Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons^™

Biomechanical Outcomes Of Distinct Tka Surgical Alignments And Implant Designs, Alexis Kathleen Nelson-Tranum

Theses and Dissertations (ETD)

Introduction. Total knee arthroplasty (TKA) has advanced over the past two decades from traditional post-operative neutral alignment methods with an overall goal of implant longevity to ones that are more personalized to better replicate individual native knee kinematics. Personalizing TKA knee kinematics to better replicate a patient’s native knee kinematics has evolved in response to a reported 20% dissatisfaction by patients with their TKA. These personalization advancements include innovations in surgical alignment techniques include the kinematic alignment (KA) and joint line obliquity (JLO) restoration, in contrast to the mechanical alignment (MA) technique that places everyone into the same mold. Additionally, …

Genotypes Of Snps Of Key Genes Regulate Susceptibility And Drug Sensitivity To Neovascular Amd, Jinglin Cui

Theses and Dissertations (ETD)

Age-related macular degeneration (AMD), particularly its neovascular form, stands as a leading cause of blindness globally, with its prevalence in our country on a steady rise. This underscores the critical impact of neovascular AMD (nAMD) management on patient quality of life and societal burden. Current optimal treatments hinge on anti-vascular endothelial growth factor (anti-VEGF) therapies, though their efficacy varies across different drugs and individuals, highlighting the importance of precise drug selection in clinical outcomes. Research suggests that factors such as baseline vision, age, disease duration, lesion size, central retina thickness, neovascularization type, and demographic differences influence nAMD prognosis. In addition, …

The Validity And Reliability Of Ultrasound As A Tool For Assessing Skeletal Muscle Characteristics In The Pediatric Population, Elizabeth Seewer

Theses and Dissertations (ETD)

Annually, around 5 million people in the U.S. are admitted to Intensive Care Units (ICU) due to critical conditions, with pediatric patients comprising 21% of these admissions. Approximately 40% of pediatric ICU (PICU) patients require mechanical ventilation and extended stays, and about 6% result in death. Survivors often face long-term disabilities, including loss of skeletal muscle mass (SMM), a risk factor for morbidity and mortality. Abdominal computed tomography (CT) scans, often performed during PICU admissions, can assess muscle mass but pose risks of increased cost and radiation exposure. While CT and Magnetic Resonance Imaging (MRI) are gold standards for muscle …

Instrumental Assessment Of Aero-Resistive Expiratory Muscle Strength Rehabilitation Devices, Angela M. Dietsch, Rahul Krishnamurthy, Kelsey Young, Steven M. Barlow

Department of Special Education and Communication Disorders: Faculty Publications

Purpose

Expiratory muscle strength training (EMST) is increasingly being used to treat voice, cough, and swallowing deficits in a wide range of conditions. However, a multitude of aero-resistive EMST models are commercially available, and the absence of side-by-side comparative data interferes with clinicians’ ability to assess which model is best suited to a particular client’s needs. The primary aim of this research was to test and compare the pressure and flow parameters of six currently available EMST models to help inform clinical decision making.

Method

We identified and tested five devices of each of six different EMST models to generate …

Disseminated Coccidioidomycosis Discovered Through Skin Biopsy In A Pregnant Patient From Mexico, Henry Lim, Christina Guo, Marshall Hall, Christian Scheufele, Christopher M. Wong, Michael Carletti, Stephen Weis

North Texas GME Research Forum 2024

Introduction: Coccidioidomycosis is an infection caused by the organism Coccidioides immitis, a fungus endemic to the southwestern United States, Mexico, Central and South America. The presentation of coccidioidomycosis can range from symptoms resembling a simple upper respiratory infection, such as cough, to more severe systemic symptoms including fever, malaise, and chills. Cutaneous lesions of coccidioidomycosis demonstrate a large heterogeneity of clinical manifestations but are significant as they may be the presenting sign of disseminated disease. While usually confined to the lungs, extrapulmonary coccidioidomycosis can occur in about 1 in 200 patients, most commonly associated with immunocompromised status. Pregnancy is an …

Retrospective Review Of Adverse Events After Treatment Of Non-Melanoma Skin Cancer With Image-Guided Superficial Radiation Therapy, Marshall Hall, Henry Lim, Jason Pham, Alyssa Forsyth, Wenqin Du

North Texas GME Research Forum 2024

No abstract provided.

