Manu Mital

Thermal Detection of Embedded Tumors using Infrared Imaging

Breast cancer is the most common cancer among women. Thermography, also known as thermal or infrared imaging, is a procedure to determine if an abnormality is present in the breast tissue temperature distribution. This abnormality in temperature distribution might indicate the presence of an embedded tumor. Although thermography is currently used to indicate the presence of an abnormality, there are no standard procedures to interpret these and determine the location of an embedded tumor. This research is a first step towards this direction. It explores the relationship between the characteristics (location and power) of an embedded heat source and the resulting temperature distribution on the surface. Experiments were conducted using a resistance heater that was embedded in agar in order to simulate the heat produced by a tumor in the biological tissue. The resulting temperature distribution on the surface was imaged using an infrared camera. In order to estimate the location and heat generation rate of the source from these temperature distributions, a genetic algorithm was used as the estimation method. The genetic algorithm utilizes a finite difference scheme for the direct solution of the Pennes bioheat equation. It was determined that a genetic algorithm based approach is well suited for the estimation problem since both the depth and the heat generation rate of the heat source were accurately predicted.

Breast Tumor simulation and parameters estimation using evolutionary algorithms

An estimation methodology is presented to determine the breast tumor parameters using the surface temperature profile that may be obtained by infrared thermography. The estimation methodology involves evolutionary algorithms using artificial neural network (ANN) and genetic algorithm (GA). The ANN is used to map the relationship of tumor parameters (depth, size, and heat generation) to the temperature profile over the idealized breast model. The relationship obtained from ANN is compared to that obtained by finite element software. Results from ANN training/testing were in good agreement with those obtained from finite element model. After ANN validation, GA is used to estimate tumor parameters by minimizing a fitness function involving comparing the temperature profiles from simulated or clinical data to those obtained by ANN. Results show that it is possible to determine the depth, diameter, and heat generation rate from the surface temperature data (with 5% random noise) with good accuracy for the 2D model. With 10% noise, the accuracy of estimation deteriorates for deep-seated tumors with low heat generation. In order to further develop this methodology for use in a clinical scenario, several aspects such as 3D breast geometry and the effects of nonuniform cooling should be considered in future investigations.

A methodology for determining optimal thermal damage in magnetic nanoparticle hyperthermia cancer treatment

Hyperthermia treatment of tumors uses localized heating to damage cancer cells and can also be utilized to increase the efficacy of other treatment methods such as chemotherapy. Magnetic nanoparticle hyperthermia is one of the least invasive techniques of delivering heat. It is based on injecting magnetic nanoparticles into the tumor and subjecting them to an alternating magnetic field. The technique is aimed at damaging the tumor without affecting the surrounding healthy tissue. In this preliminary study, we consider a simplified model (two concentric spheres that represent the tumor and its surrounding tissues) that employs a numerical solution of the Pennes bioheat equation. The model assumes a Gaussian distribution for the spatial variation of the applied thermal energy and an exponential decay function for the time variation. The objective of the study is to optimize the parameters that control the spatial and the time variation of the thermal energy. The optimization process is performed by formulating a fitness function that rewards damage in the region representing the tumor but penalizes damage in the surrounding tissues. Because of the flatness of this fitness function near the optimum, a genetic algorithm is used as the optimization method for its robust non-gradient-based approach. The overall aim of this work is to propose a methodology that can be used for hyperthermia treatment in a clinical scenario.

Evaluation of Thermal Resistance Matrix Method for an Embedded Power Electronic Module

Thermal characterization provides data on the thermal performance of electronic components under given cooling conditions. The most common thermal characterization parameter used to characterize the behavior of electronic components is the thermal resistance. In this work, experiments are conducted to obtain thermal characterization data for different chips in a multichip package. Using this data, it is shown that the assumption of a linear temperature rise with input power is valid within the expected range of operation of the electronic module. Secondly, the applicability of a resistance matrix superposition methodology to the packaging structure of an integrated power electronic module is evaluated. The temperatures and the associated uncertainties involved in using the resistance matrix superposition method are compared to those obtained directly by powering all chips. It is shown that for any arbitrary power losses from the chips, the resistance matrix superposition method can predict the temperatures of a multichip package with reasonable accuracy for temperature rise up to 50degC.

