Radiology Commons^™

Synthesis, Radiolabeling And Evaluation Of A Suite Of Tracers With 44Sc For Detecting Extracellular Dna, Zhiyao Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

Neutrophil extracellular traps involve the rapid translocation of DNA to the outside of the cell under certain stimuli. This structure forms a fibrous network that is able to limit the spread of pathogens and to kill microorganisms. It has also been shown to be present in various pathological processes such as inflammation, autoimmune diseases, and cancer metastasis. Currently, the formation process of NETs in vivo is being extensively studied. However noninvasive detection and quantitation has yet to be achieved. A class of PET tracers are described here that consists of a DNA dye as the backbone that is labeled with …

In Situ Microwave Fixation Provides An Instantaneous Snapshot Of The Brain Metabolome, Jelena A. Juras, Madison B. Webb, Lyndsay E. A. Young, Kia H. Markussen, Tara R. Hawkinson, Michael D. Buoncristiani, Kayli E. Bolton, Peyton T. Coburn, Meredith I. Williams, Lisa P. Y. Sun, William C. Sanders, Ronald C. Bruntz, Lindsey R. Conroy, Chi Wang, Matthew S. Gentry, Bret N. Smith, Ramon C. Sun

Markey Cancer Center Faculty Publications

Brain glucose metabolism is highly heterogeneous among brain regions and continues postmortem. In particular, we demonstrate exhaustion of glycogen and glucose and an increase in lactate production during conventional rapid brain resection and preservation by liquid nitrogen. In contrast, we show that these post- mortem changes are not observed with simultaneous animal sacrifice and in situ fixation with focused, high- power microwave. We further employ microwave fixation to define brain glucose metabolism in the mouse model of streptozotocin-induced type 1 diabetes. Using both total pool and isotope tracing analyses, we identified global glucose hypometabolism in multiple brain regions, evidenced by …

Effective Connectivity Of Functional Mri Via Deep Learning Methods, Kai-Cheng Chuang

LSU Doctoral Dissertations

Effective connectivity, based on functional magnetic resonance imaging (fMRI) time series signals, is the quantification of how strongly brain activity in a certain source brain region contributes to brain activity in a target brain region, independent of the contributions of other source regions. Current methods to solve this problem have several limitations. They are either unable to model nonlinear relationships between source and target signals, unable to efficiently quantify time lags in source-target relationships, unable to identify time-varying relationships, or fail to account for variability in the hemodynamic response function that converts neuron activity to a measurable signal. In this …

Prediction Of Rapid Early Progression And Survival Risk With Pre-Radiation Mri In Who Grade 4 Glioma Patients, Walia Farzana, Mustafa M. Basree, Norou Diawara, Zeina Shboul, Sagel Dubey, Marie M. Lockheart, Mohamed Hamza, Joshua D. Palmer, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Rapid early progression (REP) has been defined as increased nodular enhancement at the border of the resection cavity, the appearance of new lesions outside the resection cavity, or increased enhancement of the residual disease after surgery and before radiation. Patients with REP have worse survival compared to patients without REP (non-REP). Therefore, a reliable method for differentiating REP from non-REP is hypothesized to assist in personlized treatment planning. A potential approach is to use the radiomics and fractal texture features extracted from brain tumors to characterize morphological and physiological properties. We propose a random sampling-based ensemble classification model. The proposed …

Predictive Digital Twin For Optimizing Patient-Specific Radiotherapy Regimens Under Uncertainty In High-Grade Gliomas, Anirban Chaudhuri, Graham Pash, David A Hormuth, Guillermo Lorenzo, Michael Kapteyn, Chengyue Wu, Ernesto A B F Lima, Thomas E Yankeelov, Karen Willcox

Faculty, Staff and Student Publications

We develop a methodology to create data-driven predictive digital twins for optimal risk-aware clinical decision-making. We illustrate the methodology as an enabler for an anticipatory personalized treatment that accounts for uncertainties in the underlying tumor biology in high-grade gliomas, where heterogeneity in the response to standard-of-care (SOC) radiotherapy contributes to sub-optimal patient outcomes. The digital twin is initialized through prior distributions derived from population-level clinical data in the literature for a mechanistic model's parameters. Then the digital twin is personalized using Bayesian model calibration for assimilating patient-specific magnetic resonance imaging data. The calibrated digital twin is used to propose optimal …