Geometric Favre-Racouchot Syndrome Following Image-Guided Superficial Radiation Therapy, Marshall Hall, Cecilia Nguyen, Christian Scheufele, Christopher M. Wong, Stephen E. Weis, Michael Carletti, Henry Lim

North Texas GME Research Forum 2024

Introduction: Favre-Racouchot Syndrome is a cutaneous disease characterized by nodules, cysts, and comedones located in sun-exposed areas of the face. It is most commonly found on the bilateral temporal and periorbital skin. Favre-Racouchot Syndrome is most associated with chronic sun exposure. It occurs more commonly in cigarette smokers. It has been rarely associated with radiation therapy. It has not been reported after image-guided superficial radiation therapy or in a geometric pattern. Case presentation: We present the first two recorded cases of Favre-Racouchot Syndrome occurring in the setting of image-guided superficial radiation therapy. Both patients presented with well-demarcated geometric plaques with …

Improving Lesion Diameter Reporting On Skin Biopsy Requisition Forms: A Quality Improvement Project, Christopher Wong, Christian Scheufele, Marshall Hall, Henry Lim, Daniel A. Nguyen, Stephen Weis, Michael Carletti, Dustin Wilkes

North Texas GME Research Forum 2024

Background: Skin biopsy requisition forms (SBRFs) are the primary communication tool between dermatologists and dermatopathologists. Diameters of biopsied skin lesions are frequently omitted on SBRFs. This quality improvement project aimed to increase the rate of reporting diameters of neoplasms on SBRFs from an academic dermatology outpatient clinic to greater than 65% within three years. Methods: The Plan-Do-Study-Act model was utilized. An initial audit was performed for SBRFs of biopsies obtained between July 1, 2021, and February 4, 2022 (“Cycle 1”). On February 4, 2022, the authors discussed societal guidelines for lesion diameter reporting on SBRFs (“Intervention A”). Cycle 2 prospectively …

A Konnyaku Jelly Model For Ultrasound-Guided Fascia Iliaca Compartment Block, Arthraj J. Vyas, Matthew C. Lo, Arthur Au, Md

Alpha Omega Alpha Research Symposium Posters

Purpose

Konnyaku Jelly:

•Previously used as effective ultrasound-guided IV access phantom

•Withstands multiple needle piercings without phantom deterioration

•<$3 per pack

Employing A Machine Learning Approach In Precision Oncology To Predict Pik3ca Functional Status And Identify Phenocopying Variants Of Deleterious Pik3ca Mutations, Javier Castillo

CMC Senior Theses

The following proposal describes a modular machine learning approach that detects malfunctioning genes and pathways in cancer using the transcriptome of cancer patients. The transcriptome is underused in precision oncology and, combined with machine learning, can aid in the identification of hidden responders. Applied to the PI3K/AKT/mTOR pathway, this method can be used to predict PIK3CA functional status and identify phenocopying variants of deleterious PIK3CA mutations. The classifier will do this by integrating RNA-seq, copy number, and mutation data from tumors to determine the functional status of PIK3CA using a set of learned gene-specific weights. The classifier will then be …

Socioeconomic Status And Health Disparities Drive Differences In Accelerometer-Derived Physical Activity In Fatty Liver Disease And Significant Fibrosis, Lucia Tabacu, Sajag Swami, Mark Ledbetter, Mohamad S. Siddiqui, Ekaterina Smirnova

Mathematics & Statistics Faculty Publications

Background and aims

The cornerstone of clinical management of patients with nonalcoholic fatty liver disease (NAFLD) are lifestyle changes such as increasing physical activity (PA) aimed at improving cardiometabolic risk. To inform NAFLD prevention and treatment guidelines we aimed to: (i) quantify the role of PA on lowering the risk for NAFLD and fibrosis; (ii) characterize NAFLD and fibrosis association with PA in the context of socioeconomic environment.

