Bioimaging and Biomedical Optics Commons^™

Plasma Protein Signatures Of Adult Asthma, Gordon J. Smilnak, Yura Lee, Abhijnan Chattopadhyay, Annah B. Wyss, Julie D. White, Sinjini Sikdar, Jianping Jin, Andrew J. Grant, Alison A. Motsinger-Reif, Jian-Liang Li, Mikyeong Lee, Bing Yu, Stephanie J. London

Mathematics & Statistics Faculty Publications

Background: Adult asthma is complex and incompletely understood. Plasma proteomics is an evolving technique that can both generate biomarkers and provide insights into disease mechanisms. We aimed to identify plasma proteomic signatures of adult asthma.

Methods: Protein abundance in plasma was measured in individuals from the Agricultural Lung Health Study (ALHS) (761 asthma, 1095 non-case) and the Atherosclerosis Risk in Communities study (470 asthma, 10,669 non-case) using the SOMAScan 5K array. Associations with asthma were estimated using covariate adjusted logistic regression and meta-analyzed using inverse-variance weighting. Additionally, in ALHS, we examined phenotypes based on both asthma and seroatopy (asthma with …

Reactive Chemistries For Protein Labeling, Degradation, And Stimuli Responsive Delivery, Myrat Kurbanov

Doctoral Dissertations

Reactive chemistries for protein chemical modification play an instrumental role in chemical biology, proteomics, and therapeutics. Depending on the application, the selectivity of these modifications can range from precise modification of an amino acid sequence by genetic manipulation of protein expression machinery to a stochastic modification of lysine residues on the protein surface. Ligand-Directed (LD) chemistry is one of the few methods for targeted modification of endogenous proteins without genetic engineering. However, current LD strategies are limited by stringent amino acid selectivity. To bridge this gap, this thesis focuses on the development of highly reactive LD Triggerable Michael Acceptors (LD-TMAcs) …

Analyzing Pseudomonas Aeruginosa With Bacteriophage Tags Using Photoacoustic Flow Cytometry, Jennifer C. Schinke

Electronic Theses and Dissertations

The number of daily bacterial infections is climbing and the CDC explains that this is due to the antibiotic-resistant threat in the United States. Finding a faster way of bacterial identification is necessary as it currently takes 1-4 days for a medical lab to culture and identify bacteria. Photoacoustic flow cytometry (PAFC) can be used as an alternative method resulting in swift identification within an hour (Edgar, 2019). Pseudomonas aeruginosa, cell line PA01, will be coated in up to a few hundred red dyed phages making it detectible by the photoacoustic flow cytometry system. Bacteriophages (phages) are viruses that …

Mechanisms Of Theta Burst Transcranial Ultrasound Induced Plasticity In The Human Motor Cortex, Yazan Shamli Oghli, Talyta Grippe, Tarun Arora, Tasnuva Hoque, Ghazaleh Darmani, Robert Chen

Department of Medicine Faculty Papers

BACKGROUND: Transcranial ultrasound stimulation (TUS) is a novel non-invasive brain stimulation technique with high depth penetrance and spatial resolution. Theta-burst TUS (tbTUS) is a plasticity-inducing protocol which increases motor cortical excitability for up to 30 min following 80s of sonication. While this protocol may have therapeutic potential for the treatment of psychiatric and neurological disorders, the mechanisms of action of TUS remain unclear.

OBJECTIVE: We conducted the first pharmacological study to examine the mechanisms of TUS in human primary motor cortex. By administering brain-active drugs with known mechanisms of action, we aimed to elucidate the mechanisms of tbTUS.

METHODS: Fourteen …

Noninvasively Monitoring Of Cerebral Blood Flow In Piglet Models Of Graded Hemorrhage And Hypoxic Ischemic Brain Injury Using Diffuse Correlation Spectroscopy And Near-Infrared Spectroscopy, Randolph Sinahon, Danielle Shoshany, Shadi Malaeb, Mert Deniz Polat, Meltem Izzetoglu, Kurtulus Izzetoglu

St. Chris Research Day

No abstract provided.

Cerebral Blood Flow Measured By Diffuse Correlation Spectroscopy For Monitoring Depth Of Anesthesia In Piglets, Mert Deniz Polat, Kurtulus Izzetoglu, Randolph Sinahon, Meltem Izzetoglu, Shadi Malaeb

St. Chris Research Day

No abstract provided.