Alignment And Range Verification In Proton Therapy Using Proton Radiography And Proton Ct, Joseph Piet

Graduate Research Theses & Dissertations

Protons are used in radiation therapy to lower doses to healthy tissues by utilizing their Bragg peak. Protons can be used both in imaging and treatment. One of the uses of protons in imaging we tested is its use to align patients using a single beam's eye proton radiograph (pRad). By using a beam's eye pRad, and comparing the water equivalent thickness (WET) to proton digitally reconstructed radiographs (pDRRs), we show that we can measure the best alignment on six axes, three translational and three rotational. This is done by defining a cost function, chi squared, which quantifies the misalignment …

Comparison Of Physics-Based Deformable Registration Methods For Image-Guided Neurosurgery, Nikos Chrisochoides, Yixun Liu, Fotis Drakopoulos, Andriy Kot, Panos Foteinos, Christos Tsolakis, Emmanuel Billias, Olivier Clatz, Nicholas Ayache, Andrey Fedorov, Alex Golby, Peter Black, Ron Kikinis

Computer Science Faculty Publications

This paper compares three finite element-based methods used in a physics-based non-rigid registration approach and reports on the progress made over the last 15 years. Large brain shifts caused by brain tumor removal affect registration accuracy by creating point and element outliers. A combination of approximation- and geometry-based point and element outlier rejection improves the rigid registration error by 2.5 mm and meets the real-time constraints (4 min). In addition, the paper raises several questions and presents two open problems for the robust estimation and improvement of registration error in the presence of outliers due to sparse, noisy, and incomplete …

Lens: A Novel Image Processing-Based Approach For Low-Cost Segmentation Of Computed Tomography Scans Of Lungs, Monica Hinga

Computer Science ETDs

A staggering amount of data has been collected and analyzed since the beginning of the COVID-19 pandemic. Some of that data, however, particularly computed tomography (CT) scans of lungs, are difficult to analyze computationally. Segmentation of COVID-19 lesions provides researchers with insights into where lesions form, their volume, and in the case of time course data, how lesions grow as disease progresses. Spatial information, which has received little attention in the literature, has the potential to provide valuable insight to within-host viral and immune dynamics. Unfortunately, state-of-the-art supervised deep learning methods require labeled data, which can be prohibitively expensive to …

Diagnostic Value Of Ultrasound In Children With Transverse Testicular Ectopia, Wei Zhou, Shoulin Li, Hao Wang, Jianchun Yin, Xiaodong Liu, Junhai Jiang, Guanglun Zhou, Jianguo Wen

Faculty, Staff and Student Publications

OBJECTIVE: The study aimed to investigate the diagnostic value of ultrasound in children's transverse testicular ectopia (TTE).

MATERIALS AND METHODS: We retrospectively studies all TTE cases diagnosed in our hospital from January 2017 to December 2021. All cases were evaluated by ultrasound examination and compared to physical examination and diagnostic laparoscopy results.

RESULTS: This study included 14 TTE patients in total, with a median age was 1.08 years. In the 14 TTE, physical examination found 10 TTE cases, of which nine testes were located in the opposite scrotum, one testis was located in the opposite groin, and the other four …

Machine Learning And Scalable Informatics Methods To Predict Disease Status From Multimodal Biomedical Data, Hossein Mohammadian Foroushani

McKelvey School of Engineering Graduate Student Theses & Dissertations

Biological understanding of complex diseases such as stroke and obesity is critical for the advancement of medicine. Further knowledge discovery can provide effective biomarkers to improve disease diagnosis and prognosis, identify driver mutations, predict individual genetic susceptibility for early prevention and effective disease management, and facilitate development of personalized drugs. Stroke is the second leading cause of death and long-term disability in the world. Thus, stroke management is a time-sensitive emergency. The initial hours after stroke onset map the trajectory of subsequent neurologic complications. Cerebral edema develops hours to days after acute ischemic stroke and may result in midline shift …

