Magnetic Resonance Elastography (MRE) is a medical imaging technique used to generate a map of tissue elasticity. The resulting image is known as an elastogram, and gives a quantitative measure of stiffness in the examined tissue. The method is indirect; the elasticity, itself, is not measured. Instead, the physical response to a known stress is captured using magnetic resonance imaging, and is related to an elasticity parameter through a mathematical model of the tissue. In dynamic elastography, a harmonic stress is externally applied by a mechanical actuator, which is oriented to induce shear waves through the tissue. Once the system reaches a quasi-steady state, the displacement field is measured at a sequence of points in time. This data is the input to elasticity reconstruction algorithms. In this dissertation, the tissue is modelled as a linearly viscoelastic, isotropic continuum, undergoing harmonic motion with a known fundamental frequency. With this model, viscoelasticity is described by the complex versions of Lamé's first and second parameters. The second parameter, known as the complex shear modulus, is the one of interest. The term involving the first parameter is usually deemed negligible, so is ignored. The task is to invert the tissue model, a system of linear differential equations, to find the desired parameter. Direct inversion methods use the measured data directly in the model. Most current direct methods assume the shear modulus can be approximated locally by a constant, so ignore all derivative terms. This is known as the local homogeneity assumption, and allows for a simple, algebraic solution. The accuracy, however, is limited by the validity of the assumption. One of the purposes of MRE is to find pathological tissue marked by a higher than normal stiffness. At the boundaries of such diseased tissue, the stiffness is expected to change, invalidating the local homogeneity assumption, and hence, the shear modulus estimate. In order to capture the true shape of any stiff regions, a method must allow for local variations. Two new inversion methods are derived. In the first, a Green's function is introduced in an attempt to solve the differential equations. To simplify the system, the tissue is taken to be incompressible, another common assumption in direct inversion methods. Unfortunately, without designing an iterative procedure, the method still requires a homogeneity assumption, limiting potential accuracy. However, it is very fast and robust. In the second new inversion method, neither of the local homogeneity or incompressibility assumptions are made. Instead, the problem is re-posed in a quadratic optimization form. The system of linear differential equations is set as a constraint, and any free parameters are steered through quadratic programming techniques. It is found that, in most cases, there are no degrees of freedom in the optimization problem. This suggests that the system of differential equations has a fully determined solution, even without initial, boundary, or regularization conditions. The result is that estimates of the shear modulus and its derivatives can be obtained, locally, without requiring any assumptions that might invalidate the solution. The new inversion algorithms are compared to a few prominent, existing ones, testing accuracy and robustness. The Green's function method is found to have a comparable accuracy and noise performance to existing techniques. The second inversion method, employing quadratic optimization, is shown to be significantly more accurate, but not as robust. It seems the two goals of increasing accuracy and robustness are somewhat conflicting. One possible way to improve performance is to gather and use more data. If a second displacement field is generated using a different actuator location, further differential equations are obtained, resulting in a larger system. This enlarged system is better determined, and has improved signal-to-noise properties. It is shown that using data from a second field can increase accuracy for all methods.

This thesis details the development of ultra-short, single-walled carbon nanotubes (US-tubes) for use as nanocapsules to contain and deliver medical agents for both imaging (Gd3+ ) and therapeutic (211 At) purposes. In particular, Gd3+ -loaded US-tubes, known as gadonanotubes, operate as high-performance MRI contrast agents with relaxivities (image enhancement efficacy) a factor of 40-100 greater than current clinical contrast agents. Furthermore, gadonanotube relaxivities are highly pH-dependent, with image intensity nearly tripling from pH 7.5 to 6.8. Coupled with their high efficacies and targeting potential, these agents are promising candidates for next-generation targeted imaging probes for the early detection of cancer. Single gadonanotubes have also been encapsulated in a polymer shell for use as an intravenous MRI contrast agent. In addition, a new functionalization scheme has been developed to covalently attach a variety of amino acids in high quantity to the outer surface of the gadonanotubes and to attach a small peptide sequence for targeting breast cancer cells. The gadonanotubes have also been used as magnetic cell labeling agents, while also demonstrating efficacy in vivo as contrast agents. In addition to functioning as an imaging agent platform, the US-tubes have demonstrated efficacy as nanocapsules for radiotherapeutic agents. Astatine-211 (At-211), an α-emitting radionuclide, can be loaded inside the US-tube with excellent containment stability for the targeted delivery of an α-radiotherapeutic agent to micrometastatic and single-cell cancers. The loading levels for At-211 are comparable to, or better than, other known compounds. At-211, existing as the mixed-halogen compound 211 AtCl, is retained in the US-tube nanocapsules due to van der Waals forces between the 211AtCl and the interior sidewalls of the nanotube. Finally, the US-tubes have been shown to induce few health risks in mammalian experiments. Acute toxicity tests were conducted on mice with both raw and purified full-length carbon nanotubes (SWNTs), as well as US-tubes, using large doses (up to 1 g/kg of bodyweight). Even at these large doses, no animal death was recorded, although in a few cases behavioral changes were observed. Nanotubes were observed to be eliminated from the liver and kidneys through the urine and feces. It is believed that any toxicity at high doses can be attenuated (and prevented) by properly formulating the administered dose.

