Thermal Properties Of Biological Tissues Research Articles

Polynomial chaos expansion of SAR and temperature increase variability in 3 T MRI due to stochastic input data

Objective. Numerical simulations are largely adopted to estimate dosimetric quantities, e.g. specific absorption rate (SAR) and temperature increase, in tissues to assess the patient exposure to the radiofrequency (RF) field generated during magnetic resonance imaging (MRI). Simulations rely on reference anatomical human models and tabulated data of electromagnetic and thermal properties of biological tissues. However, concerns may arise about the applicability of the computed results to any phenotype, introducing a significant degree of freedom in the simulation input data. In addition, simulation input data can be affected by uncertainty in relative positioning of the anatomical model with respect to the RF coil. The objective of this work is the to estimate the variability of SAR and temperature increase at 3 T head MRI due to different sources of variability in input data, with the final aim to associate a global uncertainty to the dosimetric outcomes. Approach. A stochastic approach based on arbitrary Polynomial Chaos Expansion is used to evaluate the effects of several input variability’s (anatomy, tissue properties, body position) on dosimetric outputs, referring to head imaging with a 3 T MRI scanner. Main results. It is found that head anatomy is the prevailing source of variability for the considered dosimetric quantities, rather than the variability due to tissue properties and head positioning. From knowledge of the variability of the dosimetric quantities, an uncertainty can be attributed to the results obtained using a generic anatomical head model when SAR and temperature increase values are compared with safety exposure limits. Significance. This work associates a global uncertainty to SAR and temperature increase predictions, to be considered when comparing the numerically evaluated dosimetric quantities with reference exposure limits. The adopted methodology can be extended to other exposure scenarios for MRI safety purposes.

APPLICATION OF STOCHASTIC PARTICLE SWARM OPTIMIZATION ALGORITHM FOR NONINVASIVE DETERMINATION OF TEMPERATURE-DEPENDENT THERMAL PROPERTIES OF BIOLOGICAL TISSUE

The knowledge of thermal properties of biological tissue is of great importance to medical diagnosis and thermotherapy. In this study, an inverse model based on stochastic particle swarm optimization (SPSO) algorithm and sensitivity analysis is developed to determine the temperature-dependent thermal properties of one-dimensional biological tissue. The noninvasive determination task is formulated as an inverse problem which is solved by the SPSO algorithm from the knowledge of surface temperature measurements. A logistic mapping strategy is introduced to improve the quality of the initial particle swarm. Retrieval results demonstrate that the developed inverse technique is robust to determine the temperature-dependent thermal conductivity, specific heat and blood perfusion rate of biological tissue. The maximum relative error of the simultaneous determination results is less than 0.8%. The maximum determination error is 1.15% when a 3% random deviation is considered. Meanwhile, the present SPSO algorithm is proved to be more efficient and accurate than other intelligent algorithms. Considering the convergence accuracy and computational time, the population size of the SPSO algorithm is suggested to be M = 80.

One-Dimensional Systemic Modeling of Thermal Sensors Based on Miniature Bead-Type Thermistors.

Accurate measurements of thermal properties is a major concern, for both scientists and the industry. The complexity and diversity of current and future demands (biomedical applications, HVAC, smart buildings, climate change adapted cities, etc.) require making the thermal characterization methods used in laboratory more accessible and portable, by miniaturizing, automating, and connecting them. Designing new materials with innovative thermal properties or studying the thermal properties of biological tissues often require the use of miniaturized and non-invasive sensors, capable of accurately measuring the thermal properties of small quantities of materials. In this context, miniature electro-thermal resistive sensors are particularly well suited, in both material science and biomedical instrumentation, both in vitro and in vivo. This paper presents a one-dimensional (1D) electro-thermal systemic modeling of miniature thermistor bead-type sensors. A Godunov-SPICE discretization scheme is introduced, which allows for very efficient modeling of the entire system (control and signal processing circuits, sensors, and materials to be characterized) in a single workspace. The present modeling is applied to the thermal characterization of different biocompatible liquids (glycerol, water, and glycerol–water mixtures) using a miniature bead-type thermistor. The numerical results are in very good agreement with the experimental ones, demonstrating the relevance of the present modeling. A new quasi-absolute thermal characterization method is then reported and discussed. The multi-physics modeling described in this paper could in the future greatly contribute to the development of new portable instrumental approaches.

Measurement of Ex Vivo Liver, Brain and Pancreas Thermal Properties as Function of Temperature.

The ability to predict heat transfer during hyperthermal and ablative techniques for cancer treatment relies on understanding the thermal properties of biological tissue. In this work, the thermal properties of ex vivo liver, pancreas and brain tissues are reported as a function of temperature. The thermal diffusivity, thermal conductivity and volumetric heat capacity of these tissues were measured in the temperature range from 22 to around 97 °C. Concerning the pancreas, a phase change occurred around 45 °C; therefore, its thermal properties were investigated only until this temperature. Results indicate that the thermal properties of the liver and brain have a non-linear relationship with temperature in the investigated range. In these tissues, the thermal properties were almost constant until 60 to 70 °C and then gradually changed until 92 °C. In particular, the thermal conductivity increased by 100% for the brain and 60% for the liver up to 92 °C, while thermal diffusivity increased by 90% and 40%, respectively. However, the heat capacity did not significantly change in this temperature range. The thermal conductivity and thermal diffusivity were dramatically increased from 92 to 97 °C, which seems to be due to water vaporization and state transition in the tissues. Moreover, the measurement uncertainty, determined at each temperature, increased after 92 °C. In the temperature range of 22 to 45 °C, the thermal properties of pancreatic tissue did not change significantly, in accordance with the results for the brain and liver. For the three tissues, the best fit curves are provided with regression analysis based on measured data to predict the tissue thermal behavior. These curves describe the temperature dependency of tissue thermal properties in a temperature range relevant for hyperthermia and ablation treatments and may help in constructing more accurate models of bioheat transfer for optimization and pre-planning of thermal procedures.