Methods

A sample of 2648 participants from the NHANES 2003–2006 was selected to develop survey weighted multivariable logistic regression models for predicting NAFLD and significant fibrosis, diagnosed non-invasively via fatty liver index …

Compton Scattering Of Mammographic Soft X-Ray Beams By Alkali And Transition Metal Salt Filters Produce X-Ray Interference Zones That May Have Treatment Potential For Localized Cancer Lesions, Subhendra N. Sarkar, Eric Lobel, Sabina Rakhmatova, Derbie Desir, Somdat Kissoon, Daler Djuraev, Katie Tam

Publications and Research

In breast x-ray imaging scattered radiation adds 50% of harmful radiation dose from anisotropic Compton scattering mechanism. We have been working with double layered inorganic salt materials that can induce Compton scattering to the incident mammographic x ray beams (in 20-30 kVp range) with adequate isotropy (angular control). Typically metal nitrates and alkali halide salt layers are shown here to cause low energy radiation interference zones with high and low photon intensities and local flux heterogeneity in terms of flux covariance. Spatial variation of low energy photon flux creates concentrated and sparse radiation zones that may be used to induce …

Impact Of Tiered Implementation Of Clinical Decision Support System For Acute Kidney Injury And Nephrotoxin Exposure In Cardiac Surgery Patients, Christopher M. Justice Ii

Graduate Theses, Dissertations, and Problem Reports (ETD)

Background: Nephrotoxin exposure may worsen kidney injury and impair kidney recovery if continued in patients with acute kidney injury (AKI).

Objective: To determine if tiered implementation of a clinical decision support system (CDSS) would reduce nephrotoxin use in cardiac surgery patients with AKI.

Methods: We assessed patients admitted to the cardiac surgery intensive care unit at a tertiary care center from January 2020 to December 2021, and August 2022 to September 2023. A passive electronic AKI alert was activated in Jul 2020, followed by an electronic nephrotoxin alert in March 2023. In this alert, active nephrotoxic medication orders resulted in …

Successful Management Of Spontaneous Unilateral Twin Ectopic Pregnancy With Two-Step Dose Of Methotrexate, Lauren A. Forbes, Navya Nuthivana, Renee Morales

Department of Obstetrics & Gynecology Faculty Publications

The incidence of unilateral tubal twin pregnancy is 1/20,000–1/250,000 with about 100 reported cases. Four of the six cases that were medically managed were successful. A 24-year-old female presented to the emergency department (ED) with vaginal bleeding and abdominal cramping. She was hemodynamically stable without signs of an acute abdomen. Laboratory evaluation revealed she was pregnant with a serum beta-human chorionic gonadotropin (b-hCG) of 798 mIU/mL. Transvaginal ultrasound (TVUS) revealed a single left tubal pregnancy with a yolk sac. The patient elected medical management with body surface area (BSA)–based intramuscular (IM) methotrexate (MTX). On Day 4, the patient returned to …

Caries Risk Prediction In Pediatric Patients Using Machine Learning Techniques: A Retrospective Study, Nagarathna P J, Vishnu Priya Veeraraghavan, Aysha Jebin A, Shikar Daniel, Kaladhar Reddy Aileni, Santosh R Patil

International Arab Journal of Dentistry

Introduction: Dental caries is a multifactorial disease prevalent in children and is often influenced by behavioral, environmental, and genetic factors. Traditional caries risk assessment methods have a limited accuracy and objectivity. Machine learning (ML) models provide a data-driven approach for predicting caries risk, thereby enabling targeted interventions.

Objectives: The main objective of this study is to develop and validate ML models for predicting caries risk in pediatric patients aged 6–12 years by incorporating clinical, behavioral, dietary, and socioeconomic factors.

