Data-driven Stochastic Model for Quantifying the Interplay Between Amyloid-beta and Calcium Levels in Alzheimer's Disease.

The abnormal aggregation of extracellular amyloid-ß(Aß) in senile plaques resulting in calcium Ca+2 dyshomeostasis is one of the primary symptoms of Alzheimer's disease (AD). Significant research efforts have been devoted in the past to better understand the underlying molecular mechanisms driving Aß deposition and Ca+2 dysregulation. Importantly, synaptic impairments, neuronal loss, and cognitive failure in AD patients are all related to the buildup of intraneuronal Aß accumulation. Moreover, increasing evidence show a feed-forward loop between Aß and Ca+2 levels, i.e. Aß disrupts neuronal Ca+2 levels, which in turn affects the formation of Aß. To better understand this interaction, we report a novel stochastic model where we analyze the positive feedback loop between Aß and Ca+2 using ADNI data. A good therapeutic treatment plan for AD requires precise predictions. Stochastic models offer an appropriate framework for modelling AD since AD studies are observational in nature and involve regular patient visits. The etiology of AD may be described as a multi-state disease process using the approximate Bayesian computation method. So, utilizing ADNI data from 2-year visits for AD patients, we employ this method to investigate the interplay between Aß and Ca+2 levels at various disease development phases. Incorporating the ADNI data in our physics-based Bayesian model, we discovered that a sufficiently large disruption in either Aß metabolism or intracellular Ca+2 homeostasis causes the relative growth rate in both Ca+2 and Aß, which corresponds to the development of AD. The imbalance of Ca+2 ions causes Aß disorders by directly or indirectly affecting a variety of cellular and subcellular processes, and the altered homeostasis may worsen the abnormalities of Ca+2 ion transportation and deposition. This suggests that altering the Ca+2 balance or the balance between Aß and Ca+2 by chelating them may be able to reduce disorders associated with AD and open up new research possibilities for AD therapy.

Non-Fourier Bioheat Transfer Analysis in Brain Tissue During Interstitial Laser Ablation: Analysis of Multiple Influential Factors.

This work presents the dual-phase lag-based non-Fourier bioheat transfer model of brain tissue subjected to interstitial laser ablation. The finite element method has been utilized to predict the brain tissue's temperature distributions and ablation volumes. A sensitivity analysis has been conducted to quantify the effect of variations in the input laser power, treatment time, laser fiber diameter, laser wavelength, and non-Fourier phase lags. Notably, in this work, the temperature-dependent thermal properties of brain tissue have been considered. The developed model has been validated by comparing the temperature obtained from the numerical and ex vivo brain tissue during interstitial laser ablation. The ex vivo brain model has been further extended to in vivo settings by incorporating the blood perfusion effects. The results of the systematic analysis highlight the importance of considering temperature-dependent thermal properties of the brain tissue, non-Fourier behavior, and microvascular perfusion effects in the computational models for accurate predictions of the treatment outcomes during interstitial laser ablation, thereby minimizing the damage to surrounding healthy tissue. The developed model and parametric analysis reported in this study would assist in a more accurate and precise prediction of the temperature distribution, thus allowing to optimize the thermal dosage during laser therapy in the brain.

Numerical Modeling and Simulation of Non-Invasive Acupuncture Therapy Utilizing Near-Infrared Light-Emitting Diode.

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.

The Impact of Intermittent Fasting on Patients With Suspected Gastroesophageal Reflux Disease.

GOAL: The aim was to investigate the short-term impact of time restricted feeding on patients with suspected gastroesophageal reflux disease (GERD). BACKGROUND: Lifestyle modifications are often suggested, but the role of diet in GERD is unclear. Intermittent fasting is popular in the media and has demonstrated potential benefits with weight loss and inflammatory conditions as well as alterations in gastrointestinal hormones. STUDY: Patients who were referred for 96-hour ambulatory wireless pH monitoring off proton pump inhibitor to investigate GERD symptoms were screened for eligibility. Patients were instructed to maintain their baseline diet for the first 2 days of pH monitoring and switch to an intermittent fasting regimen (16 consecutive hour fast and 8 h eating window) for the second 2 days. Objective measures of reflux and GERD symptom severity were collected and analyzed. RESULTS: A total of 25 participants were analyzed. 9/25 (36%) fully adhered to the intermittent fasting regimen, with 21/25 (84%) demonstrating at least partial compliance. Mean acid exposure time on fasting days was 3.5% versus 4.3% on nonfasting days. Intermittent fasting was associated with a 0.64 reduction in acid exposure time (95% CI: -2.32, 1.05). There was a reduction in GERD symptom scores of heartburn and regurgitation during periods of intermittent fasting (14.3 vs. 9.9; difference of -4.46, 95% CI: -7.6,-1.32). CONCLUSIONS: Initial adherence to time restricted eating may be difficult for patients. There is weak statistical evidence to suggest that intermittent fasting mildly reduces acid exposure. Our data show that short-term intermittent fasting improves symptoms of both regurgitation and heartburn.

