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A novel radiation imaging technology for in vivo molecular imaging in small mammals is described. The goal of this project is to develop a new type of imaging detector system suitable for real-time in vivo probe imaging studies in small animals. This technology takes advantage of the gamma-ray and x-ray emission properties of the radioisotope iodine 125 (125I) which is employed as the label for molecular probes. The radioisotope 125I is a gamma-ray emitting radioisotope that can be commercially obtained already attached to biomedically interesting molecules to be used as tracers for biomedical and molecular biology research.;The isotope 125I decays via electron capture consequently emitting a 35 keV gamma-ray followed by the near coincident emission of several 27--32 keV Kalpha and Kbeta shell x-rays. Because of these phenomena, a coincidence condition can be set to detect 125I thus enabling the reduction of any background radiation that could contaminate the image. The detector system is based on an array of CsI(Na) crystal scintillators coupled to a 125 mm diameter position sensitive photomultiplier tube. An additional standard 125 mm diameter photomultiplier tube coupled to a NaI(Tl) scintillator acts as the coincident detector. to achieve high resolution images the detector system utilizes a custom-built copper laminate high resolution collimator. The 125I detector system can achieve a spatial resolution of less than 2 mm FWHM for an object at a distance of 1.5 cm from the collimator. The measured total detector sensitivity while using the copper collimator was 68 cpm/muCi.;Results of in vivo mouse imaging studies of the biodistribution of iodine, melatonin, and a neurotransmitter analog (RTI-55) are presented. Many studies in molecular biology deal with following the expression and regulation of a gene at different stages of an organism's development or under different physiological conditions. This detector system makes it possible for laboratories without access to standard nuclear medicine radiopharmaceuticals to perform in vivo imaging research on small a mammals using a whole range of 125I labeled markers that are obtainable from commercial sources.

Periodontal disease is one of the two major causes of tooth loss today, and has been associated with several systemic diseases, such as diabetes, cardiovascular disease, stroke, and adverse pregnancy outcomes. Unfortunately, the most widely used diagnostic tool for assessment of periodontal diseases, measurement of periodontal attachment loss with a manual probe, may overestimate attachment loss by as much as 2mm in untreated sites, while underestimating attachment loss by an even greater margin following treatment. Manual probing is also invasive, which causes patient discomfort.;This work describes the development and testing of an ultrasonographic periodontal probe designed to replace manual probing. It uses a thin stream of water to project an ultrasonic beam into the periodontal pocket and then measures echoes off the periodontal ligament. Development issues addressed in this work included the proper design of the probe tip, which is needed to narrow the ultrasonic beam from a transducer with a 2mm diameter active area to a 0.5mm beam, which is the approximate width of the periodontal pocket at the gingival margin. The proper choice of transducer frequency, the proper method for controlling water flow from the probe, and the development of signal processing algorithms to aid in the interpretation of the echoes were also addressed. to test the ultrasonographic probe, clinical trials were conducted on 12 patients in conjunction with the Old Dominion University School of Dental Hygiene. These tests indicate that probing depth measurements obtained through the ultrasonographic probe do not correlate with manual probing depths, since ultrasonographic probing measures echoes off specific anatomical features, while manual probing measures resistance to probing force. However, ultrasonographic probing did show promise as a diagnostic tool, as ultrasonic probing depth measurements correlated to overall gingival health, as measured by the Gingival Index of Loe and Silness. In addition, ultrasonographic probing, when combined with an automated feature recognition algorithm, showed better repeatability than manual and controlled-force probing.

Three critical issues about medical image non-rigid registration are performance, robustness and accuracy. A registration method, which is capable of responding timely with an accurate alignment, robust against the variation of the image intensity and the missing data, is desirable for its clinical use. This work addresses all three of these issues. Unacceptable execution time of Non-rigid registration (NRR) often presents a major obstacle to its routine clinical use. We present a hybrid data partitioning method to parallelize a NRR method on a cooperative architecture, which enables us to get closer to the goal: accelerating using architecture rather than designing a parallel algorithm from scratch. to further accelerate the performance for the GPU part, a GPU optimization tool is provided to automatically optimize GPU execution configuration.;Missing data and variation of the intensity are two severe challenges for the robustness of the registration method. A novel point-based NRR method is presented to resolve mapping function (deformation field) with the point correspondence missing. The novelty of this method lies in incorporating a finite element biomechanical model into an Expectation and Maximization (EM) framework to resolve the correspondence and mapping function simultaneously. This method is extended to deal with the deformation induced by tumor resection, which imposes another challenge, i.e. incomplete intra-operative MRI. The registration is formulated as a three variable (Correspondence, Deformation Field, and Resection Region) functional minimization problem and resolved by a Nested Expectation and Maximization framework. The experimental results show the effectiveness of this method in correcting the deformation in the vicinity of the tumor. to deal with the variation of the intensity, two different methods are developed depending on the specific application. For the mono-modality registration on delayed enhanced cardiac MRI and cine MRI, a hybrid registration method is designed by unifying both intensity- and feature point-based metrics into one cost function. The experiment on the moving propagation of suspicious myocardial infarction shows effectiveness of this hybrid method. For the multi-modality registration on MRI and CT, a Mutual Information (MI)-based NRR is developed by modeling the underlying deformation as a Free-Form Deformation (FFD). MI is sensitive to the variation of the intensity due to equidistant bins. We overcome this disadvantage by designing a Top-to-Down K-means clustering method to naturally group similar intensities into one bin. The experiment shows this method can increase the accuracy of the MI-based registration.;In image registration, a finite element biomechanical model is usually employed to simulate the underlying movement of the soft tissue. We develop a multi-tissue mesh generation method to build a heterogeneous biomechanical model to realistically simulate the underlying movement of the brain. We focus on the following four critical mesh properties: tissue-dependent resolution, fidelity to tissue boundaries, smoothness of mesh surfaces, and element quality. Each mesh property can be controlled on a tissue level. The experiments on comparing the homogeneous model with the heterogeneous model demonstrate the effectiveness of the heterogeneous model in improving the registration accuracy.

