Parametric optimization for tumour identification: bioheat equation using ANOVA and the Taguchi method

Three-dimensional numerical evaluation of skin surface thermal contrast by application of hypothermia at different depths and sizes of the breast tumor

BACKGROUND AND OBJECTIVE

Thermal procedures can provide improvements in the thermal contrast of thermographic images in an attempt to diagnose early cases of breast cancer. This work aims to analyze the thermal contrast of different stages and depths of breast tumors from hypothermia treatment using an active thermography analysis. The influence of variation in metabolic heat generation and adipose tissue composition on thermal contrasts is also analyzed.

METHODS

The proposed methodology was based on the solution of the Pennes equation for a three-dimensional model similar to the real anatomy of the breast by commercial software COMSOL Multiphysics. The thermal procedure consists of three steps: Stationary, hypothermia and thermal recovery. During hypothermia, the boundary condition of the external surface was replaced by a constant temperature of 0, 5, 10, and 15 ^∘C, simulating a gel pack, for cooling times of up to 20 min. In the thermal recovery, after the removal of the cooling, the breast was submitted again to the condition of natural convection on the external surface.

RESULTS

Thermal contrasts in superficial tumors, for all hypothermia resulted in improvements in thermographs. For smallest tumor, the use of high resolution and sensitive thermal imaging cameras to acquire this thermal change may be necessary. For tumor of diameter of 10 cm, cooling from 0 ^∘C can increase the thermal contrast by up to 136% compared to the passive thermography. Analyzes with deeper tumors showed very small temperature variations. Even so, the thermal contrast gain in cooling at 0 ^∘C for the tumor with a diameter of 1 cm reached 37% in relation to passive thermography.

CONCLUSIONS

Thus, this work contributes as an important tool in the analysis of the appropriate use of hypothermia for different cases in early stages of breast cancer, considering that long times are needed to obtain the best thermal contrast.

Optimizing growth conditions in vertical farming: enhancing lettuce and basil cultivation through the application of the Taguchi method

This paper reports on the findings of an experimental study that investigated the impact of various environmental factors on the growth of lettuce and basil plants in vertical farms. The study employed the Taguchi method, a statistical design of experiments approach, to efficiently identify the optimal growth conditions for these crops in a hyper-controlled environment. By reducing the time and cost of designing and running experiments, this method allowed for the simultaneous investigation of multiple environmental factors that affect plant growth. A total of 27 treatments were selected using the Taguchi approach, and the signal to noise ratio was calculated to predict the optimal levels of each environmental condition for maximizing basil and lettuce growth parameters. The results showed that most of the parameters, except for EC and relative humidity for certain growth parameters, were interrelated with each other. To validate the results, confirmation tests were conducted based on the predicted optimal parameters. The low error ratio between expected and predicted values (1-3%) confirmed the effectiveness of the Taguchi approach for determining the optimal environmental conditions for plant growth in vertical farms.

Adaptive fuzzy control of drug delivery in cancer treatment using combination of chemotherapy and antiangiogenic therapy

This paper introduces the adaptive fuzzy control scheme as a promising control technique for cancer treatment from a theoretical point of view. A mathematical model describing the dynamics of tumor growth under the drug interventions of chemotherapy and antiangiogenic therapy is considered. The model incorporates the effects of normal cells, cancer cells, and endothelial cells. Then, the control goals in cancer treatment are discussed and the desired trajectory for a typical patient is derived using the optimal control theory. Since the dynamic model of tumor growth is not accurate and also varies from patient to patient, an adaptive fuzzy controller is designed to make the outputs of the dynamic model track the desired trajectory. The proposed control system is model-independent and identifies the dynamic model of tumor growth over time. The performance of the designed controller is assessed by several numerical simulations. Finally, a hardware-in-the-loop simulation is conducted to validate the results.

