Exploring Novel Contrast Agents with Anthropomorphic Mesh Models in MCNP

Breast cancer is the leading cancer in women with an estimated 13% of women in the United States developing a form of invasive breast cancer in her lifetime. The survival rate is estimated to be 85%, but the American Cancer Society estimates that early detection of breast cancer in the localized stage increases the breast cancer survival rate to 99%. However, early detection is dependent on the sensitivity of breast imaging techniques and currently, the sensitivity is suboptimal for women with dense breasts and obscure cancers. Recently, studies have indicated that exploring new contrast agents can provide access to improved sensitivity because of their potential to increase the effective Z of the target tissue. Furthermore, contrast-enhanced tomosynthesis is a viable imaging method that can provide a 3D view of the breast while providing tumor enhancement for improved visibility. This project aims to facilitate the search for practical contrast agents that can improve sensitivity during breast imaging. More specifically, the objective of this project is to find novel ways to improve the differentiation between tumor and glandular tissue by creating a realistic anthropomorphic model that not only considers the geometry of the breast but its physiological components as well. This project aims to combine tomosynthesis breast imaging methods with novel contrast agents to explore their efficacy and limitations. To achieve the goals of this project, several techniques are employed. A realistic tomosynthesis environment is created by constructing a detailed Hologic tomosynthesis breast imaging machine, including the source, flat-panel detector, and support equipment, using MCNP. Realistic breast phantoms that consider geometric and biophysical accuracy are created by incorporating a time dependency into the model. Once the contrast agents are incorporated, their efficacy is calculated by quantifying tumor visibility as a function of breast size, density, tumor location, tumor stage, and tumor type. After running simulations, this project will generate clear and accurate radiographs demonstrating the structural components of the breast and the effects of contrast enhancement on any embedded tumors. The results will provide an indication of the contrast agents that provide promise. The data acquired in this project will provide insight on the process of creating an anthropomorphic breast phantom for tomosynthesis studies, as well as insight on setbacks that are identified with the methods used. Contrast-enhanced tomosynthesis is clinically possible and is a promising technique for improving sensitivity. This project explores this technique and provides insight on possible ways to improve breast imaging sensitivity

A dual modality, DCE-MRI and x-ray, physical phantom for quantitative evaluation of breast imaging protocols

The current clinical standard for breast cancer screening is mammography. However, this technique has a low sensitivity which results in missed cancers. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has recently emerged as a promising technique for breast cancer diagnosis and has been reported as being superior to mammography for screening of high-risk women and evaluation of extent of disease. At the same time, low and variable specificity has been documented in the literature as well as a rising number of mastectomies possibly due to the increasing use of DCE-MRI. In this study, we developed and characterized a dual-modality, x-ray and DCE-MRI, anthropomorphic breast phantom for the quantitative assessment of breast imaging protocols. X-ray properties of the phantom were quantitatively compared with patient data, including attenuation coefficients, which matched human values to within the measurement error, and tissue structure using spatial covariance matrices of image data, which were found to be similar in size to patient data. Simulations of the phantom scatter-to-primary ratio (SPR) were produced and experimentally validated then compared with published SPR predictions for homogeneous phantoms. SPR values were as high as 85% in some areas and were heavily influenced by the heterogeneous tissue structure. MRI properties of the phantom, T1 and T2 relaxation values and tissue structure, were also quantitatively compared with patient data and found to match within two error bars. Finally, a dynamic lesion that mimics lesion border shape and washout curve shape was included in the phantom. High spatial and temporal resolution x-ray measurements of the washout curve shape were performed to determine the true contrast agent concentration as a function of time. DCE-MRI phantom measurements using a clinical imaging protocol were compared against the x-ray truth measurements. MRI signal intensity curves were shown to be less specific to lesion type than the x-ray derived contrast agent concentration curves. This phantom allows, for the first time, for quantitative evaluation of and direct comparisons between x-ray and MRI breast imaging modalities in the context of lesion detection and characterization