Evaluation And Clinical Implementation Of A Dual-Energy Ct Stopping-Power Ratio Mapping Technique For Proton-Therapy Treatment Planning, Maria Jose Medrano Matamoros

McKelvey School of Engineering Graduate Student Theses & Dissertations

Proton radiotherapy has the potential to treat tumors with better conformal dose distribution than competing modalities when the rapid dose falloff at the end of the proton-beam range is correctly aligned to the edge of the clinical target volume (CTV). However, its clinical potential is dependent on the accurate localization of the Bragg-peak position from predicted stopping-power ratio maps. The method that is most commonly used in today’s clinical practice for predicting stopping-power ratio (SPR) consists of a stoichiometric calibrationtechnique based on single-energy CT (SECT) for direct estimation of patient-specific SPR distribution from vendor-reconstructed Hounsfield Unit (HU) images. Unfortunately, this …

Advancing The Portability, Field Of View, And Spatiotemporal Resolution Of Multi-Parametric Photoacoustic Microscopy, Fenghe Zhong

McKelvey School of Engineering Graduate Student Theses & Dissertations

Capable of structural, functional, molecular, and metabolic imaging with high spatial resolution in vivo, photoacoustic microscopy (PAM) is an emerging tool in biomedical research. Further, recent advances in multi-parametric acquisition and analysis make PAM uniquely capable of simultaneously mapping the total concentration of hemoglobin (CHb), oxygen saturation of hemoglobin (sO2), and blood flow speed. However, there are multiple major limitations, including, the large footprint, low imaging speed, limited imaging contrast, and insufficient axial resolution, which impedance its applications in basic and translational research. In this dissertation, I presented potential solutions to overcome the limitations above.In the first part of this …

Absolute Quantification Of Tc-99m Activity Distributions Using A Planar Molecular Breast Imaging Commercial System, Benjamin P. Lopez

Dissertations and Theses (Open Access)

Molecular breast imaging (MBI) uses two dedicated-breast semiconductor detectors to visualize the preferential uptake of technetium-99m-sestamibi (^99mTc-sestamibi) by breast cancer cells relative to surrounding benign breast tissues. Clinically, MBI is used primarily as a supplementary tool to standard-of-care mammography because of its improved detection of breast cancers, especially in women with mammographically-dense breasts. Because of a lack of image corrections, MBI applications are currently limited to qualitative evaluations of relative pixel intensities between image regions with suspected lesions and normal tissue.

The objective of this dissertation was to use Monte Carlo simulations to better characterize the MBI imaging …

Hepatocellular Carcinoma Image-Guided Intervention: Quantitative Characterization Of Reagents For Thermochemical Ablation, Emily A. Thompson

Dissertations and Theses (Open Access)

Thermochemical ablation (TCA) is a minimally invasive therapy under development for hepatocellular carcinoma, a leading cause of cancer death worldwide. TCA utilizes acid-base chemistry delivered simultaneously to induce local ablation when administered. When delivered via a mixing catheter placed directly into the tumor, acid (e.g., AcOH) and base (e.g., NaOH) react to completion at the catheter tip, producing the acetate salt, water, and releasing heat (Δ>50°C) in sufficient quantities to induce lethal osmotic and thermal stress in tumor cells. However, these two reagents are not distinguishable from tissues with noninvasive imaging modalities, which makes monitoring the delivery of TCA …

Understanding Deep Learning - Challenges And Prospects, Niha Adnan, Fahad Umer

Department of Surgery Docs

The developments in Artificial Intelligence have been on the rise since its advent. The advancements in this field have been the innovative research area across a wide range of industries, making its incorporation in dentistry inevitable. Artificial Intelligence techniques are making serious progress in the diagnostic and treatment planning aspects of dental clinical practice. This will ultimately help in the elimination of subjectivity and human error that are often part of radiographic interpretations, and will improve the overall efficiency of the process. The various types of Artificial Intelligence algorithms that exist today make the understanding of their application quite complex. …

Blood Flow Restriction Training After Patellar Instability (Brains Trial), Benjamin D. Brightwell, Austin V. Stone, Xiaojuan Li, Peter A. Hardy, Katherine L. Thompson, Brian W. Noehren, Cale A. Jacobs