Positron Emission Tomography (PET) is a widely used imaging modality for diagnosing patients with cancer. Recently, there have been three novel developments in PET imaging aiming to increase PET image quality and quantification. This thesis focuses on the optimization of PET image quality on these three developments. The first development is the fully 3D PET data acquisition and reconstruction. 3D Acquisitions are not constrained in collecting events in single 2D planes and can span across different planes. 3D acquisition provides better detection since it can accept more events. Also it can result in lower radiation dose to the patient and shorter imaging times. With the application of 3D acquisition, a fully 3D iterative reconstruction algorithm was also developed. The aim of the first project in this thesis is to evaluate the PET image and raw data quality when this fully 3D iterative reconstruction algorithm is applied. The second development in PET imaging is the time-of-flight (TOF) PET data acquisition and reconstruction. TOF imaging has the ability to measure the difference between the detection times, thus localize the event location more accurately to increase the image quality. The second project in this thesis focuses on optimizing the TOF reconstruction parameters on a newly developed TOF PET scanner. Then the improvement of TOF information on image quality is assessed using the derived optimal parameters. Finally the effect of scan duration is evaluated to determine whether similar image quality could be obtained between TOF and non-TOF while using less scan time for TOF. The third development is the interest in building PET / magnetic resonance (MR) multi-modality scanner. MR imaging has the ability to show high soft tissue contrast and can assess physiological processes, which cannot be achieved on PET images. One problem in developing PET/MR system is that it is not possible with current MR acquisition schemes to translate the MR image into an attenuation map to correct for PET attenuations. The third project in this thesis proposed and assessed an approach for the attenuation correction of PET data in potential PET/MR systems to improve PET image quality and quantification.

MRI is a well known and widely spread technique to characterize cardiac pathologies due to its high spatial resolution, its accessibility and its adjustable contrast among soft tissues. In attempt to close the gap between blood flow, myocardial movement and the cardiac fucntion, researching in the MRI field addresses the quantification of some of the most relevant blood and myocardial parameters. During this proyect a new tool that allows reading, postprocessing, quantifying and visualizing 2D motion sense MR data has been developed. In order to analyze intracardiac blood flow and wall motion, the new tool quantifies velocity, turbulent kinetic energy, pressure and strain. In the results section the final tool is presented, describing the visualization modes, which represent the quantified parameters both individually and combined; and detailing auxiliary tool features as masking, thresholding, zooming, and cursors. Finally, thecnical aspects as the convenience of two dimensional examinations to create compact tools, and the challenges of masking as part of the relative pressure calculation, among others, are discussed; ending up with the proposal of some future developments.