Virtual clinical trials in medical imaging: a review

The accelerating complexity and variety of medical imaging devices and methods have outpaced the ability to evaluate and optimize their design and clinical use. This is a significant and increasing challenge for both scientific investigations and clinical applications. Evaluations would ideally be done using clinical imaging trials. These experiments, however, are often not practical due to ethical limitations, expense, time requirements, or lack of ground truth. Virtual clinical trials (VCTs) (also known as in silico imaging trials or virtual imaging trials) offer an alternative means to efficiently evaluate medical imaging technologies virtually. They do so by simulating the patients, imaging systems, and interpreters. The field of VCTs has been constantly advanced over the past decades in multiple areas. We summarize the major developments and current status of the field of VCTs in medical imaging. We review the core components of a VCT: computational phantoms, simulators of different imaging modalities, and interpretation models. We also highlight some of the applications of VCTs across various imaging modalities

Evaluation of a diffraction-enhanced imaging (DEI) prototype and exploration of novel applications for clinical implementation of DEI

Conventional mammographic image contrast is derived from x-ray absorption, resulting in breast structure visualization due to density gradients that attenuate radiation without distinction between transmitted, scattered, or refracted x-rays. Diffraction-enhanced imaging (DEI) allows for increased contrast with decreased radiation dose compared to conventional mammographic imaging due to monochromatic x-rays, its unique refraction-based contrast mechanism, and excellent scatter rejection. Although laboratory breast imaging studies have demonstrated excellent breast imaging, important clinical translation and application studies are needed before the DEI system can be established as a useful breast imaging modality. This dissertation focuses on several important studies toward the development of a clinical DEI system. First, contrast-enhanced DEI was explored using commercially available contrast agents. Phantoms were imaged at a range of x-ray energies and relevant contrast agent concentrations. Second, we performed a reader study to determine if superior DEI contrast mechanisms preserve image quality as tissue thickness increases. Breast specimens were imaged at several thicknesses, and radiologist perception of lesion visibility was recorded. Lastly, a prototype DEI system utilizing an x-ray tube source was evaluated through a reader study. Breast tissue specimens were imaged on the traditional and prototype DEI systems, and expert radiologists evaluated image quality and pathology correlation. This dissertation will demonstrate proof-of-principle for contrast-enhanced DEI, establishing the feasibility of contrast-enhanced DEI using commercially available contrast agents. Further, it will show that DEI might be able to reduce breast compression, and thus the perception of pain during mammography, without significantly decreasing breast lesion visibility. Finally, this research shows the successful implementation of a DEI prototype, displaying breast features with approximately statistically equivalent visibility to the traditional DEI system. Together, this research is an important step toward the clinical translation of DEI, a technology with the potential to facilitate early breast cancer detection and diagnosis

Imaging of the Breast

Early detection of breast cancer combined with targeted therapy offers the best outcome for breast cancer patients. This volume deal with a wide range of new technical innovations for improving breast cancer detection, diagnosis and therapy. There is a special focus on improvements in mammographic image quality, image analysis, magnetic resonance imaging of the breast and molecular imaging. A chapter on targeted therapy explores the option of less radical postoperative therapy for women with early, screen-detected breast cancers

Creating Anthropomorphic Models with Mesh Phantoms in MCNP to Simulate Mammography

Breast cancer is the most common cancer among women as it accounts for about 25% of all female cancer cases. Studies have shown that early detection of breast cancer increases the chances of a positive prognosis amongst patients therefore it is crucial to provide accurate diagnosis tools in routine exams. Experimenting with new techniques and tools that can provide increased accuracy requires time-consuming and costly studies, therefore, simulating outcomes that have high potential can provide guidance for increased accuracy without requiring expensive tests. This project outlines the possibility of developing an advanced anthropomorphic mesh phantom of the breast to experiment different contrast agents with. The phantom would contain all the components of a real breast and it would be able to simulate the physiological and metabolic components that play a role in the outcome of a real tomosynthesis-mammography scan. This project focuses on creating a basic model of a breast and a tomosynthesis system that provides an indication on whether a simulation system can be produced. The materials used for this project include Abaqus/CAE software, Python, MCNP6.2, and scripting tools as well as resources on tomosynthesis equipment. The results demonstrated a positive outcome thus indicating that the model can be further developed to incorporate the multiple components of a real breast scan to increase the simulation’s realism. Further work on this project will focus on increasing the model’s complexity and incorporating contrast agents so that the efficacy of each can be explored

