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When modeling heat propagation in biological bodies, a non-negligible relaxation time (typically between 15-30 s) is required for the thermal waves to accumulate and transfer, i.e. thermal waves propagate at a finite velocity. To accommodate for this feature that is characteristic to heat transfer in biological bodies, the classical Fourier's law has to be modified resulting in the thermal-wave model of bio-heat transfer. The purpose of the paper is to retrieve the space-dependent blood perfusion coefficient in such a thermal-wave model of bio-heat transfer from final time temperature measurements.

The non-linear and ill-posed blood perfusion coefficient identification problem is reformulated as a non-linear minimization problem of a Tikhonov regularization functional subject to lower and upper simple bounds on the unknown coefficient. For the numerical discretization, an unconditionally stable direct solver based on the Crank–Nicolson finite difference scheme is developed. The Tikhonov regularization functional is minimized iteratively by the built-in routine lsqnonlin from the MATLAB optimization toolbox. Both exact and numerically simulated noisy input data are inverted.

The reconstruction of the unknown blood perfusion coefficient for three benchmark numerical examples is illustrated and discussed to verify the proposed numerical procedure. Moreover, the proposed algorithm is tested on a physical example which consists of identifying the blood perfusion rate of a biological tissue subjected to an external source of laser irradiation. The numerical results demonstrate that accurate and stable solutions are obtained.

Although previous studies estimated the important thermo-physical blood perfusion coefficient, they neglected the wave-like nature of heat conduction present in biological tissues that are captured by the more accurate thermal-wave model of bio-heat transfer. The originalities of the present paper are to account for such a more accurate thermal-wave bio-heat model and to investigate the possibility of determining its space-dependent blood perfusion coefficient from temperature measurements at the final time.

The main objective of this paper is to investigate the response of human skin to an intense temperature drop at the surface. In addition, this paper aims to evaluate the efficiency of finite difference and finite volume methods in solving the highly nonlinear form of Pennes’ bioheat equation.

One-dimensional linear and nonlinear forms of Pennes’ bioheat equation with uniform grids were used to study the behavior of human skin. The specific heat capacity, thermal conductivity and blood perfusion rate were assumed to be linear functions of temperature. The nonlinear form of the bioheat equation was solved using the Newton linearization method for the finite difference method and the Picard linearization method for the finite volume method. The algorithms were validated by comparing the results from both methods.

The study demonstrated the capacity of both finite difference and finite volume methods to solve the one-dimensional and highly nonlinear form of the bioheat equation. The investigation of human skin’s thermal behavior indicated that thermal conductivity and blood perfusion rate are the most effective properties in mitigating a surface temperature drop, while specific heat capacity has a lesser impact and can be considered constant.

This paper modeled the transient heat distribution within human skin in a one-dimensional manner, using temperate-dependent physical properties. The nonlinear equation was solved with two numerical methods to ensure the validity of the results, despite the complexity of the formulation. The findings of this study can help in understanding the behavior of human skin under extreme temperature conditions, which can be beneficial in various fields, including medical and engineering.

Cancer is the foremost disease that causes death. The objective of hyperthermia in cancer therapy is to raise the temperature of cancerous tissue above a therapeutic value while maintaining the surrounding normal tissue at sublethal temperature values in cases where surgical intervention is dangerous or impossible. The malignant tissue is heated up to 42°C in the treatment. In this method, the unaffected tissues are aimed to have minimum damage, while the affected ones are destroyed. Therefore, it is very important for the optimization of the method to know the temperature profiles in both tissues. Accurately estimating the tissue temperatures has been a very important issue for tumor hyperthermia treatment planning. This paper, proposes to theoretically predict the temperature response of the biological tissues subject to external EM heating by using the space‐dependent blood perfusion term in Pennes bio‐heat equation.

The bio‐heat transfer equation is parabolic partial differential equation. Grid points including independent variables are initially formed in solution of partial differential equation by finite element method. In this study, one dimensional bio‐heat transfer equation is solved by flex‐PDE finite element method.

In this study, the bio‐heat transfer equation is solved for variable blood perfusion values and the temperature field resulting after a hyperthermia treatment is obtained. Homogeneous, non‐homogeneous tissue and constant, variable blood perfusion rates are considered in this study to display the temperature fields in the biological material exposed to externally induced electromagnetic irradiation.

Temperature‐dependent tissue thermophysical properties have been used and the Pennes equation is solved by FEM analysis. Variable blood perfusion and heat generation values have been used in calculations for healthy tissue and tissue with tumor.

The purpose of this paper is to present an inverse analysis procedure based on a coupled numerical formulation through which the coefficients describing non‐linear thermal properties of blood perfusion may be identified.

The coupled numerical technique involves a combination of the dual reciprocity boundary element method (DRBEM) and a genetic algorithm (GA) for the solution of the Pennes bioheat equation. Both linear and quadratic temperature‐dependent variations are considered for the blood perfusion.