Modern medicine has become reliant on medical imaging. Multiple modalities, e. g. magnetic resonance imaging (MRI), computed tomography (CT), etc. , are used to provide as much information about the patient as possible. The problem of geometrically aligning the resulting images is called image registration. Mutual information, an information theoretic similarity measure, allows for automated intermodal image registration algorithms. <br /><br /> In applications such as cancer therapy, diagnosticians are more concerned with the alignment of images over a region of interest such as a cancerous lesion, than over an entire image set. Attempts to register only the regions of interest, defined manually by diagnosticians, fail due to inaccurate mutual information estimation over the region of overlap of these small regions. <br /><br /> This thesis examines the region of union as an alternative to the region of overlap. We demonstrate that the region of union improves the accuracy and reliability of mutual information estimation over small regions. <br /><br /> We also present two new mutual information based similarity measures which allow for localized image registration by combining local and global image information. The new similarity measures are based on convex combinations of the information contained in the regions of interest and the information contained in the global images. <br /><br /> Preliminary results indicate that the proposed similarity measures are capable of localizing image registration. Experiments using medical images from computer tomography and positron emission tomography demonstrate the initial success of these measures. <br /><br /> Finally, in other applications, auto-detection of regions of interest may prove useful and would allow for fully automated localized image registration. We examine methods to automatically detect potential regions of interest based on local activity level and present some encouraging results.

Magnetic Resonance Elastography (MRE) is a medical imaging technique used to generate a map of tissue elasticity. The resulting image is known as an elastogram, and gives a quantitative measure of stiffness in the examined tissue. The method is indirect; the elasticity, itself, is not measured. Instead, the physical response to a known stress is captured using magnetic resonance imaging, and is related to an elasticity parameter through a mathematical model of the tissue. In dynamic elastography, a harmonic stress is externally applied by a mechanical actuator, which is oriented to induce shear waves through the tissue. Once the system reaches a quasi-steady state, the displacement field is measured at a sequence of points in time. This data is the input to elasticity reconstruction algorithms. In this dissertation, the tissue is modelled as a linearly viscoelastic, isotropic continuum, undergoing harmonic motion with a known fundamental frequency. With this model, viscoelasticity is described by the complex versions of Lamé's first and second parameters. The second parameter, known as the complex shear modulus, is the one of interest. The term involving the first parameter is usually deemed negligible, so is ignored. The task is to invert the tissue model, a system of linear differential equations, to find the desired parameter. Direct inversion methods use the measured data directly in the model. Most current direct methods assume the shear modulus can be approximated locally by a constant, so ignore all derivative terms. This is known as the local homogeneity assumption, and allows for a simple, algebraic solution. The accuracy, however, is limited by the validity of the assumption. One of the purposes of MRE is to find pathological tissue marked by a higher than normal stiffness. At the boundaries of such diseased tissue, the stiffness is expected to change, invalidating the local homogeneity assumption, and hence, the shear modulus estimate. In order to capture the true shape of any stiff regions, a method must allow for local variations. Two new inversion methods are derived. In the first, a Green's function is introduced in an attempt to solve the differential equations. To simplify the system, the tissue is taken to be incompressible, another common assumption in direct inversion methods. Unfortunately, without designing an iterative procedure, the method still requires a homogeneity assumption, limiting potential accuracy. However, it is very fast and robust. In the second new inversion method, neither of the local homogeneity or incompressibility assumptions are made. Instead, the problem is re-posed in a quadratic optimization form. The system of linear differential equations is set as a constraint, and any free parameters are steered through quadratic programming techniques. It is found that, in most cases, there are no degrees of freedom in the optimization problem. This suggests that the system of differential equations has a fully determined solution, even without initial, boundary, or regularization conditions. The result is that estimates of the shear modulus and its derivatives can be obtained, locally, without requiring any assumptions that might invalidate the solution. The new inversion algorithms are compared to a few prominent, existing ones, testing accuracy and robustness. The Green's function method is found to have a comparable accuracy and noise performance to existing techniques. The second inversion method, employing quadratic optimization, is shown to be significantly more accurate, but not as robust. It seems the two goals of increasing accuracy and robustness are somewhat conflicting. One possible way to improve performance is to gather and use more data. If a second displacement field is generated using a different actuator location, further differential equations are obtained, resulting in a larger system. This enlarged system is better determined, and has improved signal-to-noise properties. It is shown that using data from a second field can increase accuracy for all methods.