Theoretical Analysis for Using Pulsed Heating Power in Magnetic Hyperthermia Therapy of Breast Cancer

In magnetic hyperthermia, magnetic nanoparticles (MNPs) are used to generate heat in an alternating magnetic field to destroy cancerous cells. This field can be continuous or pulsed. Although a large amount of research has been devoted to studying the efficiency and side effects of continuous fields, little attention has been paid to the use of pulsed fields. In this simulation study, Fourier's law and COMSOL software have been utilized to identify the heating power necessary for treating breast cancer under blood flow and metabolism to obtain the optimized condition among the pulsed powers for thermal ablation. The results showed that for small source diameters (not larger than 4 mm), pulsed powers with high duties were more effective than continuous power. Although by increasing the source domain the fraction of damage caused by continuous power reached the damage caused by the pulsed powers, it affected the healthy tissues more (at least two times greater) than the pulsed powers. Pulsed powers with high duty (0.8 and 0.9) showed the optimized condition and the results have been explained based on the Arrhenius equation. Utilizing the pulsed powers for breast cancer treatment can potentially be an efficient approach for treating breast tumors due to requiring lower heating power and minimizing side effects to the healthy tissues.

An improved analytical model for heat flow in cancerous tumours to avoid thermal injuries during hyperthermia

The present study highlights an analytical hybrid scheme consisted of a shift of variables and finite integral transform for analysing a local thermal non-equilibrium (LTNE) bioheat model. This model can have utilised to be a betterment of prediction of the temperature field in the localised hyperthermia therapy (LHT) for the treatment of cancer patients. As the hyperthermia treatment is only the application in living tissues, an appropriate initial condition for the therapeutic thermal response is proposed instead of a constant temperature taken in the previous studies based on the 1-D heat flow. The present analysis suggests the therapeutic exposure time of 7776.8s (2.16 h) with constant heat flux and the exposure time of 10969.9s (3.06 h) with a sinusoidal heat flux within the usual temperature range of the hyperthermia (in a combination of thermal ablation and medium temperature hyperthermia) to be more effective in the treatment protocol. The presented results show that fatal injuries (tissue trauma, thermal burn, etc.) of internal organs might be possible to avoid by the current therapeutic condition. Therefore, this study may nullify the adverse effect of the existing model with the constant heating and consequently, the repercussion of the several therapeutic variables is to estimate with the development of a thermal profile for the suitability of a therapeutic condition. On the other hand, the present study well matches with the published analysis in case of both the theoretical and experimental (live tissues of the pig due to unavailability of real-time data on the human body) studies and it found the maximum deviation of the thermal response as 2.26% and 2.66%, respectively.

Numerical Modeling and Parametric Optimization of Micromixer for Low Diffusivity Fluids

This paper deals with the design, analysis and optimization of micro-mixer for fluids having very low diffusivity (in the order of 10−12m2/s) to be used in Lab on Chip (LOC) for medical diagnosis. As flow is laminar and the cross-sectional area is in microscale, the viscous forces are strong causing the fluids to be transported in streamline with minimum diffusion. The main objective in designing a micro mixer is to achieve complete mixing with minimum channel length and pressure drop. In this work a passive micro mixer with two inlets and one outlet (Y shaped passive micro mixer) with obstacles in various shapes and sizes is modelled, to study the effect of mixing. After a CFD analysis, Analysis of variance (ANOVA) of 3Kdesign with 3 parameters as well as a 2Kdesign with 4 parameters was performed to study the effect of parameters on mixing index (mixing length) and pressure loss. There is a negative correlation between the response obtained for mixing length and pressure loss while varying the parameters. This makes it difficult to predict the optimum configuration. Taguchi method is used to obtain an optimum configuration to overcome this negative correlatiozn.

Developing an Optimum Protocol for Thermoluminescence Dosimetry with GR-200 Chips using Taguchi Method