Temperature dependence of thermal properties of ex vivo liver tissue up to ablative temperatures

Thermal properties of ex vivo bovine liver were measured as a function of temperature, by heating tissue samples in a temperature-controlled oil bath over a temperature range from about 21 °C to about 113 °C. Results evidenced temperature-dependent non-linear changes of the thermal properties, with the temperature of 100 °C representing a break point: the thermal properties increased with temperature up to 99 °C and then decreased above 100 °C. The rate of increase appeared dramatic between 90 °C and 99 °C, owing to the onset of vaporisation of water contained in the tissue. In particular, at 99 °C, the thermal conductivity reported an increase of about four times with respect to the value measured at 90 °C, whilst about a two-fold increase was reported for both the volumetric heat capacity and the thermal diffusivity. Temperatures higher than 100 °C were reached only after complete vaporisation of water contained in the tissue, resulting in about 70% loss of weight from the tissue. An overall decrease of about 71% and 63% was reported for the thermal conductivity and volumetric heat capacity, respectively, in the temperature range 101 °C–113 °C. A decrease of about 25% was reported in the measured values of the thermal diffusivity in the temperature range 101 °C–108 °C, whilst a slight increase of measured values, not statistically significant, was observed in the temperature range 108 °C–113 °C. The temperature dependent changes of the thermal parameters were modelled with non-linear regression analysis to calculate the best-fit curves interpolating measured data. The proposed regression models could be used to numerically assess the changes in the thermal properties of biological tissues at supra-physiological temperatures relevant in thermal ablation procedures, as well as their effect on the prediction of the ablation zone dimensions in computational models for treatment planning.

Measurement of thermal and ultrasonic properties of some biological tissues

The measurement of thermal and ultrasonic properties of biological tissues is essential for the assessment of the temperature rise induced in vivo by diagnostic ultrasound. In this paper, we present measurements of thermal conductivity, thermal diffusivity, speed of sound and ultrasonic attenuation of fresh ex vivo porcine tissue, namely ‘muscle’ (from abdomen and leg), ‘skin with subcutaneous fat’ (from abdomen and leg), ‘abdominal fat’ and ‘bone’. The measurements of the thermal properties of biological tissue samples are based on a transient method. Thermal property measurements show that subcutaneous fat has the lowest thermal conductivity (0.23 W m−1 K−1), while muscle gives the highest values (0.46 W m−1 K−1). Thermal diffusivity of muscle tissue recorded the highest value among the studied tissues (0.16 mm2 s−1) while that of skin with subcutaneous fat gave the lowest value (0.11 mm2 s−1). A scanning acoustic macroscope was used to measure attenuation coefficient and speed of sound for the tissue samples. The results for the speed of sound are broadly similar to those reported in the literature. The power law dependence of the attenuation coefficient of the form η = a f b as a function of frequency was found to be more appropriate than the linear fit in this study.

Temperature-Change-Based Thermal Tomography

Thermal properties of biological tissues play a critical role in the study of tumor angiogenesis and the design and monitoring of thermal therapies. To map thermal parameters noninvasively, we propose temperature-change-based thermal tomography (TTT) that relies on relative temperature mapping using magnetic resonance imaging (MRI). Our approach is unique in two aspects: (1) the steady-state body temperature in thermal equilibrium is not restricted to be spatially invariant, and (2) absolute temperature mapping is not required. These two features are physiologically realistic and technically convenient. Our numerical simulation indicates that a (9 mm)3 tumor inside a breast phantom can be reliably depicted, assuming moderate temperature mapping accuracy of 0.5°C.

Experimental and Numerical Study of One, Two, and Three Embedded Needle Cryoprobes Simultaneously Operated by High Pressure Argon Gas

One, two, and three needle cryoprobes, 1.47mm outside diameter, simultaneously and uniformly operated by high pressure argon gas, were tested in a gel simulating the thermal properties of biological tissues. The probes were inserted into the same depth in the gel through two parallel templates with holes drilled on a 5×5mm2 mesh. The temperature of the active segment of the probe was monitored by a single soldered thermocouple (TC). Temperatures in the gel were monitored by K-type TC strings in the radial, and in the downward and upward axial directions. The phase-change problem in the gel was solved by ANSYS7.0, based on the enthalpy method. Calculated and measured results compared reasonably well with the most deviations observed in the upward axial direction. Results of this study may be summarized as follows: (a) Due to the cylindrical structure of the probe, the advancement of the frozen fronts was more pronounced in the upward axial and the radial directions than in the downward direction. (b) The farthest placement of the two probes (10mm) yielded the largest volumes enclosed by the isothermal contours. (c) In the tightest two placement configurations of the three probes, the −40°C fronts of all frozen lumps have joined together even after 1min of operation, while in the less tight configurations, joining occurred later. (d) In multiprobe applications and for a given duration of application, there exists a certain placement configuration that will produce the maximal volume of any temperature-specific frozen lump. The computational tool presented in this study could assist the surgeon in the preplanning of cryosurgical procedures and thus reduce uncertainties and enhance its success rate.

Photoacoustic study of thermal properties of biological tissues detected by PVDF film transducer

A PVDF piezoelectric film transducer is used in a photoacoustic piezoelectric technique for studying thermal diffusivities of biological tissues. The experimental precision may be improved by using PVDF films because the acoustic impedance of PVDF films is close to that of biological tissues. Thermal diffusivities of several fresh porcine tissues in vitro are studied and the results are compared with previously obtained ones.