Methods: This retrospective observational study included 148 children aged 6–12 years. Data, including demographic details, Decayed Missing Filling …

Tim/Tam Receptors: A Potential Biomarker For Predicting Sensitivity To Zika Virus-Induced Oncolysis In Non-Small Cell Lung Cancers, Shankari Somasekar

Honors Undergraduate Theses

Non-small cell lung cancers (NSCLC) constitute 80-85% of lung cancers and are the leading cause of cancer-related deaths globally. The most common cause is prolonged smoking. Current treatment options for NSCLC include surgery, radiation, chemotherapy, targeted drug therapy, and immunotherapy. Although these medications are effective in the short term, patients often face issues of drug resistance and debilitating side effects with prolonged use. Currently, the use of Zika virus (ZIKV) is being researched as a possible alternative treatment for cancer, which minimizes side effects and the risk of drug resistance. TIM/TAM proteins are identified as the putative ZIKV receptors on …

Reliability And Minimal Detectable Change Of The Mx3 Hydration Testing System, Ian Winter, Josie Burdin, Patrick B. Wilson

Exercise Science Faculty Publications

Assessing hydration status outside of laboratories can be challenging given that most hydration measures are invasive, stationary, costly, or have questionable validity. This study investigated the within-day, test-retest reliability, and minimal detectable change (MDC) of the MX3 Hydration Testing System (MX3 Diagnostics), a relatively low cost, noninvasive, and portable method to measure saliva osmolality. Seventy-five adults (44 men, 31 women; 29.6±10.8 yr, 171.1±9.2 cm, 79.1±15.4 kg) presented two saliva samples approximately 3 to 5 minutes apart. Fluid intake was avoided for at least 5 minutes prior to sample collections. For each sample collection, a researcher used the MX3 to tap …

A Scoping Review Of Population Diversity In The Common Genomic Aberrations Of Clear Cell Renal Cell Carcinoma, Sean S. Kumar, Ninad Khandekar, Komal Dani, Saina R. Bhatt, Vinay Duddalwar, Anishka D'Souza

Department of Medicine Faculty Publications

Introduction: Previous literature has shown that clear cell renal cell carcinoma (ccRCC) is becoming a more prevalent diagnosis and that the incidence and mortality differ both regionally and racially. While the molecular profiles for ccRCC are studied regionally through biopsy and sequencing techniques, the genomic landscape and ccRCC diversity data are not well-studied. We conducted a review of the known genomic data on 6 of the most clinically relevant DNA biomarkers in ccRCC: Von Hippel-Landau (vHL), Polybromo-1 (PBRM1), Breast Cancer Gene 1-Associated Protein 1 (BAP1), Histone-Lysine N-Methyltransferase Domain-Containing 2 (SETD2), Mammalian Target of Rapamycin (mTOR), and Lysine-Specific Demethylase 5C (KDM5C). …

Positive Airway Pressure And Mask Factors Affective Adherence In Patients With Obstructive Sleep Apnea, Rutvi Sheth, Michel Audette, Soham Sheth

Electrical & Computer Engineering Faculty Publications

Purpose: Sleep apnea is a major risk factor for cardiovascular disorders. CPAP (Continuous Positive Airway Pressure) therapy is the main treatment for sleep apnea. However, adherence with CPAP remains a concern. Although there are various factors attributed to failure of CPAP therapy, mask related factors are not well studied.

Methods: The study recruited patients with obstructive sleep apnea using CPAP from neurology outpatient clinic at Progressive Neurology and Sleep Center. An IRB (Institutional Review Board) approved questionnaire was administered to evaluate factors affecting CPAP compliance.

Results: The study recruited 24 patients. It showed that almost 50% of the patients did …

Adversarial Training Based Domain Adaptation Of Skin Cancer Images, Syed Qasim Gilani, Muhammad Umair, Maryam Naqvi, Oge Marques, Hee-Cheol Kim

Electrical & Computer Engineering Faculty Publications

Skin lesion datasets used in the research are highly imbalanced; Generative Adversarial Networks can generate synthetic skin lesion images to solve the class imbalance problem, but it can result in bias and domain shift. Domain shifts in skin lesion datasets can also occur if different instruments or imaging resolutions are used to capture skin lesion images. The deep learning models may not perform well in the presence of bias and domain shift in skin lesion datasets. This work presents a domain adaptation algorithm-based methodology for mitigating the effects of domain shift and bias in skin lesion datasets. Six experiments were …

Investigation Of The Effect Of Preparation Parameters On The Structural And Mechanical Properties Of Gelatin/Elastin/Sodium Hyaluronate Scaffolds Fabricated By The Combined Foaming And Freeze-Drying Techniques, Mansour Qamash, S. Misagh Imani, Meisam Omidi, Ciara Glancy, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

