2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA) 2022
DOI: 10.1109/memea54994.2022.9856408
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Measurement of thermal properties of biological tissues and tissue-mimicking phantom with a dual-needle sensor

Abstract: This work presents the measurement of the thermal properties of ex vivo biological tissues (i.e., porcine liver and kidney tissues) as a function of temperature, along with the thermal characterization of a tissue-mimicking agar-based phantom. The evaluation of the thermal properties was performed by the dual needle technique, adopting a sensor equipped with two needles, capable to deliver thermal energy to the biomaterial and monitor the related tissue thermal behavior. Measurements of thermal conductivity, t… Show more

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Cited by 5 publications
(5 citation statements)
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“…Since such processes are dependent upon the concentration of nanoparticles, their relative contribution to photothermal therapy can be controlled, leading to optimal nanoparticle loads, as discussed below. 42 10 0.3 tissue 24 10 750 thermal parameters 0.48% agarose 43 density (ρ) 1.03 g/mL thermal conductivity (k) 0.55 W/(m K) specific heat (c) 4200 J/(kg K) 0.8% agarose 43 density (ρ) 1.06 g/mL thermal conductivity (k) 0.5 W/(m K) specific heat (c) 4200 J/(kg K) tissue 44 density (ρ) 1.1 g/mL thermal conductivity (k) 0.55 W/(m K) specific heat (c) 4200 J/(kg K) other properties 44 blood perfusion 2) a slice in the nanoshell-free agarose medium (black, approximately 2 mm below the nanoshell band in the same NMR tube). In the experiments, a third temperature measurement was obtained as a reference (blue, water).…”
Section: ■ Results and Discussionmentioning
confidence: 99%
“…Since such processes are dependent upon the concentration of nanoparticles, their relative contribution to photothermal therapy can be controlled, leading to optimal nanoparticle loads, as discussed below. 42 10 0.3 tissue 24 10 750 thermal parameters 0.48% agarose 43 density (ρ) 1.03 g/mL thermal conductivity (k) 0.55 W/(m K) specific heat (c) 4200 J/(kg K) 0.8% agarose 43 density (ρ) 1.06 g/mL thermal conductivity (k) 0.5 W/(m K) specific heat (c) 4200 J/(kg K) tissue 44 density (ρ) 1.1 g/mL thermal conductivity (k) 0.55 W/(m K) specific heat (c) 4200 J/(kg K) other properties 44 blood perfusion 2) a slice in the nanoshell-free agarose medium (black, approximately 2 mm below the nanoshell band in the same NMR tube). In the experiments, a third temperature measurement was obtained as a reference (blue, water).…”
Section: ■ Results and Discussionmentioning
confidence: 99%
“…The temperature range of interest set in the thermal bath was ~22 °C to >90 °C, and was divided into 10 steps for porcine kidneys and 9 steps for bovine kidneys. The TEMPOS thermal properties analyzer equipped with an SH-3 dual-needle sensor was used to measure k and α , according to the transient line heat source method [ 7 , 9 , 12 , 33 , 37 , 38 , 39 ]. The adopted measurement instrument based on the transient line heat source method is characterized by several advantages in comparison with standard steady-state techniques for the measurement of thermal properties [ 56 , 57 ].…”
Section: Experimental Procedures and Methods For Data Analysismentioning
confidence: 99%
“…The measurement of thermal properties was performed in steady-state conditions in a temperature-monitored environment by means of the transfer hot-wire technique employing a dual-needle probe. The measurement accuracy of the system was validated by our research group in previous studies [12,33,39], and its accurate reading capability has also been assessed in the present work by testing the measurement instrument on a polymeric standard material. The quantitative values of the measured thermal properties of biological tissues are presented, along with the estimation of the measurement uncertainty, the best-fit regression models interpolating the experimental data, and the analysis of the residual values.…”
Section: Introductionmentioning
confidence: 91%
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“…The thermal properties were then estimated by the analyzer, which computes the minimization of mean square error between the measured temperature changes and those obtained by a mathematical heat transfer model, implemented in the software of the system. In particular, the k and α are estimated by the thermal analyzer through the following equations [11], [18]: 2 4 4…”
Section: Measurement Of the Thermal Propertiesmentioning
confidence: 99%