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

McKelvey School of Engineering 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 …

Enhancement Of Deep Learning Protein Structure Prediction, Ruoming Shen

Modeling, Simulation and Visualization Student Capstone Conference

Protein modeling is a rapidly expanding field with valuable applications in the pharmaceutical industry. Accurate protein structure prediction facilitates drug design, as extensive knowledge about the atomic structure of a given protein enables scientists to target that protein in the human body. However, protein structure identification in certain types of protein images remains challenging, with medium resolution cryogenic electron microscopy (cryo-EM) protein density maps particularly difficult to analyze. Recent advancements in computational methods, namely deep learning, have improved protein modeling. To maximize its accuracy, a deep learning model requires copious amounts of up-to-date training data.

This project explores DeepSSETracer, a …

Differentiating Axonal From Demyelinating Neuropathies Using Multiparametric Quantitative Mri Of Peripheral Nerves, Jacob D. Baraz, Stephanie Xuan, Sadaf Saba, Xue Yang, Ryan Castoro, Yang Xuan, Alison Roth, Richard D. Dortch, Jun Li, Yongsheng Chen

Medical Student Research Symposium

Objectives: To develop a multiparametric quantitative MRI (qMRI) method to track pathological changes in the peripheral neuropathies.

Background: Irrespective of the causes or types of polyneuropathies, peripheral nerves are mainly afflicted by two kinds of pathologies – axonal loss and demyelination. It is critical to differentiate between the two as treatments are different for the two conditions. While nerve conduction studies (NCS) have been used to differentiate the two pathologies in the distal nerves, there are no tools to probe the pathologies in the proximal peripheral nerves. This is particularly needed when distal nerves become non-responsive in NCS.

Methods: We …

Improving The Reliability And Accessibility Of Ct Perfusion Imaging In Acute Ischemic Stroke, Kevin J. Chung

Electronic Thesis and Dissertation Repository

CT perfusion (CTP) imaging is a validated treatment decision support tool in acute ischemic stroke. Automated analysis of CTP cerebral blood flow (CBF) and Tmax maps produces estimates of ischemic core and penumbra volumes used to determine target mismatch profiles for treatment. However, availability and utilization of CTP is low due to diagnostic variability between CTP software and technical, logistical, and radiation dose considerations that may limit its routine adoption. The objective of this doctoral research was to improve the reliability and accessibility of CTP by (1) improving diagnostic agreement between CTP software, (2) enabling perfusion imaging with standard acute …

Session 12: Active Learning To Minimize The Possible Risk From Future Epidemics, Kc Santosh

SDSU Data Science Symposium

In medical imaging informatics, for any future epidemics (e.g., Covid-19), deep learning (DL) models are of no use as they require a large dataset as they take months and even years to collect enough data (with annotations). In such a context, active learning (or human/expert-in-the-loop) is the must, where a machine can learn from the first day with minimum possible labeled data. In unsupervised learning, we propose to build pre-trained DL models that iteratively learn independently over time, where human/expert intervenes only when it makes mistakes and for only a limited data. In our work, deep features are used to …

Estimation Of Free Water-Corrected Microscopic Fractional Anisotropy., Nico J J Arezza, Tales Santini, Mohammad Omer, Corey A Baron

Medical Biophysics Publications

Water diffusion anisotropy MRI is sensitive to microstructural changes in the brain that are hallmarks of various neurological conditions. However, conventional metrics like fractional anisotropy are confounded by neuron fiber orientation dispersion, and the relatively low resolution of diffusion-weighted MRI gives rise to significant free water partial volume effects in many brain regions that are adjacent to cerebrospinal fluid. Microscopic fractional anisotropy is a recent metric that can report water diffusion anisotropy independent of neuron fiber orientation dispersion but is still susceptible to free water contamination. In this paper, we present a free water elimination (FWE) technique to estimate microscopic …

Ultrasensitive Tapered Optical Fiber Refractive Index, Erem Ujah, Meimei Lai, Gymama Slaughter

Electrical & Computer Engineering Faculty Publications

Refractive index (RI) sensors are of great interest for label-free optical biosensing. A tapered optical fiber (TOF) RI sensor with micron-sized waist diameters can dramatically enhance sensor sensitivity by reducing the mode volume over a long distance. Here, a simple and fast method is used to fabricate highly sensitive refractive index sensors based on localized surface plasmon resonance (LSPR). Two TOFs (l = 5 mm) with waist diameters of 5 µm and 12 µm demonstrated sensitivity enhancement at λ = 1559 nm for glucose sensing (5-45 wt%) at room temperature. The optical power transmission decreased with increasing glucose concentration due …