Endorectal Digital Prostate Tomosynthesis

Several areas of prostate cancer (PCa) management, such as imaging permanent brachytherapy implants or small, aggressive lesions, benefit from high image resolution. Current PCa imaging methods can have inadequate resolution for imaging these areas. Endorectal digital prostate tomosynthesis (endoDPT), an imaging method that combines an external x-ray source and an endorectal x-ray sensor, can produce three-dimensional images of the prostate region that have high image resolution compared to typical methods. This high resolution may improve PCa management and increase positive outcomes in affected men. This dissertation presents the initial development of endoDPT, including system design, image quality assessment, and examples of possible applications to prostate imaging. Experiments using computational phantoms, physical phantoms, and canine prostate specimens were conducted. Initial system design was performed computationally and three methods of endoDPT image reconstruction were developed: shift and add (SAA), backprojection (BP), and filtered BP (FBP). A physical system was developed using an XDR intraoral x-ray sensor and a GE radiography unit. The resolution and radiation dose of endoDPT were measured and compared to a GE CT scanner. Canine prostate specimens that approximated clinical cases of PCa management were imaged and compared using endoDPT, the above CT scanner, and a GE MRI scanner. This study found that the resolution of endoDPT was significantly higher than CT. The radiation dose of endoDPT was significantly lower than CT in the regions of the phantom that were not in the endoDPT field of view (FoV). Inside the endoDPT FoV, the radiation dose ranged from significantly less than to significantly greater than CT. The endoDPT images of the canine prostate specimens demonstrated qualitative improvements in resolution compared to CT and MRI, but endoDPT had difficulty in visualizing larger structures, such as the prostate border. Overall, this study has demonstrated endoDPT has high image resolution compared to typical methods of PCa imaging. Future work will be focused on development of a prototype system that improves scanning efficiency that can be used to optimize endoDPT and perform pre-clinical studies

Numerical Approaches for Solving the Combined Reconstruction and Registration of Digital Breast Tomosynthesis

Heavy demands on the development of medical imaging modalities for breast cancer detection have been witnessed in the last three decades in an attempt to reduce the mortality associated with the disease. Recently, Digital Breast Tomosynthesis (DBT) shows its promising in the early diagnosis when lesions are small. In particular, it offers potential benefits over X-ray mammography - the current modality of choice for breast screening - of increased sensitivity and specificity for comparable X-ray dose, speed, and cost. An important feature of DBT is that it provides a pseudo-3D image of the breast. This is of particular relevance for heterogeneous dense breasts of young women, which can inhibit detection of cancer using conventional mammography. In the same way that it is difficult to see a bird from the edge of the forest, detecting cancer in a conventional 2D mammogram is a challenging task. Three-dimensional DBT, however, enables us to step through the forest, i.e., the breast, reducing the confounding effect of superimposed tissue and so (potentially) increasing the sensitivity and specificity of cancer detection. The workflow in which DBT would be used clinically, involves two key tasks: reconstruction, to generate a 3D image of the breast, and registration, to enable images from different visits to be compared as is routinely performed by radiologists working with conventional mammograms. Conventional approaches proposed in the literature separate these steps, solving each task independently. This can be effective if reconstructing using a complete set of data. However, for ill-posed limited-angle problems such as DBT, estimating the deformation is difficult because of the significant artefacts associated with DBT reconstructions, leading to severe inaccuracies in the registration. The aim of my work is to find and evaluate methods capable of allying these two tasks, which will enhance the performance of each process as a result. Consequently, I prove that the processes of reconstruction and registration of DBT are not independent but reciprocal. This thesis proposes innovative numerical approaches combining reconstruction of a pair of temporal DBT acquisitions with their registration iteratively and simultaneously. To evaluate the performance of my methods I use synthetic images, breast MRI, and DBT simulations with in-vivo breast compressions. I show that, compared to the conventional sequential method, jointly estimating image intensities and transformation parameters gives superior results with respect to both reconstruction fidelity and registration accuracy