Immune checkpoint inhibitor-mediated colitis is associated with cancer overall survival.

BACKGROUND: Immune checkpoint inhibitor-mediated colitis (IMC) is a common adverse event following immune checkpoint inhibitor (ICI) therapy for cancer. IMC has been associated with improved overall survival (OS) and progression-free survival (PFS), but data are limited to a single site and predominantly for melanoma patients. AIM: To determine the association of IMC with OS and PFS and identify clinical predictors of IMC. METHODS: We performed a retrospective case-control study including 64 ICI users who developed IMC matched according to age, sex, ICI class, and malignancy to a cohort of ICI users without IMC, from May 2011 to May 2020. Using univariate and multivariate logistic regression, we determined association of presence of IMC on OS, PFS, and clinical predictors of IMC. Kaplan-Meier curves were generated to compare OS and PFS between ICI users with and without IMC. RESULTS: IMC was significantly associated with a higher OS (mean 24.3 mo vs 17.7 mo, P = 0.05) but not PFS (mean 13.7 mo vs 11.9 mo, P = 0.524). IMC was significantly associated with OS greater than 12 mo [Odds ratio (OR) 2.81, 95% confidence interval (CI) 1.17-6.77]. Vitamin D supplementation was significantly associated with increased risk of IMC (OR 2.48, 95%CI 1.01-6.07). CONCLUSION: IMC was significantly associated with OS greater than 12 mo. In contrast to prior work, we found that vitamin D use may be a risk factor for IMC.

Coupled Multiphysics Modelling of Sensors for Chemical, Biomedical, and Environmental Applications with Focus on Smart Materials and Low-Dimensional Nanostructures.

Low-dimensional nanostructures have many advantages when used in sensors compared to the traditional bulk materials, in particular in their sensitivity and specificity. In such nanostructures, the motion of carriers can be confined from one, two, or all three spatial dimensions, leading to their unique properties. New advancements in nanosensors, based on low-dimensional nanostructures, permit their functioning at scales comparable with biological processes and natural systems, allowing their efficient functionalization with chemical and biological molecules. In this article, we provide details of such sensors, focusing on their several important classes, as well as the issues of their designs based on mathematical and computational models covering a range of scales. Such multiscale models require state-of-the-art techniques for their solutions, and we provide an overview of the associated numerical methodologies and approaches in this context. We emphasize the importance of accounting for coupling between different physical fields such as thermal, electromechanical, and magnetic, as well as of additional nonlinear and nonlocal effects which can be salient features of new applications and sensor designs. Our special attention is given to nanowires and nanotubes which are well suited for nanosensor designs and applications, being able to carry a double functionality, as transducers and the media to transmit the signal. One of the key properties of these nanostructures is an enhancement in sensitivity resulting from their high surface-to-volume ratio, which leads to their geometry-dependant properties. This dependency requires careful consideration at the modelling stage, and we provide further details on this issue. Another important class of sensors analyzed here is pertinent to sensor and actuator technologies based on smart materials. The modelling of such materials in their dynamics-enabled applications represents a significant challenge as we have to deal with strongly nonlinear coupled problems, accounting for dynamic interactions between different physical fields and microstructure evolution. Among other classes, important in novel sensor applications, we have given our special attention to heterostructures and nucleic acid based nanostructures. In terms of the application areas, we have focused on chemical and biomedical fields, as well as on green energy and environmentally-friendly technologies where the efficient designs and opportune deployments of sensors are both urgent and compelling.

