OBJECTIVE: The effectiveness of current microwave ablation (MWA) therapies is limited. Administration of thermosensitive liposomes (TSLs) which release drugs in response to heat has presented a significant potential for enhancing the efficacy of thermal ablation treatment, and the benefits of targeted drug delivery. However, a complete knowledge of the mechanobiological processes underlying the drug release process, especially the intravascular drug release mechanism and its distribution in response to MWA needs to be improved. Multiscale computational-based modeling frameworks, integrating different biophysical phenomena, have recently emerged as promising tools to decipher the mechanobiological events in combo therapies. The present study aims to develop a novel multiscale computational model of TSLs delivery following MWA implantation.
METHODS: Due to the complex interplay between the heating procedure and the drug concentration maps, a computational model is developed to determine the intravascular release of doxorubicin from TSL, its transvascular transport into the interstitium, transport in the interstitium, and cell uptake. Computational models can estimate the interplays among liposome and drug properties, tumor perfusion, and heating regimen to examine the impact of essential parameters and to optimize a targeted drug delivery platform.
RESULTS: Results indicated that the synergy of TSLs with MWA allows more localized drug delivery with lower side effects. The drug release rate and tumor permeability play crucial roles in the efficacy of TSLs during MWA treatment. The computational model predicted an unencapsulated drug lime around the ablated zone, which can destroy more cancer cells compared to MWA alone by 40%. Administration of TSLs with a high release rate capacity can improve the percentage of killed cancer cells by 24%. Since the heating duration in MWA is less than 15 min, the presented combination therapy showed better performance for highly permeable tumors.
CONCLUSIONS: This study highlights the potential of the proposed computational framework to address complex and realistic scenarios in cancer treatment, which can serve as the future research foundation, including advancements in nanomedicine and optimizing the pair of TSL and MWA for both preclinical and clinical studies. The present model could be as a valuable tool for patient-specific calibration of essential parameters.

Magnetic hyperthermia regulates the therapeutic temperature within a specific range to damage malignant cells after exposing the magnetic nanoparticles inside tumor tissue to an alternating magnetic field. The therapeutic temperature of living tissues can be generally predicted using Pennes\' bio-heat equation after ignoring both the inhomogeneity of biological structure and the microstructural responses. Although various of the bio-heat transfer models proposed in literature fix these shortages, there is still a lack of a comprehensive report on investigating the discrepancy for different models when applied in the magnetic hyperthermia context. This study compares four different bio-heat equations in terms of the therapeutic temperature distribution and the heat-induced damage situation for a proposed geometric model, which is established based on computed tomography images of a tumor bearing mouse. The therapeutic temperature is also used as an index to evaluate the effect of two key relaxation times for the phase lag behavior on bio-heat transfer. Moreover, this work evaluates the effects of two blood perfusion rates on both the treatment temperature and the cumulative equivalent heating minutes at 43 °C. Numerical analysis results reveal that relaxation times for phase-lag behavior as well as the porosity for living tissues directly affect the therapeutic temperature variation and ultimately the thermal damage for the malignant tissue during magnetic hyperthermia. The dual-phase-lag equation can be converted into Pennes\' equation and simple-phase-lag equation when relaxation times meet specific conditions during the process of heat transfer. In addition, different blood perfusion rates can result in an amplitude discrepancy for treatment temperature, but this parameter does not change the characteristics of thermal propagation during therapy.

Delivery of chemotherapeutic medicines to solid tumors is critical for optimal therapeutic success and minimal adverse effects. We mathematically developed a delivery method using thermosensitive nanocarriers activated by light irradiation. To assess its efficacy and identify critical events and parameters affecting therapeutic response, we compared this method to bolus and continuous infusions of doxorubicin for both single and multiple administrations. A hybrid sprouting angiogenesis approach generates a semi-realistic microvascular network to evaluate therapeutic drug distribution and microvascular heterogeneity. A pharmacodynamics model evaluates treatment success based on tumor survival cell percentage. The study found that whereas bolus injection boosted extracellular drug concentration levels by 90%, continuous infusion improved therapeutic response due to improved bioavailability. Cancer cell death increases by 6% with several injections compared to single injections due to prolonged chemotherapeutic medication exposure. However, responsive nanocarriers supply more than 2.1 times more drug than traditional chemotherapy in extracellular space, suppressing tumor development longer. Also, controlled drug release decreases systemic side effects substantial through diminishing the concentration of free drug in the circulation. The primary finding of this work highlights the significance of high bioavailability in treatment response. The results indicate that responsive nanocarriers contribute to increased bioavailability, leading to improved therapeutic benefits. By including drug delivery features in a semi-realistic model, this numerical study sought to improve drug-bio interaction comprehension. The model provides a good framework for understanding preclinical and clinical targeted oncology study outcomes.