Orthopaedic Surgery and Sports Medicine Faculty Publications

Background

Patellar instability is a common and understudied condition that disproportionally affects athletes and military personnel. The rate of post-traumatic osteoarthritis that develops following a patellar dislocation can be up to 50% of individuals 5–15 years after injury. Conservative treatment is the standard of care for patellar instability however, there are no evidence-informed rehabilitation guidelines in the scientific literature. The purpose of this study is to assess the effectiveness of blood-flow restriction training (BFRT) for patellar instability. Our hypotheses are that this strategy will improve patient-reported outcomes and accelerate restoration of symmetric strength and knee biomechanics necessary to safely return …

System Measurements For X-Ray Phase And Diffraction Imaging, Erik Wolfgang Tripi

Legacy Theses & Dissertations (2009 - 2024)

In medical imaging, X rays are used to look inside the body to find fractures in bones, abnormal masses, cavities in teeth, and so on. What makes X rays so good at looking at these types of structures is the X ray’s penetration power. When imaging soft tissue to search for tumors, X-ray images tend to have difficulty performing well. The reason for this is that the background structures, such as fat or fibro glandular tissue have similar absorption coefficients as the tumor. Mammography tends to have a high false positive rate and can miss tumors entirely as well. There …

Statistical Measurements Of Dispersion Measure Fluctuations Of Frbs, Siyao Xu, David H. Weinberg, Bing Zhang

Physics & Astronomy Faculty Research

Extragalactic fast radio bursts (FRBs) have large dispersion measures (DMs) and are unique probes of intergalactic electron density fluctuations. By using the recently released First CHIME/FRB Catalog, we reexamined the structure function (SF) of DM fluctuations. It shows a large DM fluctuation similar to that previously reported in Xu & Zhang, but no clear correlation hinting toward large-scale turbulence is reproduced with this larger sample. To suppress the distortion effect from FRB distances and their host DMs, we focus on a subset of CHIME catalog with DM < 500 pc cm-3. A trend of nonconstant SF and nonzero correlation function (CF) at angular separations θ less than 10 is seen, but with large statistical uncertainties. The difference found between SF and that derived from CF at θ ≲ 10 can be ascribed to the large statistical uncertainties or the density inhomogeneities on scales on the order of 100 Mpc. The possible correlation of electron density fluctuations and inhomogeneities of density distribution should be tested when several thousands of FRBs are available.

From Mathematics To Medicine: A Practical Primer On Topological Data Analysis (Tda) And The Development Of Related Analytic Tools For The Functional Discovery Of Latent Structure In Fmri Data, Andrew Salch, Adam Regalski, Hassan Abdallah, Raviteja Suryadevara, Michael J. Catanzaro, Vaibhav A. Diwadkar

Mathematics Faculty Research Publications

fMRI is the preeminent method for collecting signals from the human brain in vivo, for using these signals in the service of functional discovery, and relating these discoveries to anatomical structure. Numerous computational and mathematical techniques have been deployed to extract information from the fMRI signal. Yet, the application of Topological Data Analyses (TDA) remain limited to certain sub-areas such as connectomics (that is, with summarized versions of fMRI data). While connectomics is a natural and important area of application of TDA, applications of TDA in the service of extracting structure from the (non-summarized) fMRI data itself are heretofore nonexistent. …

Quantitative Magnetic Resonance Imaging For The Early Prediction Of Treatment Response In Triple Negative Breast Cancer, Benjamin C. Musall

Dissertations and Theses (Open Access)

Triple Negative Breast Cancer (TNBC) is an aggressive subtype of breast cancer which lacks upregulated hormone receptors. Because of this, it is not vulnerable to clinically available targeted therapies. When treated with standard of care neoadjuvant systemic therapy (NAST), TNBC only shows approximately a 40% rate of pathologic complete response (pCR). A biomarker which could predict TNBC response to NAST early during treatment would be useful, as it would allow for non-responders to be triaged to alternative therapies and potentially allow for the treatment of responders to be de-escalated.