Verification Of Proton Range Predictions In Proton Treatment Planning Using X-Ray Ct Or Proton Ct Imaging, Nicholas S. Yee

Graduate Research Theses & Dissertations

The objective of this paper is to compare the range errors for two treatment plans; one using x-ray CT and the other using proton CT for calculating dose distributions in an animal tissue phantom. We shot 150 MeV proton beam through a meat phantom to a film stack to measure the exponential drop of dose at the Bragg peak until zero dose remained. Plotting the depth dose curves and performing gamma analyses are two ways to quantify the proton range errors when comparing them to depth dose curves from film measurements in the phantom. The depth dose curves give us …

The Role Of Generative Adversarial Networks In Bioimage Analysis And Computational Diagnostics., Ahmed Naglah

Electronic Theses and Dissertations

Computational technologies can contribute to the modeling and simulation of the biological environments and activities towards achieving better interpretations, analysis, and understanding. With the emergence of digital pathology, we can observe an increasing demand for more innovative, effective, and efficient computational models. Under the umbrella of artificial intelligence, deep learning mimics the brain’s way in learn complex relationships through data and experiences. In the field of bioimage analysis, models usually comprise discriminative approaches such as classification and segmentation tasks. In this thesis, we study how we can use generative AI models to improve bioimage analysis tasks using Generative Adversarial Networks …

Seeing The Big Picture: System Architecture Trends In Endoscopy And Led-Based Hyperspectral Subsystem Intergration, Craig M. Browning

<strong> Theses and Dissertations </strong>

Early-stage colorectal lesions remain difficult to detect. Early development of neoplasia tends to be small (less than 10 mm) and flat and difficult to distinguish from surrounding mucosa. Additionally, optical diagnosis of neoplasia as benign or malignant is problematic. Low rates of detection of these lesions allow for continued growth in the colorectum and increased risk of cancer formation. Therefore, it is crucial to detect neoplasia and other non-neoplastic lesions to determine risk and guide future treatment. Technology for detection needs to enhance contrast of subtle tissue differences in the colorectum and track multiple biomarkers simultaneously. This work implements one …

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 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 …

Labeling Melanoma Cells With Black Microspheres For Improved Sensitivity In Detection Via Photoacoustic Flow Cytometry, Tori Kocsis

Electronic Theses and Dissertations

Melanoma is an aggressive form of skin cancer known for developing into metastatic disease. Current clinical diagnostics, including medical imaging and tissue biopsy, provide a poor prognosis since the cancer is in the late stages of disease progression. In recent years, photoacoustic flow cytometry has allowed for the detection of circulating melanoma cells within patient blood samples in vitro. Although this method exploits the naturally-produced melanin within the cells, it has only successfully detected highly-pigmented melanoma cell lines. Since various forms of melanoma exist, each with varying melanin concentrations, this research aims to provide a novel method for detecting lightly-pigmented …

The Effects Of Metronomic And Maximum-Tolerated Dose Chemotherapy In Colorectal Cancer Angiogenesis: A Combined Approach Using Endoscopic Diffuse Reflectance Spectroscopy And Mrna Expression, Ariel Isaac Mundo Ortiz

Graduate Theses and Dissertations

Colorectal cancer (CRC) continues to be one of the most incident and deadliest types of cancer worldwide. Chemotherapy has proven effective to reduce tumor burden for CRC patients, but there are several disadvantages associated with the use of mainstay maximtolerated dose (MTD) chemotherapeutic strategies. Metronomic chemotherapy (MET) has been developed as an alternative that addresses the shortcomings of maximum-tolerated dose chemotherapy but so far its effectiveness as a neoadjuvant strategy for CRC has not been explored.