CFD based analysis of 3D printed nasopharyngeal swabs for COVID-19 diagnostics.

BACKGROUND AND OBJECTIVE: Additive manufacturing of nasopharyngeal (NP) swabs using 3D printing technology presents a viable alternative to address the immediate shortage problem of standard flock-headed swabs for rapid COVID-19 testing. Recently, several geometrical designs have been proposed for 3D printed NP swabs and their clinical trials are already underway. During clinical testing of the NP swabs, one of the key criteria to compare the efficacy of 3D printed swabs with traditional swabs is the collection efficiency. In this study, we report a numerical framework to investigate the collection efficiency of swabs utilizing the computational fluid dynamics (CFD) approach. METHODS: Three-dimensional computational domain comprising of NP swab dipped in the liquid has been considered in this study to mimic the dip test procedure. The volume of fluid (VOF) method has been employed to track the liquid-air interface as the NP swab is pulled out of the liquid. The governing equations of the multiphase model have been solved utilizing finite-volume-based ANSYS Fluent software by imposing appropriate boundary conditions. Taguchi's based design of experiment analysis has also been conducted to evaluate the influence of geometric design parameters on the collection efficiency of NP swabs. The developed model has been validated by comparing the numerically predicted collection efficiency of different 3D printed NP swabs with the experimental findings. RESULTS: Numerical predictions of the CFD model are in good agreement with the experimental results. It has been found that there prevails huge variability in the collection efficiency of the 3D printed designs of NP swabs available in the literature, ranging from 2 µl to 120 µl. Furthermore, even the smallest alteration in the geometric design parameter of the 3D printed NP swab results in significant changes in the amount of fluid captured. CONCLUSIONS: The proposed framework would assist in quantifying the collection efficiency of the 3D printed designs of NP swabs, rapidly and at a low cost. Moreover, we demonstrate that the developed framework can be extended to optimize the designs of 3D printed swabs to drastically improve the performances of the existing designs and achieve comparable efficacy to that of conventionally manufactured swabs.

Auxeticity in biosystems: an exemplification of its effects on the mechanobiology of heterogeneous living cells.

Auxeticity (negative Poisson's ratio) is the unique mechanical property found in an extensive variety of materials, such as metals, graphene, composites, polymers, foams, fibers, ceramics, zeolites, silicates and biological tissues. The enhanced mechanical features of the auxetic materials have motivated scientists to design, engineer and manufacture man-made auxetic materials to fully leverage their capabilities in different fields of research applications, including aeronautics, medical, protective equipments, smart sensors, filter cleaning, and so on. Atomic force microscopy (AFM) indentation is one of the most widely used methods for characterizing the mechanical properties and response of the living cells. In this contribution, we highlight main consequences of auxeticity for biosystems and provide a representative example to quantify the effect of nucleus auxeticity on the force response of the embryonic stem cells. A parametric study has been conducted on a heterogeneous stem cell to evaluate the effect of nucleus diameter, nucleus elasticity, indenter's shape and location on the force-indentation curve. The developed model has also been validated with the recently reported experimental studies available in the literature. Our results suggest that the nucleus auxeticity plays a profound role in cell mechanics especially for large size nucleus. We also report the mechanical stresses induced within the hyperelastic cell model under different loading conditions that would be quite useful in decoding the interrelations between mechanical stimuli and cellular behavior of auxetic biosystems. Finally, current and potential areas of applications of our findings for regenerative therapies, tissue engineering, 3 D/4D bioprinting, and the development of meta-biomaterials are discussed.

A Neuron-Glial Model of Exosomal Release in the Onset and Progression of Alzheimer's Disease.

Exosomes are nano-sized extracellular vesicles that perform a variety of biological functions linked to the pathogenesis of various neurodegenerative disorders. In Alzheimer's disease (AD), for examples, exosomes are responsible for the release of Aß oligomers, and their extracellular accumulation, although the underpinning molecular machinery remains elusive. We propose a novel model for Alzheimer's Aß accumulation based on Ca 2+-dependent exosome release from astrocytes. Moreover, we exploit our model to assess how temperature dependence of exosome release could interact with Aß neurotoxicity. We predict that voltage-gated Ca 2+ channels (VGCCs) along with the transient-receptor potential M8 (TRPM8) channel are crucial molecular components in Alzheimer's progression.