Acupuncture is one of the most extensively used complementary and alternative medicine therapies worldwide. In this study, we explore the use of near-infrared light-emitting diodes (LEDs) to provide acupuncture-like physical stimulus to the skin tissue, but in a completely non-invasive way. A computational modeling framework has been developed to investigate the light-tissue interaction within a three-dimensional multi-layer model of skin tissue. Finite element-based analysis has been conducted, to obtain the spatiotemporal temperature distribution within the skin tissue, by solving Pennes\' bioheat transfer equation, coupled with the Beer-Lambert law. The irradiation profile of the LED has been experimentally characterized and imposed in the numerical model. The experimental validation of the developed model has been conducted through comparing the numerical model predictions with those obtained experimentally on the agar phantom. The effects of the LED power, treatment duration, LED distance from the skin surface, and usage of multiple LEDs on the temperature distribution attained within the skin tissue have been systematically investigated, highlighting the safe operating power of the selected LEDs. The presented information about the spatiotemporal temperature distribution, and critical factors affecting it, would assist in better optimizing the desired thermal dosage, thereby enabling a safe and effective LED-based photothermal therapy.

Focused Ultrasound (FUS)-triggered nano-sized drug delivery, as a smart stimuli-responsive system for treating solid tumors, is computationally investigated to enhance localized delivery of drug and treatment efficacy. Integration of thermosensitive liposome (TSL), as a doxorubicin (DOX)-loaded nanocarrier, and FUS, provides a promising drug delivery system. A fully coupled partial differential system of equations, including the Helmholtz equation for FUS propagation, bio-heat transfer, interstitial fluid flow, drug transport in tissue and cellular spaces, and a pharmacodynamic model is first presented for this treatment approach. Equations are then solved by finite element methods to calculate intracellular drug concentration and treatment efficacy. The main objective of this study is to present a multi-physics and multi-scale model to simulate drug release, transport, and delivery to solid tumors, followed by an analysis of how FUS exposure time and drug release rate affect these processes. Our findings not only show the capability of model to replicate this therapeutic approach, but also confirm the benefits of this treatment with an improvement of drug aggregation in tumor and reduction of drug delivery in healthy tissue. For instance, the survival fraction of tumor cells after this treatment dropped to 62.4%, because of a large amount of delivered drugs to cancer cells. Next, a combination of three release rates (ultrafast, fast, and slow) and FUS exposure times (10, 30, and 60 min) was examined. Area under curve (AUC) results show that the combination of 30 min FUS exposure and rapid drug release leads to a practical and effective therapeutic response.

Comprehension of thermal behavior underlying the living biological tissues helps successful applications of current heat therapies. The present work is to explore the heat transport properties of irradiated tissue during tis thermal treatment, in which the local thermal non-equilibrium effect as well as temperature-dependent properties arose from complicated anatomical structure, is considered. Based on the generalized dual-phase lag (GDPL) model, a non-linear governing equation of tissue temperature with variable thermal physical properties is proposed. The effective procedure constructed on an explicit finite difference scheme is then developed to predict numerically the thermal response and thermal damage irradiated by a pulse laser as a therapeutic heat source. The parametric study on variable thermal physical parameters including the phase lag times, heat conductivity, specific heat capacity and blood perfusion rate has been performed to evaluate their influence on temperature distribution in time and space. On this basis, the thermal damage with different laser variables such as laser intensity and exposure time are further analyzed.

BACKGROUND: this study describes the development of a female finite element thermoregulatory model (FETM) METHOD: the female body model was developed from medical image datasets of a median U.S. female and was constructed to be anatomically correct. The body model preserves the geometric shapes of 13 organs and tissues, including skin, muscles, fat, bones, heart, lungs, brain, bladder, intestines, stomach, kidneys, liver, and eyes. Heat balance within the body is described by the bio-heat transfer equation. Heat exchange at the skin surface includes conduction, convection, radiation, and sweat evaporation. Vasodilation, vasoconstriction, sweating, and shivering are controlled by afferent and efferent signals to and from the skin and hypothalamus.
RESULTS: the model was validated with measured physiological data during exercise and rest in thermoneutral, hot, and cold conditions. Validations show the model predicted the core temperature (rectal and tympanic temperatures) and mean skin temperatures with acceptable accuracy (within 0.5 °C and 1.6 °C, respectively) CONCLUSION: this female FETM predicted high spatial resolution temperature distribution across the female body, which provides quantitative insights into human thermoregulatory responses in females to non-uniform and transient environmental exposure.