Quantitative Magnetic Resonance Imaging (MRI) may be used to probe and …

Using Deep Learning To Analyze Materials In Medical Images, Carson Molder

Computer Science and Computer Engineering Undergraduate Honors Theses

Modern deep learning architectures have become increasingly popular in medicine, especially for analyzing medical images. In some medical applications, deep learning image analysis models have been more accurate at predicting medical conditions than experts. Deep learning has also been effective for material analysis on photographs. We aim to leverage deep learning to perform material analysis on medical images. Because material datasets for medicine are scarce, we first introduce a texture dataset generation algorithm that automatically samples desired textures from annotated or unannotated medical images. Second, we use a novel Siamese neural network called D-CNN to predict patch similarity and build …

A Deep Learning Approach To Diagnostic Classification Of Prostate Cancer Using Pathology–Radiology Fusion, Pegah Khosravi, Maria Lysandrou, Mahmoud Eljalby, Qianzi Li, Ehsan Kazemi, Pantelis Zisimopoulos, Alexandros Sigaras, Matthew Brendel, Josue Barnes, Camir Ricketts, Dmitry Meleshko, Andy Yat, Timothy D. Mcclure, Brian D. Robinson, Andrea Sboner, Olivier Elemento, Bilal Chughtai, Iman Hajirasouliha

Publications and Research

Background

A definitive diagnosis of prostate cancer requires a biopsy to obtain tissue for pathologic analysis, but this is an invasive procedure and is associated with complications.

Purpose

To develop an artificial intelligence (AI)-based model (named AI-biopsy) for the early diagnosis of prostate cancer using magnetic resonance (MR) images labeled with histopathology information.

Study Type

Retrospective.

Population

Magnetic resonance imaging (MRI) data sets from 400 patients with suspected prostate cancer and with histological data (228 acquired in-house and 172 from external publicly available databases).

Field Strength/Sequence

1.5 to 3.0 Tesla, T2-weighted image pulse sequences.

Assessment

MR images reviewed and selected …

Therapy And Medical Imaging Applications Of Focusing Polycapillary X-Ray Optics, Weiyuan Sun

Legacy Theses & Dissertations (2009 - 2024)

Focusing polycapillary optics yield high gains in intensity and increased spatial resolution for a variety of clinical, lab-based, synchrotron, or in situ analysis applications. In this dissertation we investigate the extension of two applications of focusing polycapillary optics. The first is the application of polycapillary optics in radiation therapy. This discussion includes measurements and calculation of dose for focused beam orthovoltage therapy. A system has been designed to investigate whether the polycapillary optics can produce an X-ray beam which can give more accurate dose painting due to the higher dose concentration at the focal spot. X-ray exposures were measured with …

Joint Modeling Of Rnaseq And Radiomics Data For Glioma Molecular Characterization And Prediction, Zeina A. Shboul, Norou Diawara, Arastoo Vossough, James Y. Chen, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

RNA sequencing (RNAseq) is a recent technology that profiles gene expression by measuring the relative frequency of the RNAseq reads. RNAseq read counts data is increasingly used in oncologic care and while radiology features (radiomics) have also been gaining utility in radiology practice such as disease diagnosis, monitoring, and treatment planning. However, contemporary literature lacks appropriate RNA-radiomics (henceforth, radiogenomics) joint modeling where RNAseq distribution is adaptive and also preserves the nature of RNAseq read counts data for glioma grading and prediction. The Negative Binomial (NB) distribution may be useful to model RNAseq read counts data that addresses potential shortcomings. …

A Deep Learning U-Net For Detecting And Segmenting Liver Tumors, Vidhya Cardozo

Theses and Dissertations

Visualization of liver tumors on simulation CT scans is challenging even with contrast-enhancement, due to the sensitivity of the contrast enhancement to the timing of the CT acquisition. Image registration to magnetic resonance imaging (MRI) can be helpful for delineation, but differences in patient position, liver shape and volume, and the lack of anatomical landmarks between the two image sets makes the task difficult. This study develops a U-Net based neural network for automated liver and tumor segmentation for purposes of radiotherapy treatment planning. Non-contrast simulation based abdominal CT axial scans of 52 patients with primary liver tumors were utilized. …

