vascularization

Cited by 15 publications

References 29 publications

Thermal ablation of biological tissues in disease treatment: A review of computational models and future directions

Thermal ablation of biological tissues in disease treatment: A review of computational models and future directions

Domain Heterogeneity in Radiofrequency Therapies for Pain Relief: A Computational Study with Coupled Models

Identification of the blood perfusion rate for laser-induced thermotherapy in the liver

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