Our core body temperature is held around [Formula: see text]C by an effective internal thermoregulatory system. However, various clinical scenarios have a more favorable outcome under external temperature regulation. Therapeutic hypothermia, for example, was found beneficial for the outcome of resuscitated cardiac arrest patients due to its protection against cerebral ischemia. Nonetheless, practice shows that outcomes of targeted temperature management vary considerably in dependence on individual tissue damage levels and differences in therapeutic strategies and protocols. Here, we address these differences in detail by means of computational modeling. We develop a multi-segment and multi-node thermoregulatory model that takes into account details related to specific post-cardiac arrest-related conditions, such as thermal imbalances due to sedation and anesthesia, increased metabolic rates induced by inflammatory processes, and various external cooling techniques. In our simulations, we track the evolution of the body temperature in patients subjected to post-resuscitation care, with particular emphasis on temperature regulation via an esophageal heat transfer device, on the examination of the alternative gastric cooling with ice slurry, and on how anesthesia and the level of inflammatory response influence thermal behavior. Our research provides a better understanding of the heat transfer processes and therapies used in post-cardiac arrest patients.

OBJECTIVE: The thermal therapy is a minimally invasive technique used as an alternative approach to conventional cancer treatments. There is an increasing concern about the accuracy of the thermal simulation during the process of tumor ablation. This study is aimed at investigating the effect of finite speed of heat propagation in the biological lung tissue, experimentally and numerically.
METHODS: In the experimental study, a boundary heat flux is applied to the lung tissue specimens and the temperature variation is measured during a transient heat transfer procedure. In the numerical study, a code is developed based on the finite volume method to solve the classical bio-heat transfer, the Cattaneo and Vernotte, and the Dual-phase-lag (DPL) equations. The thermal response of tissue during the experiments is compared with the predictions of the three heat transfer models.
RESULTS: It is found that the trend of temperature variation by the DPL model resembles the experimental results. The experimental observation in parallel with the numerical results reveals that the accumulated thermal energy diffuses to the surrounding tissue with a slower rate in comparison with the conventional bio-heat transfer model. The DPL model is implemented to study the temperature elevation in the laser irradiation to lung tissue in the presence of gold nanoparticles (GNPs). It is concluded that the extent of the necrotic tumoral region and the area of the damaged healthy tissue are reduced, when the non-Fourier heat transfer is taken into account.
CONCLUSIONS: Results show that considering the phase lags is crucial in planning for an effective thermal treatment, in which the cancerous tissue is ablated and the surrounding tissues are preserved from irreversible thermal damage.

Acanthamoeba are widely distributed in the environment and are known to cause blinding keratitis and brain infections with greater than 90% mortality rate. Currently, polymerase chain reaction (PCR) is a highly sensitive and promising technique in Acanthamoeba detection. Remarkably, the rate of heating-cooling and convective heat transfer of the PCR tube is limited by low thermal conductivity of the reagents mixture. The addition of nanoparticles to the reaction has been an interesting approach that could augment the thermal conductivity of the mixture and subsequently enhance heat transfer through the PCR tube. Here, we have developed hexagonal boron nitride (hBN) nanoparticle-based PCR assay for the rapid detection of Acanthamoeba to amplify DNA from low amoeba cell density. As low as 1 × 10-4 wt % was determined as the optimum concentration of hBN nanoparticles, which increased Acanthamoeba DNA yield up to ~16%. Further, it was able to reduce PCR temperature that led to a ~2.0-fold increase in Acanthamoeba DNA yield at an improved PCR specificity at 46.2 °C low annealing temperature. hBN nanoparticles further reduced standard PCR step time by 10 min and cycles by eight; thus, enhancing Acanthamoeba detection rapidly. Enhancement of Acanthamoeba PCR DNA yield is possibly due to the high adsorption affinity of hBN nanoparticles to purine (Guanine-G) due to the higher thermal conductivity achieved in the PCR mixture due to the addition of hBN. Although further research is needed to demonstrate these findings in clinical application, we propose that the interfacial layers, Brownian motion, and percolation network contribute to the enhanced thermal conductivity effect.