Biological cells and coupled electro-mechanical effects: The role of organelles, microtubules, and nonlocal contributions.

Biological cells are exposed to a variety of mechanical loads throughout their life cycles that eventually play an important role in a wide range of cellular processes. The understanding of cell mechanics under the application of external stimuli is important for capturing the nuances of physiological and pathological events. Such critical knowledge will play an increasingly vital role in modern medical therapies such as tissue engineering and regenerative medicine, as well as in the development of new remedial treatments. At present, it is well known that the biological molecules exhibit piezoelectric properties that are of great interest for medical applications ranging from sensing to surgery. In the current study, a coupled electro-mechanical model of a biological cell has been developed to better understand the complex behaviour of biological cells subjected to piezoelectric and flexoelectric properties of their constituent organelles under the application of external forces. Importantly, a more accurate modelling paradigm has been presented to capture the nonlocal flexoelectric effect in addition to the linear piezoelectric effect based on the finite element method. Major cellular organelles considered in the developed computational model of the biological cell are the nucleus, mitochondria, microtubules, cell membrane and cytoplasm. The effects of variations in the applied forces on the intrinsic piezoelectric and flexoelectric contributions to the electro-elastic response have been systematically investigated along with accounting for the variation in the coupling coefficients. In addition, the effect of mechanical degradation of the cytoskeleton on the electro-elastic response has also been quantified. The present studies suggest that flexoelectricity could be a dominant electro-elastic coupling phenomenon, exhibiting electric fields that are four orders of magnitude higher than those generated by piezoelectric effects alone. Further, the output of the coupled electro-mechanical model is significantly dependent on the variation of flexoelectric coefficients. We have found that the mechanical degradation of the cytoskeleton results in the enhancement of both the piezo and flexoelectric responses associated with electro-mechanical coupling. In general, our study provides a framework for more accurate quantification of the mechanical/electrical transduction within the biological cells that can be critical for capturing the complex mechanisms at cellular length scales.

Domain Heterogeneity in Radiofrequency Therapies for Pain Relief: A Computational Study with Coupled Models.

The objective of the current research work is to study the differences between the predicted ablation volume in homogeneous and heterogeneous models of typical radiofrequency (RF) procedures for pain relief. A three-dimensional computational domain comprising of the realistic anatomy of the target tissue was considered in the present study. A comparative analysis was conducted for three different scenarios: (a) a completely homogeneous domain comprising of only muscle tissue, (b) a heterogeneous domain comprising of nerve and muscle tissues, and (c) a heterogeneous domain comprising of bone, nerve and muscle tissues. Finite-element-based simulations were performed to compute the temperature and electrical field distribution during conventional RF procedures for treating pain, and exemplified here for the continuous case. The predicted results reveal that the consideration of heterogeneity within the computational domain results in distorted electric field distribution and leads to a significant reduction in the attained ablation volume during the continuous RF application for pain relief. The findings of this study could provide first-hand quantitative information to clinical practitioners about the impact of such heterogeneities on the efficacy of RF procedures, thereby assisting them in developing standardized optimal protocols for different cases of interest.

Thermal ablation of biological tissues in disease treatment: A review of computational models and future directions.

Percutaneous thermal ablation has proven to be an effective modality for treating both benign and malignant tumours in various tissues. Among these modalities, radiofrequency ablation (RFA) is the most promising and widely adopted approach that has been extensively studied in the past decades. Microwave ablation (MWA) is a newly emerging modality that is gaining rapid momentum due to its capability of inducing rapid heating and attaining larger ablation volumes, and its lesser susceptibility to the heat sink effects as compared to RFA. Although the goal of both these therapies is to attain cell death in the target tissue by virtue of heating above 50°C, their underlying mechanism of action and principles greatly differs. Computational modelling is a powerful tool for studying the effect of electromagnetic interactions within the biological tissues and predicting the treatment outcomes during thermal ablative therapies. Such a priori estimation can assist the clinical practitioners during treatment planning with the goal of attaining successful tumour destruction and preservation of the surrounding healthy tissue and critical structures. This review provides current state-of-the-art developments and associated challenges in the computational modelling of thermal ablative techniques, viz., RFA and MWA, as well as touch upon several promising avenues in the modelling of laser ablation, nanoparticles assisted magnetic hyperthermia and non-invasive RFA. The application of RFA in pain relief has been extensively reviewed from modelling point of view. Additionally, future directions have also been provided to improve these models for their successful translation and integration into the hospital work flow.