This dissertation uses a combined optics and molecular biology approach (using diffuse reflectance spectroscopy and mRNA expression) to study the changes in angiogenesis and …

Bayesian Network-Based Diagnostic Support Tool With Limited Point-Of-Care Ultrasound For Work-Related Elbow Injuries, Cristina Maria Franceschini Sánchez

USF Tampa Graduate Theses and Dissertations

The upper extremity is commonly injured at the workplace, frequently involving the elbow. Currently, there are not many diagnostic support tools for elbow injuries. Developing a clinical decision support tool would allow for narrowing differential diagnoses and guide management steps in a timely and cost-effective manner. In a descriptive retrospective cohort study, 85 non-contrast elbow MRIs were obtained from a large Workers Compensation insurer database. MRIs were either (a) greater than 2 weeks after first clinic visit, or (b) more than 6 weeks after injury, but (c) not more than 3 months after injury. A Bayesian network-based diagnostic support tool …

Design And Development Of Software With A Graphical User Interface To Display And Convert Multiple Microscopic Histology Images, Sayed Ahmadreza Razian, Majid Jadidi, Alexey Kamenskiy

UNO Student Research and Creative Activity Fair

Histological images are widely used to assess the microscopic anatomy of biological tissues. Recent advancements in image analysis allow the identification of structural features on histological sections that can help advance medical device development, brain and cancer research, drug discovery, vascular mechanobiology, and many other fields. Histological slide scanners create images in SVS and TIFF formats that were designed to archive image blocks and high-resolution textual information. Because these formats were primarily intended for storage, they are often not compatible with conventional image analysis software and require conversion before they can be used in research. We have developed a user-friendly …

Cbct In Clinical Practice, Tarunjeet Pabla Bds, Dmd, Ms, Dip. Abomr, Hugo C. Campos Dds, Dmd, Mds, Dip. Abomr, Aruna Ramesh Bds, Dmd, Ms, Dip. Abomr

The Journal of the Michigan Dental Association

This feature explores the integration of Cone Beam Computed Tomography (CBCT) into dental practice, offering guidelines for best practices. Introduced in 2001, CBCT revolutionized dental radiography, impacting various clinical areas. The article emphasizes the need for clinicians to comprehend CBCT technology, its benefits, and potential risks. It delves into CBCT imaging considerations, technical parameters (Field of View, Voxel Size, Spatial and Contrast Resolution), image viewing, artifacts, machine calibration, and service. Addressing radiation dose, risks, and protection, the article outlines decision-making for 2D vs. 3D imaging. It underscores the responsibility of interpreting CBCT images, legal considerations, return on investment, and the …

Therapeutic Treatment With The Anti-Inflammatory Drug Candidate Mw151 May Partially Reduce Memory Impairment And Normalizes Hippocampal Metabolic Markers In A Mouse Model Of Comorbid Amyloid And Vascular Pathology, David J. Braun, David K. Powell, Christopher J. Mclouth, Saktimayee M. Roy, D. Martin Watterson, Linda J. Van Eldik

Neuroscience Faculty Publications

Alzheimer's disease (AD) is the leading cause of dementia in the elderly, but therapeutic options are lacking. Despite long being able to effectively treat the ill-effects of pathology present in various rodent models of AD, translation of these strategies to the clinic has so far been disappointing. One potential contributor to this situation is the fact that the vast majority of AD patients have other dementia-contributing comorbid pathologies, the most common of which are vascular in nature. This situation is modeled relatively infrequently in basic AD research, and almost never in preclinical studies. As part of our efforts to develop …

Toward A Multimodal Computer-Aided Diagnostic Tool For Alzheimer’S Disease Conversion, Danilo Pena, Jessika Suescun, Mya Schiess, Timothy M. Ellmore, Luca Giancardo, Alzheimer’S Disease Neuroimaging Initiative

Publications and Research

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder. It is one of the leading sources of morbidity and mortality in the aging population AD cardinal symptoms include memory and executive function impairment that profoundly alters a patient’s ability to perform activities of daily living. People with mild cognitive impairment (MCI) exhibit many of the early clinical symptoms of patients with AD and have a high chance of converting to AD in their lifetime. Diagnostic criteria rely on clinical assessment and brain magnetic resonance imaging (MRI). Many groups are working to help automate this process to improve the clinical workflow. Current …

Biomedical Applications Of Lanthanide Nanomaterials, For Imaging, Sensing And Therapy, Qize Zhang, Stephen O'Brien, Jan Grimm

Publications and Research

The application of nanomaterials made of rare earth elements within biomedical sciences continues to make significant progress. The rare earth elements, also called the lanthanides, play an essential role in modern life through materials and electronics. As we learn more about their utility, function, and underlying physics, we can contemplate extending their applications to biomedicine. This particularly applies to diagnosis and radiation therapy due to their relatively unique features, such as an ultra-wide Stokes shift in the luminescence, variable magnetism and potentially tunable properties, due to the library of lanthanides available and their multivalent oxidation state chemistry. The ability to …