This paper aimed to evaluate the effects of different preparation parameters, including agitation speed, agitation time, and chilling temperature, on the structural and mechanical properties of a novel gelatin/elastin/sodium hyaluronate tissue engineering scaffold, recently developed by our research group. Fabricated using a combination of foaming and freeze-drying techniques, the scaffolds were assessed to understand how these parameters influence their morphology, internal microstructure, porosity, mechanical properties, and degradation behavior. The fabrication process used in this study involved preparing a homogeneous aqueous solution containing 8% gelatin, 2% elastin, and 0.5% sodium hyaluronate (w/v), which was then subjected to mechanical agitation at speeds …

Advancing Chronic Kidney Disease Prediction Through Machine Learning And Deep Learning With Feature Analysis, Shiddarth Dey Tusar, S. M. Ahad Ali Chowdhury, Md. Jalal Uddin Chowdhury, Rana M. Pir, H. M. Nur A. Alam, Muhammad Rezaur Rahman, Md. Nural Absar Siddiky, Muhammad Enayetur Rahman

Electrical & Computer Engineering Faculty Publications

Chronic Kidney Diesease (CKD) is a significant health issue, ranking as the fourth leading cause of mortality worldwide. The traditional diagnosis and treatment process, reliant on medical experts, is time-consuming. Therefore, thereis an urgent need for more efficient diagnostic methods to improve patient outcomes and reduce mortality rates. In this study, we employ Machine Learning (ML) and Deep Learning (DL) techniques to predict CKD based on important features. Feature analysis was performed using a correlation matrix and the LASSO algo-rithm to identify the most relevant features for model training. We evaluated several ML and DL classifiers, including Logistic Regression (LR), …

Integrated Machine Learning And Deep Learning Models For Cardiovascular Disease Risk Prediction: A Comprehensive Comparative Study, Shadman Mahmood Khan Pathan, Sakan Binte Imran

Electrical & Computer Engineering Faculty Publications

Cardiovascular Diseases (CVDs) pose a significant global health challenge, necessitating accurate risk prediction for effective preventive measures. This comprehensive comparative study explores the performance of traditional Machine Learning (ML) and Deep Learning (DL) models in predicting CVD risk, utilizing a meticulously curated dataset derived from health records. Rigorous preprocessing, including normalization and outlier removal, enhances model robustness. Diverse ML models (Logistic Regression, Random Forest, Support Vector Machine, K-Nearest Neighbor, Decision Tree, and Gradient Boosting) are compared with a Long Short-Term Memory (LSTM) neural network for DL. Evaluation metrics include accuracy, ROC AUC, computation time, and memory usage. Results identify the …

Ai And Ml-Based Risk Assessment Of Chemicals: Predicting Carcinogenic Risk From Chemical-Induced Genomic Instability, Ajay Vikram Singh, Preeti Bhardwaj, Peter Laux, Prachi Pradeep, Madleen Busse, Andreas Luch, Akihiko Hirose, Christopher J. Osgood, Michael W. Stacey

Biological Sciences Faculty Publications

Chemical risk assessment plays a pivotal role in safeguarding public health and environmental safety by evaluating the potential hazards and risks associated with chemical exposures. In recent years, the convergence of artificial intelligence (AI), machine learning (ML), and omics technologies has revolutionized the field of chemical risk assessment, offering new insights into toxicity mechanisms, predictive modeling, and risk management strategies. This perspective review explores the synergistic potential of AI/ML and omics in deciphering clastogen-induced genomic instability for carcinogenic risk prediction. We provide an overview of key findings, challenges, and opportunities in integrating AI/ML and omics technologies for chemical risk assessment, …

Image-To-Mesh Conversion Method For Multi-Tissue Medical Image Computing Simulations, Fotis Drakopoulos, Yixun Liu, Kevin Garner, Nikos Chrisochoides

Computer Science Faculty Publications

Converting a three-dimensional medical image into a 3D mesh that satisfies both the quality and fidelity constraints of predictive simulations and image-guided surgical procedures remains a critical problem. Presented is an image-to-mesh conversion method called CBC3D. It first discretizes a segmented image by generating an adaptive Body-Centered Cubic mesh of high-quality elements. Next, the tetrahedral mesh is converted into a mixed element mesh of tetrahedra, pentahedra, and hexahedra to decrease element count while maintaining quality. Finally, the mesh surfaces are deformed to their corresponding physical image boundaries, improving the mesh’s fidelity. The deformation scheme builds upon the ITK open-source library …

