Thermal ablation effects on rotors that characterize functional re-entry cardiac arrhythmia.

Thermal ablation is a well-established successful treatment for cardiac arrhythmia, but it still presents limitations that require further studies and developments. In the rotor-driven functional re-entry arrhythmia, tissue heterogeneity results on the generation of spiral/scroll waves and wave break dynamics that may cause dangerous sustainable fibrillation. The selection of the target region to perform thermal ablation to mitigate this type of arrhythmia is challenging, since it considerably affects the local electrophysiology dynamics. This work deals with the numerical simulation of the thermal ablation of a cardiac muscle tissue and its effects on the dynamics of rotor-driven functional re-entry arrhythmia. A non-homogeneous two-dimensional rectangular region is used in the present numerical analysis, where radiofrequency ablation is performed. The electrophysiology problem for the propagation of the action potential in the cardiac tissue is simulated with the Fenton-Karma model. Thermal damage caused to the tissue by the radiofrequency heating is modeled by the Arrhenius equation. The effects of size and position of a heterogeneous region in the original muscle tissue were first analyzed, in order to verify the possible existence of the functional re-entry arrhythmia during the time period considered in the simulations. For each case that exhibited re-entry arrhythmia, six different ablation procedures were analyzed, depending on the position of the radiofrequency electrode and heating time. The obtained results revealed the effects of different model parameters on the existence and possible mitigation of the functional re-entry arrhythmia.

Computational model of silica nanoparticle penetration into tumor spheroids: Effects of methoxy and carboxy PEG surface functionalization and hyperthermia.

Drug delivery to tumors suffers from poor solubility, specificity, diffusion through the tumor micro-environment and nonoptimal interactions with components of the extracellular matrix and cell surface receptors. Nanoparticles and drug-polymer complexes address many of these problems. However, large size exasperates the problem of slow diffusion through the tumor. Three-dimensional tumor spheroids are good models to evaluate approaches to mitigate these difficulties and aid in design strategies to improve the delivery of drugs to treat cancer effectively. Diffusion of drug carriers is highly dependent on cell uptake rate parameters (association/dissociation) and temperature. Hyperthermia increases molecular transport and is known to act synergistically with chemotherapy to improve treatment. This study presents a new inverse estimation approach based on Bayesian probability for estimating nanoparticle cell uptake rates from experiments. The parameters were combined with a finite element computational model of nanoparticle transport under hyperthermia conditions to explore its effect on tumor porosity, diffusion and particle binding (association and dissociation) at cell surfaces. Carboxy-PEG-silane (cPEGSi) nanoparticles showed higher cell uptake compared to methoxy-PEG-silane (mPEGSi) nanoparticles. Simulations were consistent with experimental results from Skov-3 ovarian cancer spheroids. Amorphous silica (cPEGSi) nanoparticles (58 nm) concentrated at the periphery of the tumor spheroids at 37°C but mild hyperthermia (43°C) increased nanoparticle penetration. Thus, hyperthermia may enhance cancer treatment by improving blood delivery to tumors, enhancing extravasation and penetration into tumors, trigger release of drug from the carrier at the tumor site and possibly lead to synergistic anti-cancer activity with the drug.

Synthesis, characterization and photothermal analysis of nanostructured hydrides of Pd and PdCeO2.

Hyperthermia was shown to be an important co-adjuvant therapy to conventional cancer treatments. Nanoparticles can be used in the hyperthermia therapy to improve the localized absorption of energy imposed by external sources, in order to kill tumor cells solely by the effect of heat and with minimum thermal damage to surrounding healthy cells. Nanoparticles can also serve as carriers of drugs that specifically act on the tumor when heated, including hydrogen that can be desorbed to locally promote an antioxidant effect and reduce the viability of cancer cells. In this context, palladium hydride nanoparticles emerge as promising materials for the hyperthermia therapy. In this study, palladium nanocubes (PdNC) and PdCeO2 nanoparticles were synthesized. Nanofluids produced with these nanomaterials were hydrogenated and then tested to examine their photothermal effects. Nanofluids made of PdHx nanoparticles presented significant temperature increases of more than 30 °C under 3 min of diode-laser irradiation. On the other hand, nanofluids with PdCeO2H nanoparticles presented temperature increases around 11 °C under the same experimental conditions. The behavior observed with the PdCeO2H nanofluids can be attributed to the effect of H+ in reducing Ce+4 to Ce+3.

Thermal Characterization of Ex Vivo Tissue.

Cancer treatment strategies require mathematical modeling of different coupled phenomena as well as uncertainty quantification of resulting computational solutions. Due to variability in thermophysical tissue properties among individuals, and even for the same individual under different physiological conditions, uncertainties in such parameters must appropriately be taken into account for accurate planning and control of hyperthermia and thermal ablation. The objective of this work is to estimate thermophysical properties of ex vivo tissue, with bovine muscle used for experiments. The Markov chain Monte Carlo method and approximate Bayesian computation algorithm are used to find solutions of the inverse problems examined in this work. These techniques provide a framework for not only solving the inverse problem but also finding uncertainty quantification.

Temperature estimation of inflamed bowel by the photoacoustic inverse approach.