The proposed DRBEM formulation requires no internal discretisation and, in this case, no internal nodes either, apart from those defining the interface tissue/tumour. It is seen that the skin temperature variation changes as the blood perfusion increases, and in certain cases flat or nearly flat curves are produced. The proposed algorithm has difficulty to identify the perfusion parameters in these cases, although a more advanced genetic algorithm may provide improved results.

The coupled technique allows accurate inverse solutions of the Pennes bioheat equation for quantitative diagnostics on the physiological conditions of biological bodies and for optimisation of hyperthermia for cancer therapy.

The proposed technique can be used to guide hyperthermia cancer treatment, which normally involves heating tissue to 42‐43°C. When heated up to this range of temperatures, the blood flow in normal tissues, e.g. skin and muscle, increases significantly, while blood flow in the tumour zone decreases. Therefore, the consideration of temperature‐dependent blood perfusion in this case is not only essential for the correct modelling of the problem, but also should provide larger skin temperature variations, making the identification problem easier.

The purpose of this paper is to present the computational model of the neonate’s brain cooling process. The main aim of the analysis is to tune the developed computational model, make it convergent and representing the hypothermia therapy reasonably. To find the appropriate model parameters the trial of an inverse analysis, based on the standard least-square method, is performed. Having partially validated model the number of numerical simulations are carried out to compare their results with measurements made during real therapy.

The geometrical model of the newborn’s body is built using MRI and CT scans utilizing Mimics software and the Design Modeler while Ansys Fluent with its User Defined Function capability was used to implement the whole model and to carry out simulations. To model the bioheat transfer the Pennes bioheat equation is applied. In the mathematical model blood perfusion rate, metabolic heat generation rate as well as the arterial blood temperature are dependent on the tissue temperature. In order to determine the proper values of model parameters of bioheat transport in neonate’s body the attempt to inverse analysis is also performed.

The performed inverse analysis resulted in the values of model parameters (metabolic heat sources, blood perfusions etc.). Tuned model was then applied to simulate brain cooling process with reasonable accuracy. Obtained model parameters were also compared to the data obtained from neonatologists.

The presented numerical model still requires tests and simulations. The results from the inverse analysis based on the real measurements can be very valuable.

The determination of the proper parameters of the bioheat transfer in the neonatal body can finally be used to control the numerical simulations of the brain cooling process. The simulation of the re-warming process after hypothermic therapy can be improved considerably.

The performance of the numerical simulations of the brain cooling process in the proper way can finally helps protect newborns’ health and life.

In the paper 3-D real geometrical model of the newborn’s body includes head, torso and limbs and different types of tissues are distinguished in the model. The considered bioheat transfer problem is also fully 3-D. This model is then utilised together with inverse analysis in order to determine the model parameters for the newborn’s body.

The purpose of this paper is to derive the Trefftz functions (T-functions) for the Pennes’ equation and for the single-phase-lag (SPL) model (hyperbolic equation) with perfusion and then comparing field of temperature in a flat slab made of skin in the case when perfusion is taken into account, with the situation when a Fourier model is considered. When considering the process of heat conduction in the skin, one needs to take into account the average values of its thermal properties. When in biological bodies relaxation time is of the order of 20 s, the thermal wave propagation appears. The initial-boundary problems for Pennes’ model and SPL with perfusion model are considered to investigate the effect of the finite velocity of heat in the skin, perfusion and thickness of the slab on the rate of the thermal wave attenuation. As a reference model, the solution of the classic Fourier heat transfer equation for the considered problems is calculated. A heat flux has direction perpendicular to the surface of skin, considered as a flat slab. Therefore, the equations depend only on time and one spatial variable.

First of all the T-functions for the Pennes’ equation and for the SPL model with perfusion are derived. Then, an approximate solutions of the problems are expressed in the form of a linear combination of the T-functions. The T-functions satisfy the equation modeling the problem under consideration. Therefore, approximating a solution of a problem with a linear combination of n T-functions one obtains a function that satisfies the equation. The unknown coefficients of the linear combination are obtained as a result of minimization of the functional that describes an inaccuracy of satisfying the initial and boundary conditions in a mean-square sense.

The sets of T-functions for the Pennes’ equation and for the SPL model with perfusion are derived. An infinite set of these functions is a complete set of functions and stands for a base functions layout for the space of solutions for the equation used to generate them. Then, an approximate solutions of the initial-boundary problem have been found and compared to find out the effect of finite velocity of heat in the skin, perfusion and thickness of the slab on the rate of the thermal wave attenuation.

The methods used in the literature to find an approximate solution of any bioheat transfer problems are more complicated than the one used in the presented paper. However, it should be pointed out that there is some limitation concerning the T-function method, namely, the greater number of T-function is used, the greater condition number becomes. This limitation usually can be overcome using symbolic calculations or conducting calculations with a large number of significant digits.

The T-functions for the Pennes’ equation and for the SPL equation with perfusion have been reported in this paper for the first time. In the literature, the T-functions are known for other linear partial differential equations (e.g. harmonic functions for Laplace equation), but for the first time they have been derived for the two aforementioned equations. The results are discussed with respect to practical applications.