Atomistic to continuum model for studying mechanical properties of RNA nanotubes.

With rapid advancements in the emerging field of RNA nanotechnology, its current and potential applications, new important problems arise in our quest to better understand properties of RNA nanocomplexes. In this paper, our focus is on the modeling of RNA nanotubes which are important for many biological processes. These RNA complexes are also important for human beings, with their theurapeutical and biomedical applications discussed vigorously in the literature over the recent years. Here, we develop a continuum model of RNA nanotubes, originally obtained from self assembly of RNA building blocks in the molecular dynamics simulation. Based on the finite element method, we calculate the elastic properties of these nanostructures and provide a relationship between stress and strain induced in the RNA nanotube. We also analyze the variations in the displacement vector along the assembly axis for RNA nanotubes of different sizes. In particular, we show that oscillations in the amplitudes of strains and displacements significantly differ for such RNA nanotubes. These findings are discussed in the context of atomistic simulations and experimental results in this field.

Coupled thermo-electro-mechanical models for thermal ablation of biological tissues and heat relaxation time effects.

Thermal ablation is a widely applied electrosurgical process in medical treatment of soft biological tissues. Numerical modeling and simulations play an important role in prediction of temperature distribution and damage volume during the treatment planning stage of associated therapies. In this contribution we report a coupled thermo-electro-mechanical model, accounting for heat relaxation time, for more accurate and precise prediction of the temperature distribution, tissue deformation and damage volume during the thermal ablation of biological tissues. Finite element solutions are obtained for most widely used percutaneous thermal ablative techniques, viz., radiofrequency ablation (RFA) and microwave ablation (MWA). Importantly, both tissue expansion and shrinkage have been considered for modeling the tissue deformation in the coupled model of high temperature thermal ablation. The coupled model takes into account the non-Fourier effects, considering both single-phase-lag (SPL) and dual-phase-lag (DPL) models of bio-heat transfer. The temperature-dependent electrical and thermal parameters, damage-dependent blood perfusion rate and phase change effect accounting for tissue vaporization have been accounted for obtaining more clinically relevant model. The proposed model predictions are found to be in good agreement against the temperature distribution and damage volume reported by previous experimental studies. The numerical simulation results revealed that the non-Fourier effects cause a decrease in the predicted temperature distribution, tissue deformation and damage volume during the high temperature thermal ablative procedures. Furthermore, the effects of different magnitudes of phase lags of the heat flux and temperature gradient on the predicted treatment outcomes of the considered thermal ablative modalities are also quantified and discussed in detail.

Changes in alpha-foetoprotein and Gc-globulin in relation to outcomes in non-acetaminophen acute liver failure.

BACKGROUND: Changes in Gc-globulin (Gc) and in alpha-foetoprotein (AFP) have been shown to be related to outcome in patients with acute liver failure (ALF). Gc is a serum protein that complexes with intravascular actin released during cellular necrosis. AFP, also made by hepatocytes, is associated with hepatocellular growth and regeneration. Previously, low absolute levels or decreases over time in either AFP or Gc portended to be a poor outcome. METHODS: In a retrospective analysis of the double-blind trial of intravenous N-acetylcysteine (NAC) for ALF not because of acetaminophen, sera on days 1 and 3 or days 2 and 4 following admission were available to measure AFP in 70 patients and Gc in 66 patients. Mann-Whitney U tests were performed on the admission values, the absolute change and the fractional change of AFP and Gc to compare TFS (transplant-free survival) and non-TFS (death or transplantation). Logistic regression and receiver operating characteristic (ROC) analyses were performed to evaluate the markers in comparison and in addition to King's College Criteria (KCC). RESULTS: Transplant-free survival patients were characterized by increases in AFP, whereas non-TFS had significantly different (negative) absolute and fractional changes (P < .01). The addition of declining AFP levels to KCC improved the area under the curve in predicting non-TFS (AUC >70%). Gc globulin values did not differ between TFS and non-TFS in the 2-day intervals studied (P> .2). CONCLUSION: In this comparison of two prognostic markers in patients with non-acetaminophen-induced ALF, rising AFP but not rising Gc levels was associated with TFS. TRIAL REGISTRATION: ClinicalTrials.gov number NCT00004467.