Intense Monochromatic Photons Above 100 Kev From An Inverse Compton Source, Kirsten Deitrick, Georg H. Hoffstaetter, Carl Franck, Bruno D. Muratori, Peter H. Williams, Geoffrey A, Krafft, Balša Terzić, Joe Crone, Hywel Owen

Physics Faculty Publications

Quasimonochromatic x rays are difficult to produce above 100 keV, but have a number of uses in x-ray and nuclear science, particularly in the analysis of transuranic species. Inverse Compton scattering (ICS) is capable of fulfilling this need, producing photon beams with properties and energies well beyond the limits of typical synchrotron radiation facilities. We present the design and predicted output of such an ICS source at CBETA, a multiturn energy-recovery linac with a top energy of 150 MeV, which we anticipate producing x rays with energies above 400 keV and a collimated flux greater than 108 photons per second …

Fractal And Edge-Based Techniques For Kidney Enhancement And Segmentation On Magnetic Resonance Images (Mri), Alaá Rateb Mahmoud Al-Shamasneh

Student Works (2020-2029)

Recently, many rapid developments in digital medical imaging have made further contributions to healthcare systems. However, the segmentation of regions of interest in medical images plays a vital role in assisting doctors in their medical diagnoses and for the early detection of disease. Since health issues related to the kidneys are increasing exponentially, this thesis focused on developing methods for the segmentation of MRI images of the kidney. Kidney images frequently suffer from low contrast, low resolution and noise, and are blur. Hence, it is necessary to enhance the images in order to improve the segmentation. Therefore, the current thesis …

Hyperpolarized Carbon-13 Magnetic Resonance Measurements Of Tissue Perfusion And Metabolism, Keith Michel

Dissertations and Theses (Open Access)

Hyperpolarized Magnetic Resonance Imaging (HP MRI) is an emerging modality that enables non-invasive interrogation of cells and tissues with unprecedented biochemical detail. This technology provides rapid imaging measurements of the activity of a small quantity of molecules with a strongly polarized nuclear magnetic moment. This polarization is created in a polarizer separate from the imaging magnet, and decays continuously towards a non-detectable thermal equilibrium once the imaging agent is removed from the polarizer and administered by intravenous injection. Specialized imaging strategies are therefore needed to extract as much information as possible from the HP signal during its limited lifetime.

In …

Integrated Multiparametric Radiomics And Informatics System For Characterizing Breast Tumor Characteristics With The Oncotypedx Gene Assay, Michael A. Jacobs, Christopher B. Umbricht, Vishwa S. Parekh, Riham H. El Khouli, Leslie Cope, Katarzyna J. Macura, Susan Harvey, Antonio C. Wolff

Radiology Faculty Publications

Optimal use of multiparametric magnetic resonance imaging (mpMRI) can identify key MRI parameters and provide unique tissue signatures defining phenotypes of breast cancer. We have developed and implemented a new machine-learning informatic system, termed Informatics Radiomics Integration System (IRIS) that integrates clinical variables, derived from imaging and electronic medical health records (EHR) with multiparametric radiomics (mpRad) for identifying potential risk of local or systemic recurrence in breast cancer patients. We tested the model in patients (n = 80) who had Estrogen Receptor positive disease and underwent OncotypeDX gene testing, radiomic analysis, and breast mpMRI. The IRIS method was trained …

Mapping Gadolinium Contrast In A Complex Ionic And Photosynthesis Environment Of Pineapple By Near-Infrared And X-Ray Imaging, Subhendra Sarkar, Zoya Vinokur, Chen Xu, Tetiana Soloviova, Amina Shahbaz, Aldona Gjoni

Publications and Research

This work explores the diffusivity of a lanthanide complex, Eovist (Gadolinium-Ethoxy Benzyl Diethylenetriamine pentaacetate) that is stable in neutral media but is not in acidic environment. In the current work an acidic fruit model like pineapple that is rich in transition metals was used and a possible transmetallation reaction among Eovist and transition metal complexes was tested using X-ray imaging. Another goal of this work was to perturb the usual and the unusual photosynthesis systems that pineapple has maintained for millions of years during the evolution of circadian genes for efficient water conservation by dark photosynthesis. To detect such photosynthesis …