Thermoluminescence dosimetry (TLD) is a powerful technique with wide applications in personal, environmental and clinical dosimetry. The optimum annealing, storage and reading protocols are very effective in accuracy of TLD response. The purpose of this study is to obtain an optimum protocol for GR-200; LiF: Mg, Cu, P, by optimizing the effective parameters, to increase the reliability of the TLD response using Taguchi method. Taguchi method has been used in this study for optimization of annealing, storage and reading protocols of the TLDs. A number of 108 GR-200 chips were divided into 27 groups, each containing four chips. The TLDs were exposed to three different doses, and stored, annealed and read out by different procedures as suggested by Taguchi Method. By comparing the signal-to-noise ratios the optimum dosimetry procedure was obtained. According to the results, the optimum values for annealing temperature (°C), Annealing Time (s), Annealing to Exposure time (d), Exposure to Readout time (d), Pre-heat Temperature (°C), Pre-heat Time (s), Heating Rate (°C/s), Maximum Temperature of Readout (°C), readout time (s) and Storage Temperature (°C) are 240, 90, 1, 2, 50, 0, 15, 240, 13 and -20, respectively. Using the optimum protocol, an efficient glow curve with low residual signals can be achieved. Using optimum protocol obtained by Taguchi method, the dosimetry can be effectively performed with great accuracy.

THERMAL IMAGING AS AN ADJUNCT TOOL FOR IDENTIFYING FETAL GROWTH – A PILOT STUDY

Monitoring the fetal growth and diagnosing any possible abnormality plays a vital role in ensuring the healthy growth of a fetus. Certain health issues like Hyperthermia, Premature Rupture of Membranes (PROM) and Intrauterine Growth Restriction (IUGR) has to be diagnosed early. A pilot study comprising of 27 pregnant and 2 non-pregnant subjects was conducted to check the effectiveness of Thermal imaging in predicting the fetal growth. The heat dissipated by the fetus to the maternal abdominal wall is acquired as a surface thermal distribution. These images were processed qualitatively and quantitatively for better understanding. There was a consistent higher thermal pattern for pregnant women. A more pronounced temperature pattern is notable in the umbilical region that correlates with gestation age. However, as thermal pattern varies with age, gestation period and BMI, it is advisable to track the same person and compare the images for better assessment. This pilot study justifies the need for more elaborate study in building a database for classification and interpretation of thermogram to detect fetal abnormality with reduced human interpretation.

Towards Building a Computer Aided Education System for Special Students Using Wearable Sensor Technologies

Human computer interaction is a growing field in terms of helping people in their daily life to improve their living. Especially, people with some disability may need an interface which is more appropriate and compatible with their needs. Our research is focused on similar kinds of problems, such as students with some mental disorder or mood disruption problems. To improve their learning process, an intelligent emotion recognition system is essential which has an ability to recognize the current emotional state of the brain. Nowadays, in special schools, instructors are commonly use some conventional methods for managing special students for educational purposes. In this paper, we proposed a novel computer aided method for instructors at special schools where they can teach special students with the support of our system using wearable technologies.

Parameter estimation of breast tumour using dynamic neural network from thermal pattern

This article presents a new approach for estimating the depth, size, and metabolic heat generation rate of a tumour. For this purpose, the surface temperature distribution of a breast thermal image and the dynamic neural network was used. The research consisted of two steps: forward and inverse. For the forward section, a finite element model was created. The Pennes bio-heat equation was solved to find surface and depth temperature distributions. Data from the analysis, then, were used to train the dynamic neural network model (DNN). Results from the DNN training/testing confirmed those of the finite element model. For the inverse section, the trained neural network was applied to estimate the depth temperature distribution (tumour position) from the surface temperature profile, extracted from the thermal image. Finally, tumour parameters were obtained from the depth temperature distribution. Experimental findings (20 patients) were promising in terms of the model's potential for retrieving tumour parameters.

Potentialities of steady-state and transient thermography in breast tumour depth detection: A numerical study

Breast thermography still has inherent limitations that prevent it from being fully accepted as a breast screening modality in medicine. The main challenges of breast thermography are to reduce false positive results and to increase the sensitivity of a thermogram. Further, it is still difficult to obtain information about tumour parameters such as metabolic heat, tumour depth and diameter from a thermogram. However, infrared technology and image processing have advanced significantly and recent clinical studies have shown increased sensitivity of thermography in cancer diagnosis. The aim of this paper is to study numerically the possibilities of extracting information about the tumour depth from steady state thermography and transient thermography after cold stress with no need to use any specific inversion technique. Both methods are based on the numerical solution of Pennes bioheat equation for a simple three-dimensional breast model. The effectiveness of two approaches used for depth detection from steady state thermography is assessed. The effect of breast density on the steady state thermal contrast has also been studied. The use of a cold stress test and the recording of transient contrasts during rewarming were found to be potentially suitable for tumour depth detection during the rewarming process. Sensitivity to parameters such as cold stress temperature and cooling time is investigated using the numerical model and simulation results reveal two prominent depth-related characteristic times which do not strongly depend on the temperature of the cold stress or on the cooling period.