Numerical study to establish relationship between coagulation volume and target tip temperature during temperature-controlled radiofrequency ablation.

The present study aims at proposing a relationship between the coagulation volume and the target tip temperature in different tissues (viz., liver, lung, kidney, and breast) during temperature-controlled radiofrequency ablation (RFA). A 20-min RFA has been modelled using commercially available monopolar multi-tine electrode subjected to different target tip temperatures that varied from 70°C to 100°C with an increment of 10°C. A closed-loop feedback proportional-integral-derivative (PID) controller has been employed within the finite element model to perform temperature-controlled RFA. The coagulation necrosis has been attained by solving the coupled electric field distribution, the Pennes bioheat and the first-order Arrhenius rate equations within the three-dimensional finite element model of different tissues. The computational study considers temperature-dependent electrical and thermal conductivities along with the non-linear piecewise model of blood perfusion. The comparison between coagulation volume obtained from the numerical and in vitro experimental studies has been done to evaluate the aptness of the numerical models. In the present study, a total of 20 numerical simulations have been performed along with 12 experiments on tissue-mimicking phantom gel using RFA device. The study revealed a strong dependence of the coagulation volume on the pre-set target tip temperature and ablation time during RFA application. Further, the effect of target tip temperature on the applied input voltage has been studied in different tissues. Based on the results attained from the numerical study, statistical correlations between the coagulation volume and treatment time have been developed at different target tip temperatures for each tissue.

Temperature-controlled radiofrequency ablation of different tissues using two-compartment models.

PURPOSE: This study aims to analyse the efficacy of temperature-controlled radiofrequency ablation (RFA) in different tissues. MATERIALS AND METHODS: A three-dimensional, 12 cm cubical model representing the healthy tissue has been studied in which spherical tumour of 2.5 cm has been embedded. Different body sites considered in the study are liver, kidney, lung and breast. The thermo-electric analysis has been performed to estimate the temperature distribution and ablation volume. A programmable temperature-controlled RFA has been employed by incorporating the closed-loop feedback PID controller. The model fidelity and integrity have been evaluated by comparing the numerical results with the experimental in vitro results obtained during RFA of polyacrylamide tissue-mimicking phantom gel. RESULTS: The results revealed that significant variations persist among the input voltage requirements and the temperature distributions within different tissues of interest. The highest ablation volume has been produced in hypovascular lungs whereas least ablation volume has been produced in kidney being a highly perfused tissue. The variation in optimal treatment time for complete necrosis of tumour along with quantification of damage to the surrounding healthy tissue has also been reported. CONCLUSIONS: The results show that the surrounding tissue environment significantly affects the ablation volume produced during RFA. The optimal treatment time for complete tumour ablation can play a critical role in minimising the damage to the surrounding healthy tissue and ensuring safe and risk free application of RFA. The obtained results emphasise the need for developing organ-specific clinical protocols and systems during RFA of tumour.

Thermal analysis of induced damage to the healthy cell during RFA of breast tumor.

Effective pre-clinical computational modeling strategies have been demonstrated in this article to enable risk free clinical application of radiofrequency ablation (RFA) of breast tumor. The present study (a) determines various optimal regulating parameters required for RFA of tumor and (b) introduces an essential clinical monitoring scheme to minimize the extent of damage to the healthy cell during RFA of tumor. The therapeutic capabilities offered by RFA of breast tumor, viz., the rise in local temperature and induced thermal damage have been predicted by integrating the bioheat transfer model, the electric field distribution model and the thermal damage model. The mathematical model has been validated with the experimental results available in the literature. The results revealed that, the effective damage of tumor volume sparing healthy tissue essentially depends on the voltage, the exposure time, the local heat distribution, the tumor stage and the electrode geometric configuration. It has been confirmed that, the assessment of damage front can accurately determine the extent of damage as compared to the thermal front. The study further evaluates the damaged healthy and tumor volumes due to RFA of different stages of breast cancer. The assessment of cell survival and damage fractions discloses the propensity of reappearance/healing of tumor cells after treatment.