Numerical simulation of dual-phase-lag bioheat transfer model during thermal therapy

Kumar, P.; Kumar, Dinesh; Rai, K.N.

doi:10.1016/j.mbs.2016.08.013

Cited by 28 publications

(7 citation statements)

References 45 publications

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“…where Q m0 is reference metabolic heat source coefficient and β is a constant term. The term Q r shows externally generated heat per unit volume of local tissue due to absorption of electromagnetic radiation in tissue, given by Kumar et al, 2 that is,…”

Section: Mathematical Formulationmentioning

confidence: 99%

A numerical study on nonlinear DPL model for analyzing heat transfer in tissue during thermal therapy

Maurya

Kumar²,

Sharma

et al. 2021

Heat Trans

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In the present paper, therapeutic treatment of infected tumorous cells has been studied through mathematical modeling and simulation of heat transfer in tissues by using a nonlinear dual-phase lag bioheat transfer model with Dirichlet boundary condition. The components of volumetric heat source in this model such as blood perfusion and metabolism are assumed experimentally validated temperature-dependent function, which gives more accurate temperature distribution in tissues through this model. We have used the finite difference and RK (4, 5) techniques of numerical methods to solve the proposed problem and obtained the exact solution in a particular case. After comparison, we got a good agreement between them. We have used dimensionless quantities throughout this paper. The effect of relaxation and thermalization time with respect to dimensionless temperature distribution has been analyzed in the treatment process. K E Y W O R D Sexperimental data, heat transfer, nonlinear DPL bioheat transfer model, temperature-dependent blood perfusion, thermal therapy, tissues, temperature-dependent metabolism

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Section: Mathematical Formulationmentioning

confidence: 99%

A numerical study on nonlinear DPL model for analyzing heat transfer in tissue during thermal therapy

Maurya

Kumar²,

Sharma

et al. 2021

Heat Trans

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“…This is also assumed to be the uniform starting temperature. The excess metabolic heat rate Q [W m À3 ] was assumed to be negligible [43]. The last term on the right-hand side is the power absorption P [W m À3 ], which is a function of the electric fieldẼ [V m À1 ]:…”

Section: Treatment and Treatment Planningmentioning

confidence: 99%

Clinical validation of a novel thermophysical bladder model designed to improve the accuracy of hyperthermia treatment planning in the pelvic region

Schooneveldt

Kok

Bakker

et al. 2018

International Journal of Hyperthermia

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2018) Clinical validation of a novel thermophysical bladder model designed to improve the accuracy of hyperthermia treatment planning in the pelvic region, International Journal of Hyperthermia, 35:1, 383-397, ABSTRACTPurpose: Hyperthermia treatment planning for deep locoregional hyperthermia treatment may assist in phase and amplitude steering to optimize the temperature distribution. This study aims to incorporate a physically correct description of bladder properties in treatment planning, notably the presence of convection and absence of perfusion within the bladder lumen, and to assess accuracy and clinical implications for non muscle invasive bladder cancer patients treated with locoregional hyperthermia. Methods: We implemented a convective thermophysical fluid model based on the Boussinesq approximation to the Navier-Stokes equations using the (finite element) OpenFOAM toolkit. A clinician delineated the bladder on CT scans obtained from 14 bladder cancer patients. We performed (1) conventional treatment planning with a perfused muscle-like solid bladder, (2) with bladder content properties without and (3) with flow dynamics. Finally, we compared temperature distributions predicted by the three models with temperature measurements obtained during treatment. Results: Much higher and more uniform bladder temperatures are predicted with physically accurate fluid modeling compared to previously employed muscle-like models. The differences reflect the homogenizing effect of convection, and the absence of perfusion. Median steady state temperatures simulated with the novel convective model (3) deviated on average À0.6 C (À12%) from values measured during treatment, compared to À3.7 C (À71%) and þ1.5 C (þ29%) deviation for the muscle-like (1) and static (2) models, respectively. The Grashof number was 3.2 ± 1.5 Â 10 5 (mean ± SD). Conclusions: Incorporating fluid modeling in hyperthermia treatment planning yields significantly improved predictions of the temperature distribution in the bladder lumen during hyperthermia treatment. ARTICLE HISTORY KEYWORDSHyperthermia treatment planning; fluid modeling; non muscle invasive bladder cancer (NMIBC); mitomycin C (MMC)

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“…Malek and Abbasi used strongly continuous semigroup for solving optimal control subject to PBE (Malek and Abbasi, 2015, 2016). Direct solution for linear and nonlinear dual-phase-lag bioheat transfer model is presented in the literature (Kumar et al, 2016) and (Kumar et al, 2017), respectively. Cao and Lesnic reconstructed the perfusion coefficient and initial temperature simultaneously by optimization methods (Cao and Lesnic, 2019).…”

Section: Introductionmentioning

confidence: 99%

Solving two-dimensional bioheat optimal control problem in solid and vessel domain by pseudospectral discretization

Dastyar

Malek

Yousefi

2022

Transactions of the Institute of Measurement and Control

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In this paper, an optimal control problem subject to an energy transfer equation in thermally significant blood vessel coupled with the Pennes governing equation is solved. The proposed dynamical system is modeled by a system of conduction-reaction and convection-conduction equations. Chebyshev–Gauss–Lobatto (CGL) and Legendre–Gauss–Lobatto (LGL) points are applied to discretize optimal control problem. Then, the problem transferred into a quadratic programming problem using domain decomposition and matching the solution and its first derivative across the related interfaces. The Tikhonov regularization method is used to compute the optimal regularization parameter for the objective function. Some theories have been discussed to prove that the discrete problem has a solution and it is also consistent with the continuous problem. Numerical results are compared and numerical convergent is shown. Optimal and non-optimal external heat source is compared and it is shown that the mathematical modeling is effective in saving the external heat energy. Numerical results show that by this process of heating at the final time, the temperature is very close to the desired temperature without damaging the vessel domain. Numerical results and corresponding graphs are depicted.

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Numerical simulation of dual-phase-lag bioheat transfer model during thermal therapy

Cited by 28 publications

References 45 publications

A numerical study on nonlinear DPL model for analyzing heat transfer in tissue during thermal therapy

A numerical study on nonlinear DPL model for analyzing heat transfer in tissue during thermal therapy

Clinical validation of a novel thermophysical bladder model designed to improve the accuracy of hyperthermia treatment planning in the pelvic region

Solving two-dimensional bioheat optimal control problem in solid and vessel domain by pseudospectral discretization

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