Deep Learning Approach To Improved Image Quality For Medical Diagnostics, Olivia Loesch, Katie Leyba, Halyley Chan, Craig Goergen

Discovery Undergraduate Interdisciplinary Research Internship

The United Nation’s health-related Sustainable Development Goals are difficult to achieve in low- and middle-income countries due to workforce shortages and inadequate health surveillance systems. However, with the growth of artificial intelligence (AI) and computer algorithms, it is possible to apply AI to healthcare technologies to improve progress towards these UN standards. This project aims at using and improving computer algorithms and deep learning to aid in the extraction of important structural and functional information from murine carotid artery ultrasound and photoacoustic images. First, we created a large database of simulated photoacoustic images to optimize the algorithms. These images were …

Generation, Analysis, And Evaluation Of Patient-Specific, Osteoligamentous, Spine Meshes, Austin R. Tapp

Biomedical Engineering Theses & Dissertations

Scoliosis, an abnormal curvature of the spine, is traditionally corrected with bracing treatments or by a highly invasive posterior spinal fusion (PSF) operation. These correction strategies are constrained by current imaging modalities, which fail to elucidate the soft tissue anatomy that is known to play a critical role in spinal stiffness and overall structure. Osteoligamentous segmentations of the spinal column offer a foundation for downstream finite element (FE) studies seeking to optimize bracing treatments or determine ideal surgical approaches.

This thesis presents methods for automatically and semi-automatically segmenting vertebrae and surrounding soft tissues of the spinal column using X-ray computed …

Pairwise Correlation Analysis Of The Alzheimer’S Disease Neuroimaging Initiative (Adni) Dataset Reveals Significant Feature Correlation, Erik D. Huckvale, Matthew W. Hodgman, Brianna B. Greenwood, Devorah O. Stucki, Katrisa M. Ward, Mark T. W. Ebbert, John S. K. Kauwe, The Alzheimer’S Disease Neuroimaging Initiative, The Alzheimer’S Disease Metabolomics Consortium, Justin B. Miller

Sanders-Brown Center on Aging Faculty Publications

The Alzheimer’s Disease Neuroimaging Initiative (ADNI) contains extensive patient measurements (e.g., magnetic resonance imaging [MRI], biometrics, RNA expression, etc.) from Alzheimer’s disease (AD) cases and controls that have recently been used by machine learning algorithms to evaluate AD onset and progression. While using a variety of biomarkers is essential to AD research, highly correlated input features can significantly decrease machine learning model generalizability and performance. Additionally, redundant features unnecessarily increase computational time and resources necessary to train predictive models. Therefore, we used 49,288 biomarkers and 793,600 extracted MRI features to assess feature correlation within the ADNI dataset to determine the …

Artificial Image Objects For Classification Of Breast Cancer Biomarkers With Transcriptome Sequencing Data And Convolutional Neural Network Algorithms, Xiangning Chen, Daniel G. Chen, Zhongming Zhao, Justin M. Balko, Jingchun Chen

School of Medicine Faculty Publications

Background: Transcriptome sequencing has been broadly available in clinical studies. However, it remains a challenge to utilize these data effectively for clinical applications due to the high dimension of the data and the highly correlated expression between individual genes. Methods: We proposed a method to transform RNA sequencing data into artificial image objects (AIOs) and applied convolutional neural network (CNN) algorithms to classify these AIOs. With the AIO technique, we considered each gene as a pixel in an image and its expression level as pixel intensity. Using the GSE96058 (n = 2976), GSE81538 (n = 405), and GSE163882 (n = …

Frequency Dependent Diffusion Kurtosis Measurement In The Human Brain With Oscillating Gradients, Kevin B. Borsos

Electronic Thesis and Dissertation Repository

Oscillating gradient spin-echo (OGSE) is an implementation of diffusion MRI that enables shorter effective diffusion times than the conventional pulse gradient spin-echo (PGSE) by periodically modulating the diffusion gradient. Measurements of the diffusion kurtosis, which reflects the degree of restricted diffusion, have previously been prohibited with OGSE due to technical limitations of clinical gradient systems. This thesis presents a novel oscillating gradient waveform that enables the measurement of kurtosis using OGSE without requiring advanced gradient hardware. Decreases of kurtosis are observed in OGSE acquisitions of healthy human subjects relative to PGSE, demonstrating the dependence of the kurtosis on oscillation frequency. …