Dual energy X-radiography is a method first developed in the mid-1970's by which one uses the information contained in the energy spectrum of the transmitted X-ray flux through an object. With this information one can distinguish the types of materials present in a radiograph and thus allow a computer to subtract them from the image enhancing the contrast of the remaining materials. Using this method, one can see details, which would have been hidden by overlying structures of other materials such as seen in radiographs of parts, made up of mixtures of metals and composites. There is also great interest in this technique for medical imaging of the chest where images of the organs are significantly improved by subtracting the bones. However, even with the enhanced capabilities realized with this technique, the majority of X-radiography systems only measures the bulk transmitted X-ray intensity and ignores the information contained in the energy spectrum. This is due to the added expense, time requirements, and registration problems incurred using standard radiographic methods to obtain dual energy radiographs. This dissertation describes a novel method which overcomes these problems and allows one to perform inexpensive, near real time, single shot dual energy X-radiography. The work of this thesis resulted in US patent #5,742,660.

In vivo small animal imaging has become an essential technique for molecular biology studies. However, requirements of spatial resolution, sensitivity and image quality are quite challenging for the development of small-animal imaging systems. The capabilities of the system are also significant for carrying out small animal imaging in a wide range of biological studies. The goal of this dissertation is to develop a high-performance imaging system that can readily meet a wide range of requirements for a variety of small animal imaging applications. Several achievements have been made in order to fulfill this goal.;To supplement our system for parallel-hole single photon emission computed tomography (SPECT) based upon a 110 mm diameter circular detector, we have developed novel compact gamma cameras suitable for imaging an entire mouse. These gamma cameras facilitate multi-head (>2) parallel-hole SPECT with the mouse in close proximity to the detector face in order to preserve spatial resolution. Each compact gamma cameras incorporates pixellated Nal(Tl) scintillators and a pair of Hamamatsu H8500 position sensitive photomultiplier tubes (PSPMTs). Two types of copper-beryllium parallel-hole collimators have been designed. These provide high-sensitivity imaging of I-125 or excellent spatial resolution over a range of object-detector distances. Both phantom and animal studies have demonstrated that these gamma cameras perform well for planar scintigraphy and parallel-hole SPECT of mice.;To further address the resolution limitations in parallel-hole SPECT and the sensitivity and limited field of view of single-pinhole SPECT, we have developed novel multipinhole helical SPECT based upon a 110 mm diameter circular detector equipped with a pixellated Nal(Tl) scintillator array. A brass collimator has been designed and produced containing five 1 mm diameter pinholes. Results obtained in SPECT studies of various phantoms show an enlarged field of view, very good resolution and improved sensitivity using this new imaging technique.;These studies in small-animal imaging have been applied to in vivo biological studies related to human health issues including studies of the thyroid and breast cancer. A re-evaluation study of potassium iodide blocking efficiency in radioiodine uptake in mice suggests that the FDA-recommended human dose of stable potassium iodide may not be sufficient to effectively protect the thyroid from radioiodine contamination. Another recent study has demonstrated that multipinhole helical SPECT can resolve the fine structure of the mouse thyroid using a relatively low dose (200 muCi). Another preclinical study has focused on breast tumor imaging using a compact gamma camera and an endogenous reporter gene. In that ongoing study, mammary tumors are imaged at different stages. Preliminary results indicate different functional patterns in the uptake of radiotracers and their potential relationship with other tumor parameters such as tumor size.;In summary, we have developed a versatile imaging system suitable for in vivo small animal research as evidenced by a variety of applications. The modular construction of this system will allow expansion and further development as new needs and new opportunities arise.

