Numerical Investigation of Magnetic Nanoparticles Distribution Inside a Cylindrical Porous Tumor Considering the Influences of Interstitial Fluid Flow

Zakariapour, Mostafa; Hamedi, Mohammad-Hossein; Fatouraee, Nasser

doi:10.1007/s11242-016-0772-1

Cited by 12 publications

(4 citation statements)

References 32 publications

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“…(11). The mass transfer equation can then be used for describing the behavior of nanofluid diffusion after injection when the velocity gap between the MNPs and interstitial flow is ignored, [32] ∂C…”

Section: -3mentioning

confidence: 99%

Thermal apoptosis analysis considering injection behavior optimization and mass diffusion during magnetic hyperthermia

Tang¹,

Zou²,

Flesch³

et al. 2022

Chinese Phys. B

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Thermally induced apoptosis for tumors depends mainly on the intrinsic characteristics of biological tissues as well as treatment temperature profile during magnetic hyperthermia. Further, treatment temperature distribution inside tumor depends on the injection behavior of irregular tumors, such as the injection dose and the injection location of nanofluids. In order to improve the treatment effect, the simulated annealing algorithm is adopted in this work to optimize the nanofluid injection behavior, and the improved Arrhenius model is used to evaluate the malignant ablations for three typical malignant tumor cell models. In addition, both the injection behavior optimization and the mass diffusion of nanofluid are both taken into consideration in order to improve the treatment effect. The simulation results demonstrate that the injection behavior can be optimized effectively by the proposed optimization method before therapy, the result of which can also conduce to improving the thermal apoptosis possibility for proposed typical malignant cells. Furthermore, an effective approach is also employed by considering longer diffusion duration and correct power dissipation at the same time. The results show that a better result can then be obtained than those in other cases when the power dissipation of MNPs is set to be Q MNP = 5.4 × 107 W·m3 and the diffusion time is 16 h.

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Section: -3mentioning

confidence: 99%

Thermal apoptosis analysis considering injection behavior optimization and mass diffusion during magnetic hyperthermia

Tang¹,

Zou²,

Flesch³

et al. 2022

Chinese Phys. B

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“…The interstitial pressure can be calculated by solving equation (6) with the finite element method and then the interstitial velocity can be obtained using Darcy's law. Based on the resulting interstitial velocity, the interstitial transfer of MNPs can be described by the convection diffusion equation as a result of the conservation laws of mass and momentum [16,22]:…”

Section: Mass Transfer and Diffusion In Interstitiummentioning

confidence: 99%

“…Sefidar et al proposed an advanced numerical method to solve the fluid flow and solute transport equations, and investigated the effect of tumor shape and size on drug delivery to solid tumors [15]. Furthermore, Zakariapour et al proposed a numerical simulation of interstitial fluid and blood flows and diffusion of MNPs based on the governing equation for the fluid flow, considering the tumor to be a rigid porous media [16]. Those two works present relevant contrib utions to the modeling of MNPs spatial distribution after injection, but they do not present any temperature analysis.…”

Section: Introductionmentioning

confidence: 99%

Numerical investigation of temperature field in magnetic hyperthermia considering mass transfer and diffusion in interstitial tissue

Tang

Flesch

Jin

2017

J. Phys. D: Appl. Phys.

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Magnetic nanoparticle (MNP) hyperthermia ablates malignant cells by heating the region of interest when MNPs are subjected to an external alternating magnetic field. The energy density to be dissipated into heat, and consequently the temperature profile during treatment, depends on the distribution of MNPs within the tumoral region. This paper uses numerical models to evaluate the temporal and spatial temperature distributions inside a tumor when intratumoral injection of MNPs is considered. To this end, the theories of mass transfer and diffusion in interstitial tissue are combined with Rosensweig’s theory and Pennes bio-heat transfer equation, and the finite element method is used for analyzing the temperature field under different scenarios. Simulation results demonstrate that the treatment temperature field strongly depends on factors, such as the injection method, particle size, injection concentration and injection dose. However, the maximal temperature reached during hyperthermia and the effective treatment area are difficult to control. In order to obtain better treatment effects, this paper investigates a solution that uses a kind of material with low Curie temperature and the results show that the effective treatment area of hyperthermia can be significantly improved using this type of MNP.

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“…Diffusion processes can also be studied using gel samples immersed in a liquid different from their pore fluid (Hæreid et al 1995 ), or gel samples injected with ferrofluid (Salloum et al 2008 ). Numerical simulations predict ferrofluid flow and nanoparticle diffusion in cancer cells (Zakariapour et al 2016 ). The results of these studies show that ferrofluid can diffuse in the gel pore structure, thus providing potentially useful impregnation methods.…”

Section: Introductionmentioning

confidence: 99%

Ferrofluid Impregnation Efficiency and Its Spatial Variability in Natural and Synthetic Porous Media: Implications for Magnetic Pore Fabric Studies

2022

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Magnetic pore fabrics (MPF) are an efficient way to characterize pore space anisotropy, i.e., the average pore shape and orientation. They are determined by impregnating rocks with ferrofluid and then measuring their magnetic anisotropy. Obtaining even impregnation of the entire pore space is key for reliable results, and a major challenge in MPF studies. Here, impregnation efficiency and its spatial variability are systematically tested for natural (wood, rock) and synthetic (gel) samples, using oil- and water-based ferrofluids, and comparing various impregnation methods: percolation, standard vacuum impregnation, flowthrough vacuum impregnation, immersion, diffusion, and diffusion assisted by magnetic forcing. Seemingly best impregnation was achieved by standard vacuum impregnation and oil-based ferrofluid (76%), and percolation (53%) on rock samples; however, sub-sampling revealed inhomogeneous distribution of the fluid within the samples. Flowthrough vacuum impregnation yielded slightly lower bulk impregnation efficiencies, but more homogeneous distribution of the fluid. Magnetically assisted diffusion led to faster impregnation in gel samples, but appeared to be hindered in rocks by particle aggregation. This suggests that processes other than the mechanical transport of nanoparticles in the pore space need to be taken into account, including potential interactions between the ferrofluid and rock, particle aggregation and filtering. Our results indicate that bulk measurements are not sufficient to assess impregnation efficiency. Since spatial variation of impregnation efficiency may affect MPF orientation, degree and shape, impregnation efficiency should be tested on sub-samples prior to MPF interpretation.

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Numerical Investigation of Magnetic Nanoparticles Distribution Inside a Cylindrical Porous Tumor Considering the Influences of Interstitial Fluid Flow

Cited by 12 publications

References 32 publications

Thermal apoptosis analysis considering injection behavior optimization and mass diffusion during magnetic hyperthermia

Thermal apoptosis analysis considering injection behavior optimization and mass diffusion during magnetic hyperthermia

Numerical investigation of temperature field in magnetic hyperthermia considering mass transfer and diffusion in interstitial tissue

Ferrofluid Impregnation Efficiency and Its Spatial Variability in Natural and Synthetic Porous Media: Implications for Magnetic Pore Fabric Studies

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