The goal of this work is to extend the state-of-the-art in digital medical X-ray imaging as it pertains to real-time, low-noise imaging and multi-mode imager functionality. One focus of this research in digital flat-panel imagers is to increase the detective quantum efficiency, particularly at low X-ray exposures, in order to enable low-noise imaging applications such as fluoroscopy or tomographic mammography. Another focus of this research is in the creation of a multi-mode imager, such as a combined radiographic and fluoroscopic (R&F) imager, which will reduce hospital costs, both in terms of equipment acquisition and storage space. To that end, we propose a novel three-transistor multi-mode digital flat-panel imager with a dynamic range capable for use in R&F applications, with a particular focus on noise optimization for low-noise real-time digital flat-panel X-ray fluoroscopy. This work involves the derivation and optimization of the total input referred noise of an active pixel sensor (APS) in terms of the on-pixel thin-film transistor device dimensions. It is determined that in order to minimize noise, all non-transistor capacitances at the pixel sense node needed to be minimized. This leads to a design where the on-pixel storage capacitance is eliminated; and instead the gate capacitance of the sense-node transistor is used to store the incoming X-ray converted charge. This work allows researchers to gain insight into the fundamental noise operation of active pixels used in medical imaging, and to appropriately choose device dimensions. Due to the inherent large feature sizes of thin-film transistors, active pixel flat-panel X-ray medical imagers offer lower resolution than their film-screen counterparts. By demonstrating the desirability of smaller device dimensions for reduced noise and the elimination of a storage capacitor, this research frees some of the area constraints that exist in active pixel flat-panel imagers, allowing for smaller pixels, and thus higher resolution medical imagers. The noise analysis and optimization as a function of pixel TFT device dimensions in this work is applicable to any amorphous silicon (a-Si) based charge-sensitive pixel, and is easily extended to other device technologies such as polysilicon (poly-Si). iv In addition, experimental results of a 64x64 pixel four-transistor APS imaging array fabricated in a-Si technology and mated with an a-Se photoconductor for use in medical X-ray imaging is presented. MTF results and transient response in the presence of X-rays (image lag) for the APS array are poor, which is ascribed to high charge trapping at the silicon nitride/a-Se interface. Improvements to the silicon nitride passivation layer and pixel layout are suggested to reduce this charge trapping. The prototype imager is compared directly with a state-of-the-art a-Si PPS imaging array and demonstrates good SNR performance for X-ray exposures down to 1.5μR. Pixel design and fabrication process improvements are suggested for low-exposure APS testing and improved low-noise performance.

<p>This thesis research builds upon prior work that developed separate SPECT and CT (computed mammotomography, or breast CT) devices that were independently capable of imaging an uncompressed breast in 3D space. To further develop the system as a clinically viable device, it was necessary to integrate the separate imaging systems onto a single gantry, and to simultaneously design a patient-friendly bed that could routinely and effectively position the patient during dual-modality imaging of her uncompressed breast in the system's common field of view. This thesis describes this process and also investigates practical challenges associated with dedicated breast imaging of a prone patient using the integrated SPECT-CT device.</p> <p>We initially characterized the practicability of implementing the novel x-ray beam ultra-thick K-edge filtration scheme designed for routine use with the breast CT system. Extensive computer simulations and physical measurements were performed to characterize the x-ray beam produced using K-edge filtration with cerium and to compare it to beams produced using other filtration methods and materials. The advantages of using this heavily filtered x-ray beam for uncompressed breast CT imaging were then further evaluated by measuring the dose absorbed by an uncompressed cadaver breast during the course of a routine tomographic scan. It was found that the breast CT device is indeed capable of imaging uncompressed breasts at dose levels below that of the maximum utilized for dual-view screening mammography.</p> <p>To prepare the separate SPECT and CT systems for integration onto a single platform, the cross contamination of the image of one modality by primary and scattered photons of the complementary modality was quantified. It was found that contamination levels of the emission (SPECT) image by the x-ray transmission source were generally far less than 2% when using photopeak energy windows up to ±8%. In addition, while there was some quantifiable evidence of a variation in the transmission image in response to the presence of <super>99m</super>Tc photons in the patient, the effect of primary and scattered <super>99m</super>Tc photons on the visibility of 5 mm acrylic photons in a low contrast x-ray transmission environment was negligible. </p> <p>A novel, tiered, stainless steel patient bed was then designed to allow dual-modality imaging using the integrated SPECT-CT system. The performance of the hybrid SPECT-CT system was evaluated during early stage dual-modality patient imaging trials with particular emphasis placed on the performance of the patient bed. The bed was successful in its primary task of enabling dual-modality imaging of a patient's breast in the common field of view, but practical challenges to more effective patient imaging were identified as well as some novel solutions to these challenges.</p> <p>In the final section of the thesis research, the feasibility of using two of these solutions was investigated with a view to imaging more of the patient's posterior breast volume. Limited angle tomographic trajectories and trajectories that involve raising or lowering the patient bed in mid tomographic acquisition were initially investigated using various geometric phantoms. A very low contrast imaging task was then tested using an observer study to quantify the effect of these trajectories on the ability of observers to maintain visibility of small geometric objects. </p> <p>This initial integrated SPECT-CT imaging system has demonstrated its ability to successfully perform low dose, dual-modality imaging of the uncompressed breast. Challenges and solutions have been identified here that will make future SPECT-CT designs even more powerful and a clinically relevant technique for molecular imaging of the breast.</p> / Dissertation