IN SILICO MODELING OF TUMOR GROWTH

Tumor growth is strongly coupled with both residual stress generated during the growth process and also biochemical factors. Several models have already been proposed to capture tumor growth considering either diffusion of nutrients concentration or residual stresses inside a tumor. In this work, a new method was proposed to model the generated residual stress in a growing solid using the continuum framework. This method was coupled with energy metabolism to predict the behavior of a soft tissue tumor. Moreover, it was shown that the main reason of vascular collapse in the middle of a tumor or vascular reopening in the tumor core can be the residual stress, generated during the growth.

Evaluation of the diagnostic power of thermography in breast cancer using Bayesian network classifiers

Breast cancer is one of the leading causes of death among women worldwide. There are a number of techniques used for diagnosing this disease: mammography, ultrasound, and biopsy, among others. Each of these has well-known advantages and disadvantages. A relatively new method, based on the temperature a tumor may produce, has recently been explored: thermography. In this paper, we will evaluate the diagnostic power of thermography in breast cancer using Bayesian network classifiers. We will show how the information provided by the thermal image can be used in order to characterize patients suspected of having cancer. Our main contribution is the proposal of a score, based on the aforementioned information, that could help distinguish sick patients from healthy ones. Our main results suggest the potential of this technique in such a goal but also show its main limitations that have to be overcome to consider it as an effective diagnosis complementary tool.

INFLUENCE OF INFRARED RADIATION ON THE HUMAN SKIN TEMPERATURE — EXPERIMENTAL DATA AND MODELING

The temperature rise of the hand palm has been measured with infrared thermography under the influence of an external infrared radiation source. The temperature rises could be very well fitted to exponential function, so that the experimental data could be summarized with just two parameters: amplitude and time constant. A simple mathematical model has been set up to explain the experimentally observed phenomena. It was found that the blood perfusion is essential to explain the results. From our measurements, which is essentially a noninvasive technique, several parameters could be found, the numerical values of which, agree with data found in the literature.

Thermal analysis of cancerous breast model

Breast cancer is one of the most common and dangerous cancers. Subsurface breast cancer lesions generate more heat and have increased blood supply when compared to healthy tissue, and this temperature rise is mirrored in the skin surface temperature. The rise in temperature on the skin surface, caused by the cancerous lesion, can be measured noninvasively using infrared thermography, which can be used as a diagnostic tool to detect the presence of a lesion. However, its diagnostic ability is limited when image interpretation relies on qualitative principles. In this study, we present a quantitative thermal analysis of breast cancer using a 3D computational model of the breast. The COMSOL FEM software was used to carry out the analysis. The effect of various parameters (tumor size, location, metabolic heat generation and blood perfusion rate) on the surface temperature distribution (which can be measured with infrared thermography) has been analyzed. Key defining features of the surface temperature profile have been identified, which can be used to estimate the size and location of the tumor based on (measured) surface temperature data. In addition, we employed a dynamic cooling process, to analyze surface temperature distributions during cooling and thermal recovery as a function of time. In this study, the effect of the cooling temperature on the enhancement of the temperature differences between normal tissue and cancerous lesions is evaluated. This study demonstrates that a quantification of temperature distributions by computational modeling, combined with thermographic imaging and dynamic cooling can be an important tool in the early detection of breast cancer.

OCULAR TEMPERATURE DISTRIBUTION: A MATHEMATICAL PERSPECTIVE

Mathematical modeling has proven to be a viable alternative for investigating the temperature distribution inside the human eye. This is due to its ability to overcome the limitations infrared (IR) thermography; the leading method in ocular temperature measurement. A wide range of mathematical studies on the ocular temperature distribution during various conditions have been published in the literature. In this paper, we carry out an in-depth review of the various mathematical models of the eye that have been developed in the past. Various problems and the implications from the mathematical predictions of these studies are discussed. The future directions of studies in ocular temperature distribution are deliberated.

