Thermal Analysis of the Increasing Subcutaneous Fat Thickness Within the Human Skin—A Numerical Study

Abstract

This article reports a numerical study on the thermal response of skin with increasing fat thickness. The study considers the Pennes bioheat model for skin to simulate the thermal recovery phase after the removal of undercooled condition. Based on the surface thermal maps of a three-dimensional skin, the change in fat thickness within the skin is characterized. Sensitivity study reveals that the major variation in the thermal pattern at the skin surface is mainly due to the change in fat thickness. Possible random noise associated with background disturbances is also considered to determine the associated signal-to-noise ratio.

Numerical study of high‐intensity focused ultrasound (HIFU) in fat reduction

“…These characterizations with a penetration depth of 13 mm are widely used in the treatment of body contouring in medical clinics 39 . The thickness of the layers is selected as 3.00 mm water layer, 2.35 mm skin layer, 29 and 8.00, 10.00, 12.00, 14.00, 16.00, 18.00, 20.00, 24.00 mm fat layer. The λ /4 spatial resolution is equal to 9 × 10 −5 m, and the time step is in the range 0 and the final time according to the relation l / c for each length of the geometry (varies from 9 to 25 μs depending on the thickness of 8–24 mm).…”

“…⃗ n is a normal vector of a surface. The initial conditions for the acoustic equations are p = 0 and TA B L E 1 Physical properties of the two layers of skin, fat, and also, water as matching layers [29][30][31][32][33] = 0, and the initial condition for solving the heat transfer is defined as T = T 0 = 310 K.…”

Suitability of frequency modulated thermal wave imaging for skin cancer detection—A theoretical prediction

“…The infrared (IR) imaging techniques are quite useful for pre-and postclinical evaluation, since these techniques are relatively fast and can be utilized repetitively for longer span without the risk of radiation. At present, IR imaging techniques are widely used in many biomedical applications, viz., detection of early skin cancer (Bonmarin and Le Gal, 2014a;Bhowmik et al, 2014b) and breast cancer (Lawson, 1956), estimation of skin temperature oscillation due to subsurface blood flow (Sagaidachnyi et al, 2014), estimation of burn injury (Cole et al, 1990), monitoring the efficacy of drugs (Hintersteiner et al, 2005) and treatment (Santa Cruz et al, 2009), vascular disorders (Bagavathiappan et al, 2009), pains (Gulevich et al, 1997), monitoring the thermal response of skin surface during photo-thermal ablation of subsurface tumor (Sajjadi et al, 2008;Paul et al, 2014), aftermaths of cryo-therapy (Costello et al, 2012), evaluation of the state of biological implant (Yang et al, 2009), detection and characterization of subsurface chromophores in biological materials (Milner et al, 1995;Milner et al, 1996;Telenkov et al, 2002), estimation of increasing fat thickness (Bhowmik et al, 2015), thermal tomography (Shi et al, 2014), and many more (Diakides and Bronzino, 2007). The advancement and deeper understanding of bio-optics, digital manipulation, image processing, thermal and physiological characteristics of human body made the thermography a capable technique to evaluate the subsurface changes efficiently.…”

Theoretical analysis on thermal treatment of skin with repetitive pulses

“…The effects of temperature-dependent parameters of the multi-layer breast model, such as electrical and thermal conductivities, were considered. Bhowmik 8 carried out a numerical study on the thermal response of skin with different fat thickness. The Pennes model and the numerical simulation method were employed to derive the temperature distribution of the skin tissue.…”