The purpose of this study is to evaluate the impact of external head cooling on alleviating the heat stress in the human body by analyzing the temperatures of the core body (T_c), blood (T_blood) and head (T_h) during exercise conditions using 3D whole body model.

Computational study is conducted to comprehend the influence of external head cooling on T_c, T_blood and T_h. The Pennes bioheat and energy balance equations formulated for the whole-body model are solved concurrently to obtain T_c, T_blood and T_h for external head cooling values from 33 to 233 W/m². Increased external head cooling of 404 W/m² is used to compare the numerical and experimental Th data.

Significant reductions of 0.21°C and 0.38°C are observed in Th with external head cooling of 233 and 404 W/m², respectively. However, for external head cooling of 233 W/m², lesser reductions of 0.03°C and 0.06°C are found in T_c and T_blood, respectively. Computational results for external head cooling of 404 W/m² show a difference of 15 per cent in T_h compared to experimental values from literature.

The development of stress because of heat generated within human body is major concern for athletes exercising at high intensities. This study provides an insight into the effectiveness of external head cooling in regulating the head and body temperatures during exercise conditions.

The large blood vessels (LBV) would act as a heat sink and hence play a significant role during photo-thermal therapy. Gold nanoshell was considered as a high-heat absorbing agent in photo-thermal heating to reduce the cooling effect of LBV. The heat sink effect of LBV results in insignificant irreversible tissue thermal damage. The paper aims to discuss these issues.

In this paper, the thermal history of tissue embedded with LBV during photo-thermal heating were calculated using finite element-based simulation technique. A volumetric laser source term based on modified Beer-Lambert law was introduced to model laser heating. The numerically predicted temperature drop was validated against that of previously performed experiments by the authors on tissue mimic embedded with simulated blood vessels. In the later part of the study, Arrhenius equation was coupled with the energy equation to investigate and report the irreversible thermal damage to the bio-tissues.

The results obtained conclude that tissue with different orientation of blood vessels results in different thermal response at the tissue surface. Gold nanoshells were introduced into the laser irradiated tissue to overcome the cooling effect of LBV during plasmonic photo-thermal heating. The effect of size and concentration of nanoparticles on tissue heating were analyzed. The predicted damage parameter was much lower in case of tissue embedded with blood vessel than that predicted in case of bare tissue, which results in incomplete tissue necrosis. Finally, the effects of laser specification, blood vessel specification and blood perfusion on the tissue thermal damage were examined.

The conjugate energy equations in conjunction with Arrhenius equation were solved numerically to predict the tissue irreversible damage embedded with LBV.

This study aims to at numerically retrieve five constant dimensional thermo-physical properties of a biological tissue from dimensionless boundary temperature measurements.

The thermal-wave model of bio-heat transfer is used as an appropriate model because of its realism in situations in which the heat flux is extremely high or low and imposed over a short duration of time. For the numerical discretization, an unconditionally stable finite difference scheme used as a direct solver is developed. The sensitivity coefficients of the dimensionless boundary temperature measurements with respect to five constant dimensionless parameters appearing in a non-dimensionalised version of the governing hyperbolic model are computed. The retrieval of those dimensionless parameters, from both exact and noisy measurements, is successfully achieved by using a minimization procedure based on the MATLAB optimization toolbox routine lsqnonlin. The values of the five-dimensional parameters are recovered by inverting a nonlinear system of algebraic equations connecting those parameters to the dimensionless parameters whose values have already been recovered.

Accurate and stable numerical solutions for the unknown thermo-physical properties of a biological tissue from dimensionless boundary temperature measurements are obtained using the proposed numerical procedure.

The current investigation is limited to the retrieval of constant physical properties, but future work will investigate the reconstruction of the space-dependent blood perfusion coefficient.

As noise inherently present in practical measurements is inverted, the paper is of practical significance and models a real-world situation.

The findings of the present paper are of considerable significance and interest to practitioners in the biomedical engineering and medical physics sectors.

In comparison to Alkhwaji et al. (2012), the novelty and contribution of this work are as follows: considering the more general and realistic thermal-wave model of bio-heat transfer, accounting for a relaxation time; allowing for the tissue to have a finite size; and reconstructing five thermally significant dimensional parameters.

This paper aims to test the inverse analysis, based on the standard least-square method, which will finally lead to find the appropriate parameters of modelling of the brain cooling process.

To test the presented in this paper method of inverse analysis the numerical simulations of the bioheat transfer process in the neonatal body were performed. To model the bioheat transfer the Pennes bioheat equation and the modified Fiala model were applied.

The performed tests of the inverse analysis proved that it is possible to estimate the proper parameters of the process using this tool, but always with the small mistake.

The presented method still requires a lot of tests. The test with the data from real measurements can be very valuable.

The determination of the proper parameters of the bioheat transfer in the neonatal body can finally be used to perform the numerical simulations of the brain cooling process.

The performance of the numerical simulations of the brain cooling process in the proper way can finally helps protect newborns’ health and life.

In the paper the attempt of the inverse analysis in order to determine the parameters of bioheat transfer in the newborn's body is made.