EARLY DETECTION AND VISUALIZATION OF BREAST TUMOR WITH THERMOGRAM AND NEURAL NETWORK

Although mammography is still the benchmark technique for breast cancer detection, many advantages of thermography make it a suitable adjunct tool for early detection. This paper describes the development of a computer-aided system for use together with thermography to assist in the detection and visualization/analysis of breast tumors. The system consists of a detection module for predicting the presence of tumors from thermograms, and a visualization module for generating the 3-D volumetric geometry of the suspected tumor inside the breast based on the 2-D thermogram. Detection is achieved through an artificial neural network taking the thermogram image as input, while the visualization is obtained by generating the 3-D model of the breast that produces a matching thermal image as the thermogram under a 3-D finite element analysis. A study with 200 subjects indicate that the detection sensitivity was good but the specificity was poor, but the reverse performance result was true for another back-propagation neural network which used physiological data instead of thermograms as input. This suggests that overall prediction capability can be improved by appropriate combination of the two results.

Prediction and parametric analysis of thermal profiles within heated human skin using the boundary element method

In this paper, an axisymmetric model of the human skin is developed to simulate the steady-state temperature distribution during contact with a hot solid. Simulations are carried out using the boundary element method. This study seeks to investigate the feasibility of using the boundary element method in the studies of burn. A sensitivity analysis is carried out to examine the effects of various parameters on the temperature distribution inside the skin during burn. Furthermore, a statistical analysis based on the Taguchi method is performed to determine the combination of factors that produce the desired outcome (least increase in temperature). In order to validate the accuracy of the numerical scheme, results obtained using the boundary element method are compared with the solutions obtained using the more established finite-element method.

Bioslurry phase remediation of chlorpyrifos contaminated soil: process evaluation and optimization by Taguchi design of experimental (DOE) methodology

Design of experimental (DOE) methodology using Taguchi orthogonal array (OA) was applied to evaluate the influence of eight biotic and abiotic factors (substrate-loading rate, slurry phase pH, slurry phase dissolved oxygen (DO), soil water ratio, temperature, soil microflora load, application of bioaugmentation and humic substance concentration) on the soil bound chlorpyrifos bioremediation in bioslurry phase reactor. The selected eight factors were considered at three levels (18 experiments) in the experimental design. Substrate-loading rate showed significant influence on the bioremediation process among the selected factors. Derived optimum operating conditions obtained by the methodology showed enhanced chlorpyrifos degradation from 1479.99 to 2458.33microg/g (over all 39.82% enhancement). The proposed method facilitated systematic mathematical approach to understand the complex bioremediation process and the optimization of near optimum design parameters, only with a few well-defined experimental sets.

Computer simulation in conjunction with medical thermography as an adjunct tool for early detection of breast cancer

BACKGROUND

Mathematical modelling and analysis is now accepted in the engineering design on par with experimental approaches. Computer simulations enable one to perform several 'what-if' analyses cost effectively. High speed computers and low cost of memory has helped in simulating large-scale models in a relatively shorter time frame. The possibility of extending numerical modelling in the area of breast cancer detection in conjunction with medical thermography is considered in this work.

METHODS

Thermography enables one to see the temperature pattern and look for abnormality. In a thermogram there is no radiation risk as it only captures the infrared radiation from the skin and is totally painless. But, a thermogram is only a test of physiology, whereas a mammogram is a test of anatomy. It is hoped that a thermogram along with numerical modelling will serve as an adjunct tool. Presently mammogram is the 'gold-standard' in breast cancer detection. But the interpretation of a mammogram is largely dependent on the radiologist. Therefore, a thermogram that looks into the physiological changes in combination with numerical simulation performing 'what-if' analysis could act as an adjunct tool to mammography.

RESULTS

The proposed framework suggested that it could reduce the occurrence of false-negative/positive cases.

CONCLUSION

A numerical bioheat model of a female breast is developed and simulated. The results are compared with experimental results. The possibility of this method as an early detection tool is discussed.