Theoretical calculations were performed for the propagation and interactions of particles having high atomic numbers and energy through diverse shield materials including polymeric materials and epoxy-bound lunar regolith by using transport codes for laboratory ion beams and the cosmic ray spectrum. Heavy ions fragment and lose energy upon interactions with shielding materials of specified elemental composition, density, and thickness. A fragmenting heavy iron ion produces hundreds of isotopes during nuclear reactions, which are treated in the solution of the transport problem used here. A reduced set of 80 isotopes is sufficient to represent the charge distribution, but a minimum of 122 isotopes is necessary for the mass distribution. These isotopes are adequate for ion beams with charges equal to or less than 26. to predict the single event upset (SEU) rate in electronic devices, the resultant linear energy transfer (LET) spectra from the transport code behind various materials are coupled with a measured SEU cross section versus LET curve. The SEU rate on static random access memory (SRAM) is shown as a function of shield thickness for various materials. For a given mass the most effective shields for SEU reduction are materials with high hydrogen density, such as polyethylene. The shield effectiveness for protection of biological systems is examined by using conventional quality factors to calculate the dose equivalents and also by using the probability of the neoplastic transformation of shielded C3H10T1/2 mouse cells. The attenuation of biological effects within the shield and body tissues depends on the materials properties. The results predict that hydrogenous materials are good candidates for high-performance shields. Two biological models were used. Quantitative results depended upon model.

Thesis (Ph.D.)--University of Florida, 2004. / Typescript. Title from title page of source document. Document formatted into pages; contains 139 pages. Includes Vita. Includes bibliographical references.

2’ -5’ –oligoadenylate synthetase 1 (OAS1) is an antiviral enzyme that in the presence of double-stranded RNA structures, such as viral genomes or single-stranded RNA transcripts with significant double-stranded character, converts ATP to a series of 2’ -5’ –oligoadenylates (2-5A). 2-5A promotes dimerization of latent ribonuclease (RNaseL) to form catalytically active RNaseL, a candidate hereditary prostate cancer (PCa) gene. RNaseL is anti-proliferative and promotes senescence and apoptosis in PCa cells. Genotyping analysis was completed on over 600 genomic DNA samples from African-American and Caucasian, normal and PCa subjects. Genotyping was performed to screen the following SNPs in the last exon of OAS1 (rs10774671, rs1131476, rs1051042 and rs2660) to determine splicing and linkage disequilibrium (LD) or LD decay in relation to PCa. The rs10774671 GG and AA genotypes generate isoform 1 (p46) and isoform 3 (p48), respectively and were distributed equally in the healthy population. However, in cases, the AA genotype (p46) was significantly associated with PCa risk (OR: 1.80, P-value: < 0.0001). The genotypic frequencies of rs1131476, rs1051042 and rs2660 demonstrated significant LD but showed no association to PCa risk. We also identified protective (AACA, OR =0.06612, P < 0.001) and risk (GACA, OR= 2.31, p Additionally, we utilized two genome-wide association studies analyzing OAS1 and variants found on chromosome 12 to determine their relationship with PCa susceptibility for meta-analysis: This was done to elucidate the role of OAS1 SNPs and chromosome 12 variants in a larger population cohort with PCa susceptibility for a greater understanding of gene to gene interactions. The genome wide association studies used were, the Geneva Multiethnic Genome-wide Scan of Prostate Cancer (MEC), containing 2,841 African-American samples (1,343 cases and 1,498 controls) and 1,660 Japanese/Latino samples (834 cases and 826 controls), as well as Cancer Genetic Markers of Susceptibility (CGEMS) Prostate Cancer-Primary Scan (Stage 1) - PLCO which contains 2,841 samples of European ancestry (1,172 cases and 1,157 controls). We used PLINK, a whole genome association analysis toolset, to extract data on SNPs in association with PCa.

ADVANCED IMAGING ANALYSIS FOR PREDICTING TUMOR RESPONSE AND IMPROVING CONTOUR DELINEATION UNCERTAINTY By Rebecca Nichole Mahon, MS A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at Virginia Commonwealth University. Virginia Commonwealth University, 2018 Major Director: Dr. Elisabeth Weiss, Professor, Department of Radiation Oncology Radiomics, an advanced form of imaging analysis, is a growing field of interest in medicine. Radiomics seeks to extract quantitative information from images through use of computer vision techniques to assist in improving treatment. Early prediction of treatment response is one way of improving overall patient care. This work seeks to explore the feasibility of building predictive models from radiomic texture features extracted from magnetic resonance (MR) and computed tomography (CT) images of lung cancer patients. First, repeatable primary tumor texture features from each imaging modality were identified to ensure a sufficient number of repeatable features existed for model development. Then a workflow was developed to build models to predict overall survival and local control using single modality and multi-modality radiomics features. The workflow was also applied to normal tissue contours as a control study. Multiple significant models were identified for the single modality MR- and CT-based models, while the multi-modality models were promising indicating exploration with a larger cohort is warranted. Another way advances in imaging analysis can be leveraged is in improving accuracy of contours. Unfortunately, the tumor can be close in appearance to normal tissue on medical images creating high uncertainty in the tumor boundary. As the entire defined target is treated, providing physicians with additional information when delineating the target volume can improve the accuracy of the contour and potentially reduce the amount of normal tissue incorporated into the contour. Convolution neural networks were developed and trained to identify the tumor interface with normal tissue and for one network to identify the tumor location. A mock tool was presented using the output of the network to provide the physician with the uncertainty in prediction of the interface type and the probability of the contour delineation uncertainty exceeding 5mm for the top three predictions.