Local temperature increase is one of the five classical signs of regions with inflammations. This work is focused on the application of the photoacoustic technique for the estimation of the temperature field in the colon, as the solution of an inverse problem, for the detection of inflamed regions. Two-dimensional cases are examined here involving a cross section of the bowel, which characterize either the inflammation of the whole mucosa layer, or three small inflamed regions. The inverse problem is solved for a rotating laser inside the intestine lumen, which imposes pulses for the generation of the acoustic waves. One single ultrasound detector, also located at the laser rotating shaft, provides the simulated measurements for the inverse analysis. The inverse problem is solved here with the minimization of the maximum a posteriori objective function. Results show that the proposed technique can be applied for accurate estimations of the temperature distribution in the region of interest, which might be used for the diagnosis of inflammatory bowel diseases (IBD).

Estimation of the kidney metabolic heat generation rate.

Thermogenesis results from the cellular metabolism and has a fundamental role for body thermoregulation in endothermic species. The motivation for this work is the analysis of the kidneys' contribution for thermoregulation. An inverse problem is solved for the estimation of the heat generation rate that results from the metabolic activities in the kidney, by using transient temperature measurements of the urine. The Markov chain Monte Carlo (MCMC) method is applied for the solution of the inverse problem, which presents inherent difficulties associated with low sensitivity of the parameters of main interest that represent the transient heat source term and strong correlation of the remaining model parameters. Such difficulties are dealt with in this work by using a version of the Metropolis-Hastings algorithm that samples the parameters in blocks. Simulated temperature measurements are used for the inverse problem solution, and the convergence of the Markov chains is verified with two different techniques.

Computational fluid dynamic analysis of physical forces playing a role in brain organoid cultures in two different multiplex platforms.

BACKGROUND: Organoid cultivation in suspension culture requires agitation at low shear stress to allow for nutrient diffusion, which preserves tissue structure. Multiplex systems for organoid cultivation have been proposed, but whether they meet similar shear stress parameters as the regularly used spinner flask and its correlation with the successful generation of brain organoids has not been determined. RESULTS: Here we used computational fluid dynamics (CFD) to simulate two multiplex culture conditions: steering plates on an orbital shaker and the use of a previously described bioreactor. The bioreactor had low speed and high shear stress regions that may affect cell aggregate growth, depending on volume, whereas the computed variables of the steering plates were closer to those of the spinning flask. CONCLUSION: Our protocol improves the initial steps of the standard brain organoid formation, and the produced organoids displayed regionalized brain structures, including retinal pigmented cells. Overall, we conclude that suspension culture on orbital steering plates is a cost-effective practical alternative to previously described platforms for the cultivation of brain organoids for research and multiplex testing.

Simultaneous Model Selection and Model Calibration for the Proliferation of Tumor and Normal Cells During In Vitro Chemotherapy Experiments.

In vitro experiments were conducted in this work to analyze the proliferation of tumor (DU-145) and normal (macrophage RAW 264.7) cells under the influence of a chemotherapeutic drug (doxorubicin). Approximate Bayesian Computation (ABC) was used to select among four competing models to represent the number of cells and to estimate the model parameters, based on the experimental data. For one case, the selected model was validated in a replicated experiment, through the solution of a state estimation problem with a particle filter algorithm, thus demonstrating the robustness of the ABC procedure used in this work.

Estimation of Tumor Size Evolution Using Particle Filters.

Cancer is characterized by the uncontrolled growth of cells with the ability of invading local organs and/or tissues and of spreading to other sites. Several kinds of mathematical models have been proposed in the literature, involving different levels of refinement, for the evolution of tumors and their interactions with chemotherapy drugs. In this article, we present the solution of a state estimation problem for tumor size evolution. A system of nonlinear ordinary differential equations is used as the state evolution model, which involves as state variables the numbers of tumor, normal and angiogenic cells, as well as the masses of the chemotherapy and anti-angiogenic drugs in the body. Measurements of the numbers of tumor and normal cells are considered available for the inverse analysis. Parameters appearing in the formulation of the state evolution model are treated as Gaussian random variables and their uncertainties are taken into account in the estimation of the state variables, by using an algorithm based on the auxiliary sampling importance resampling particle filter. Test cases are examined in the article dealing with a chemotherapy protocol for pancreatic cancer.

Measurement of thermophysical properties of ceramics by the flash method

The flash method, proposed by Parker, Butler, Jenkins and Abbott from the U.S. Navy Radiological Defense Laboratory in 1961, is the most popular method for measuring the thermal diffusivity of solids. In this method, the front surface of a small sample is subjected to a very short burst of radiant thermal energy. The resulting temperature rise on the opposite surface of the sample is measured and the thermal diffusivity is computed from the temperature rise versus time data. Also, the specific heat can be computed from the measured data, thus allowing for the calculation of the thermal conductivity. Several theoretical models are available for the flash method, which include adiabatic boundary conditions, heat losses, surface coating effects, among other aspects. In this paper, tests were made for the identification of thermo-physical properties of a Ceramic block. The Netzsch Nanoflash LFA 447/1 of LTTC/COPPE/UFRJ was used for the measurements.