Fabrication optimisation of carbon fiber electrode with Taguchi method

In this study, we describe an optimised procedure for fabricating carbon fiber electrodes using Taguchi quality engineering method (TQEM). The preliminary results show a S/N ratio improvement from 22 to 30 db (decibel). The optimised parameter was tested by using a glass micropipette (0.3 mm outer/2.5 mm inner length of carbon fiber) dipped into PBS solution under 2.9 V triangle-wave electrochemical processing for 15 s, followed by coating treatment of micropipette on 2.6 V DC for 45 s in 5% Nafion solution. It is thus shown that Taguchi process optimisation can improve cost, manufacture time and quality of carbon fiber electrodes.

Prediction of skin burn injury. Part 2: Parametric and sensitivity analysis

Part 2 of this paper presents an analysis of variance (ANOVA) for investigating the precedence of the various parameters, and the effects of varying these parameters, in assessment of burn injury resulting from the exposure of skin surface to heat sources. A one-dimensional model based on the finite difference method (FDM), as implemented in a spreadsheet software application, is applied to the assessment of burn injury. Henriques' theory of skin burns is used for determining the spatial and temporal extent of tissue damage. The ranks of the effects of various factors were obtained. It was found that the highest ranked factor is the initial tissue temperature followed by the thermal conductivity of the epidermal layer. The effect of blood perfusion rate is ranked much below the combinations of other factors. The results from the present numerical experiment agree well with the results obtained by Palla. Sensitivity analysis of the critical exposure levels was also carried out and results are discussed. In this study, the effects of the various parameters on injury threshold were investigated. Again, the results indicate that the four parameters: thermal conductivity of the epidermis and dermis, convective heat transfer coefficient and initial tissue temperature, have a pronounced influence on assessing the burn injury threshold. It was also found that fat thermal conductivity and blood perfusion rate have no obvious effect on injury threshold. A two-dimensional analysis was further conducted to determine the sensitivity of the predicted injury to the values of frequency factor, P, and apparent activation energy, deltaE, used in the models. Part 1 of this study details the development of the computer models based on the one- and two-dimensional bioheat equations.

Effect of blood flow, tumour and cold stress in a female breast: a novel time-accurate computer simulation

Breast cancer is a dreadful disease among women and early detection helps in achieving a cure. The mammogram is presently the standard tool for detecting breast abnormality, but its sensitivity is lower for women with dense breasts. It has been found that women with an abnormal thermogram are at a higher risk and have a poorer prognosis. However, performing and interpreting thermograms requires meticulous training. Computer simulations can be an additional tool to help the clinician in the interpretation. In this paper, a novel and flexible finite element model of a female breast is developed. Both steady state and time-dependent solutions are obtained. Steady state solutions globally match experimental thermographic results with the proper choice of blood perfusion source terms, tissue thickness and geometric scaling factor. Although the simulations may not be useful in providing a unique solution (i.e. exact size and location of the tumour owing to the complex physiological relationship between the tumour and the breast surface temperature), it would nevertheless help in the 'analysis by elimination'. An example of this type of analysis is also presented.

An improved three-dimensional direct numerical modelling and thermal analysis of a female breast with tumour

It is well known that malignant tumour tissue generally has higher metabolic and blood perfusion rates than most normal tissues. The authors aim to show that the tissue temperature profile within the breast and the surface temperature profile can be quantified to develop an expert system or diagnostic tool for breast cancer detection. The surface temperature and tissue temperature profiles are analysed for a three-dimensional numerical model of a normal breast and a breast with a tumour. Tumours of different sizes are placed at various locations. In the model, the tissue temperature profile is distorted at the tumour location and was found to compare well with in vivo tests. It was also found that as the tumour was moved to deeper locations its effect on surface temperature was lower. It was observed that small tumours in deeper regions do not have a significant isolated impact on the surface. The numerical results could also capture a shift in the position of the tumour. For tumours greater than 10 mm in the superficial regions and of significant size in deeper regions, it could be seen that the surface temperature distribution of the breast is directly related to the position and size of the tumour embedded in it. The feasibility of providing a diagnostic tool in conjunction with numerical modelling and high-resolution thermograms is also discussed.