Thermal Design Methodology for an Embedded Power Electronic Module Using Double-Sided Microchannel Cooling

This paper presents a thermal design methodology for an integrated power electronic module (IPEM) using embedded, single-phase, and laminar-flow rectangular microchannels. Three-dimensional packaging of electronic components in a small and compact volume makes thermal management more challenging, but IPEMs also offer the opportunity to extract heat from both the top and the bottom side of the module, enabling double-sided cooling. Although double-sided cooling of IPEMs can be implemented using traditional aluminum heat sinks, microchannels offer much higher heat transfer coefficients and a compact cooling approach that is compatible with the shrinking footprint of electronic packages. The overall goal of this work was to find the optimal microchannel configuration for the IPEM using double-sided cooling by evaluating the effect of channel placement, channel dimensions, and coolant flow rate. It was found that the high thermal conductivity copper of the direct bonded copper (DBC) layer is the most feasible location for the channels. Based on a new analytical heat transfer model developed for microchannels in IPEM structures, several design configurations were proposed in this study that employ the microchannels in the copper layers of the top and bottom DBCs. The designs included multiple parallel channels in copper as well as a single wide microchannel. The analytical model was verified using a finite element model, and the competing design configurations were compared against a commercial cooler. For a typical IPEM structure dissipating on the order of 100 W of heat, it was concluded that a single microchannel DBC heat sink is preferable to multiple parallel channels under a double-sided cooling configuration, considering thermal performance, pressure drop and fabrication trade-offs.

Evolutionary optimization of electronic circuitry cooling using nanofluid

Liquid cooling electronics using microchannels integrated in the chips is an attractive alternative to bulky aluminum heat sinks. Cooling can be further enhanced using nanofluids. The goals of this study are to evaluate heat transfer in a nanofluid heat sink with developing laminar flow forced convection, taking into account the pumping power penalty. The proposed model uses semiempirical correlations to calculate effective nanofluid thermophysical properties, which are then incorporated into heat transfer and friction factor correlations in literature for single-phase flows. The model predicts the thermal resistance and pumping power as a function of four design variables that include the channel diameter, velocity, number of channels, and nanoparticle fraction. The parameters are optimized with minimum thermal resistance as the objective function and fixed specified value of pumping power as the constraint. For a given value of pumping power, the benefit of nanoparticle addition is evaluated by independently optimizing the heat sink, first with nanofluid and then with water. Comparing the minimized thermal resistances revealed only a small benefit since nanoparticle addition increases the pumping power that can alternately be diverted towards an increased velocity in a pure water heat sink. The benefit further diminishes with increase in available pumping power.

Thermal Design and Optimization of a Microchannel Cooled Integrated Power Electronic Module

This paper presents thermal evaluations of an Insulated Gate Bipolar Transistor (IGBT) integrated power electronics module (IPEM) using embedded single-phase laminar-flow rectangular microchannels. IPEMs are multi-layered structures based on embedded power technology and offer the advantage of three-dimensional (3D) packaging of electronic components in a small and compact volume, replacing the traditional wire bonding technology. However, placing multiple heat generating chips in a small volume also makes thermal management more challenging. Microchannels offer an attractive cooling approach because of their compactness and high heat transfer rate. The overall goal here was to find the optimal channel cooling configuration in the IPEM by evaluating the effect of channel layout, channel dimensions and the coolant flow rate. Moreover, a double-sided cooling approach is proposed, where channels are embedded on both top and bottom layers of the IPEM. A commercially available finite element package was used to create a 3D geometric layout of the electronic module and perform thermal evaluations using forced liquid cooling with water as the coolant. A baseline finite element numerical model was validated using experiments. The results of these studies were designs for achieving best cooling performance of the IPEM.

Thermal Design and Optimization of an IGBT Power Electronic Module

This paper presents thermal design optimization of an insulated gate bipolar transistor (IGBT) integrated power electronic module (IPEM). A commercially available finite element package was used to create a 3D geometric layout of the IGBT module. Thermal simulations were performed under different forced air convection conditions, and for both single and double-sided cooling, to study the effects on the hot-spots and maximum temperature rise of the module. The design optimization for the module was performed by varying parameters (choice of materials and layer thicknesses) and studying their effect on the thermal performance of the module. The results of these studies were several improved designs for the module.Copyright

Thermal Detection of Embedded Tumors Using Infrared Imaging

Breast cancer is the most common cancer among women. Thermography, also known as thermal or infrared imaging, is a procedure to determine if an abnormality is present in the breast tissue temperature distribution. This abnormality in temperature distribution might indicate the presence of an embedded tumor. Although thermography is currently used to indicate the presence of an abnormality, there are no standard procedures to interpret these and determine the location of an embedded tumor. This research is a first step towards this direction. It explores the relationship between the characteristics (location and power) of an embedded heat source and the resulting temperature distribution on the surface. Experiments were conducted using a resistance heater that was embedded in agar in order to simulate the heat produced by a tumor in the biological tissue. The resulting temperature distribution on the surface was imaged using an infrared camera. In order to estimate the location and heat generation rate of the source from these temperature distributions, a genetic algorithm was used as the estimation method. The genetic algorithm utilizes a finite difference scheme for the direct solution of the Pennes bioheat equation. It was determined that a genetic algorithm based approach is well suited for the estimation problem since both the depth and the heat generation rate of the heat source were accurately predicted.