<p>This dissertation aims to demonstrate the feasibility of direct infarct visualization using 3D medical ultrasound. The dissertation proceeds by providing the first ever demonstration of fully-sampled 3D ultrasonic speckle tracking using raw B-Mode data of the heart. The initial demonstration uses a Cramer-Rao lower bound limited displacement estimator. The dissertation then proceeds to develop an implementable method for biased time-delay estimation. Biased time-delay estimation is shown to surpass the traditional limits described by the Cramer-Rao lower bound in a mean square error sense. Additional characterization of this new class of estimator is performed to demonstrate that with easily obtainable levels of prior information it is possible to estimate displacements that do surpass the Cramer-Rao lower bound. Finally, using 2D and 3D realizations of biased displacement estimation (Bayesian speckle tracking) the passive strain induced in the ventricle walls during atrial systole is shown to be sufficient to distinguish healthy and chronically infarcted myocardium.</p> / Dissertation

Breast cancer is the most crucial cancer type among all other cancer types. There are many imaging techniques used to screen breast carcinoma. These are mammography, ultrasound, computed tomography, magnetic resonance imaging, infrared imaging, positron emission tomography and electrical impedance tomography. However, there is no gold standard in breast carcinoma diagnosis. The object of this study is to create a hybrid system that uses thermal and electrical imaging methods together for breast cancer diagnosis. Body tissues have different electrical conductivity values depending on their state of health and types. Consequently, one can get information about the anatomy of the human body and tissue&rsquo / s health by imaging tissue conductivity distribution. Due to metabolic heat generation values and thermal characteristics that differ from tissue to tissue, thermal imaging has started to play an important role in medical diagnosis. To increase the temperature contrast in thermal images, the characteristics of the two imaging modalities can be combined. This is achieved by implementing thermal imaging applying electrical currents from the body surface within safety limits (i.e., thermal imaging in active mode). Electrical conductivity of tissues changes with frequency, so it is possible to obtain more than one thermal image for the same body. Combining these images, more detailed information about the tumor tissue can be acquired. This may increase the accuracy in diagnosis while tumor can be detected at deeper locations. Feasibility of the proposed technique is investigated with analytical and numerical simulations and experimental studies. 2-D and 3-D numerical models of the female breast are developed and feasibility work is implemented in the frequency range of 10 kHz and 800 MHz. Temporal and spatial temperature distributions are obtained at desired depths. Thermal body-phantoms are developed to simulate the healthy breast and tumor tissues in experimental studies. Thermograms of these phantoms are obtained using two different infrared cameras (microbolometer uncooled and cooled Quantum Well Infrared Photodetectors). Single and dual tumor tissues are determined using the ratio of uniform (healthy) and inhomogeneous (tumor) images. Single tumor (1 cm away from boundary) causes 55 &deg / mC temperature increase and dual tumor (2 cm away from boundary) leads to 50 &deg / mC temperature contrast. With multi-frequency current application (in the range of 10 kHz-800 MHz), the temperature contrast generated by 3.4 mm3 tumor at 9 mm depth can be detected with the state-of-the-art thermal imagers.