Mathematical Modeling of Skin Bioheat Transfer

Cells and tissues undergo complex physical processes during cryopreservation. Understanding the underlying physical phenomena is critical to improve current cryopreservation methods and to develop new techniques. Here, we describe multiscale approaches for modelling cell and tissue cryopreservation including heat transfer at macroscale level, crystallization, cell volume change and mass transport across cell membranes at microscale level. These multi-scale approaches allow us to study cell and tissue cryopreservation.

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“…The simplest example of the DPL model is its first-order Taylor expansions for both q and T , given as (Xu et al 2008a(Xu et al , 2009 …”

Section: Ii) Dual-phase-lag Modelmentioning

confidence: 99%

Multi-scale heat and mass transfer modelling of cell and tissue cryopreservation

Moon

Zhang

et al. 2010

Phil. Trans. R. Soc. A.

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“…Recent progress on the bioheat transfer of skin tissue, thermal damage, thermomechanics, and thermal pain has been systematically reviewed by Xu et al [15]. Among various useful gathered information, in Sect.…”

Section: Bioheat Transfermentioning

confidence: 98%

“…As mentioned in Sect. 1.4, currently, there are two published review papers about the thermal transport and lagging behavior in living tissues such as the human skin [15,16].…”

Section: Phase-lagging In Bio-engineeringmentioning

confidence: 99%

“…A similar procedure is used to combine the DPL model with the Pennes' bioheat equation. The mathematical modeling of skin bioheat transfer has been presented by Xu et al [15], in which three versions of the DPL model are considered. There are many other articles about the simulation of bioheat transfer by employing the DPL model as the constitutive law [23][24][25][26][27].…”

Section: Thermal Wave Model Bioheat Transfermentioning

confidence: 99%

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Macro- to Nanoscale Heat and Mass Transfer: The Lagging Behavior

2015

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The classical model of the Fourier's law is known as the most common constitutive relation for thermal transport in various engineering materials. Although the Fourier's law has been widely used in a variety of engineering application areas, there are many exceptional applications in which the Fourier's law is questionable. This paper gathers together such applications. Accordingly, the paper is divided into two parts. The first part reviews the papers pertaining to the fundamental theory of the phase-lagging models and the analytical and numerical solution approaches. The second part wrap ups the various applications of the phase-lagging models including the biological materials, ultra-high-speed laser heating, the problems involving moving media, micro/nanoscale heat transfer, multi-layered materials, the theory of thermoelasticity, heat transfer in the material defects, the diffusion problems we call as the non-Fick models, and some other applications. It is predicted that the interest in the field of phase-lagging heat transport has grown incredibly in recent years because they show good agreement with the experiments across a wide range of length and time scales.

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“…Nowadays TH imaging is a well−established method for health monitoring and examinations, as well as for assisting diagnosis [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. Recently, it was demonstrated that the TH measurements supplemented by the mathematical model offer a new approach to the quantification of allergen−in− duced skin reactions [23].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of allergic response using dynamic thermography

Rokita

Rok

Tatoń

2015

Opto-Electronics Review

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Skin dynamic termography supplemented by a mathematical model is presented as an objective and sensitive indicator of the skin prick test result. Termographic measurements were performed simultaneously with routine skin prick tests. The IR images were acquired every 70 s up to 910 s after skin prick. In the model histamine is treated as the principal mediator of the allergic reaction. Histamine produces vasolidation and the engorged vessels are responsible for an increase in skin temperature. The model parameters were determined by fitting the analytical solutions to the spatio-temporal distributions of the differences between measured and baseline temperatures. The model reproduces experimental data very well (coefficient of determination = 0.805÷0.995). The method offers a set of parameters to describe separately skin allergic reaction and skin reactivity. The release of histamine after allergen injection is the best indicator of allergic response. The diagnostic parameter better correlates with the standard evaluation of a skin prick test (correlation coefficient = 0.98) than the result of the thermographic planimetric method based on temperature and heated area determination (0.81). The high sensitivity of the method allows for determination of the allergic response in patients with the reduced skin reactivity.

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Mathematical Modeling of Skin Bioheat Transfer

Cited by 192 publications

References 305 publications

Multi-scale heat and mass transfer modelling of cell and tissue cryopreservation

Multi-scale heat and mass transfer modelling of cell and tissue cryopreservation

Macro- to Nanoscale Heat and Mass Transfer: The Lagging Behavior

Evaluation of allergic response using dynamic thermography

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