Enhancing Heart Disease Prediction With Reinforcement Learning And Data Augmentation, Gayathri R., Sangeetha S. K. B., Sandeep Kumar Mathivanan, Hariharan Rajadurai, Benjula Anbu Malar Mb, Saurav Mallik, Hong Qin

Computer Science Faculty Publications

The study presents a novel method to improve the prediction accuracy of cardiac disease by combining data augmentation techniques with reinforcement learning. The complex nature of cardiac data frequently presents challenges for traditional machine learning models, which results in subpar performance. In response, our fusion methodology improves predictive capabilities by augmenting data and utilizing reinforcement learning's skill at sequential decision-making. Our method predicts cardiac disease with an astounding 94 % accuracy rate, which is an outstanding result. This significant improvement outperforms existing techniques and shows a deeper comprehension of intricate data relationships. The amalgamation of reinforcement learning and data augmentation …

Enhanced Skin Cancer Diagnosis Through Grid Search Algorithm-Optimized Deep Learning Models For Skin Lesion Analysis, Rudresh Pillai, Neha Sharma, Sheifali Gupta, Deepali Gupta, Sapna Juneja, Saurav Malik, Hong Qin, Mohammed S. Alqahtani, Amel Ksibi

Computer Science Faculty Publications

Skin cancer is a widespread and perilous disease that necessitates prompt and precise detection for successful treatment. This research introduces a thorough method for identifying skin lesions by utilizing sophisticated deep learning (DL) techniques. The study utilizes three convolutional neural networks (CNNs)-CNN1, CNN2, and CNN3-each assigned to a distinct categorization job. Task 1 involves binary classification to determine whether skin lesions are present or absent. Task 2 involves distinguishing between benign and malignant lesions. Task 3 involves multiclass classification of skin lesion images to identify the precise type of skin lesion from a set of seven categories. The most optimal …

Elucidating Mechanisms Of Enhanced Dsrna-Nanophytoglycogen Innate Immune Responses In Healthy Human Cells, Nicholas Jadaa

Theses and Dissertations (Comprehensive)

Immunostimulatory nucleic acids, such as long double-stranded RNA (ds)RNA, can stimulate innate immune responses in a non-sequence specific manner. These molecules are recognized by pattern-recognition receptors in the cytoplasm, endosome, and on the cell surface. Activation leads to the production of mediators of innate immune pathways, including type I interferon and proinflammatory cytokines. Although these receptors are present in all cells, their role in non-immune cells is often overlooked due to their lower level of responsiveness. Nanocarriers can enhance these nucleic acid-mediated responses, allowing for exploration of innate immune pathways in non-immune cells. Nanoparticles as carriers of nucleic acids can …

Implementing Best Practice Methods Of Endotracheal Tube Cuff Inflation In The Operating Room, Katherine Zeiger Brown

Graduate Theses, Dissertations, and Problem Reports (ETD)

Background: Use of manometers, inflating the endotracheal tube (ETT) cuff with a 5-mL syringe, displaying the pressure-volume loop (PV-L) on anesthesia machines, and auscultating with a stethoscope over the trachea have been shown effective in preventing ETT cuff overinflation in the operating room (OR). Purpose: The aims of this project were to implement and evaluate a best practice guideline for ETT cuff inflation in the OR. Methods: This project was conducted in several ORs at J.W. Ruby Memorial Hospital, in Morgantown, West Virginia. Participants included anesthesiologists, certified registered nurse anesthetists (CRNAs), student registered nurse anesthetists, residents, and medics. The ETT …

Improving Awareness And Identifying Risks For Emergence Delirium In Military Veterans, Hannah E. Pino

Graduate Theses, Dissertations, and Problem Reports (ETD)

Background: Emergence delirium (ED) is an acute state of confusion during the recovery phase from anesthesia that may be life-threatening, especially in the veteran population. Military veteran status may be explored by the Have You Ever Served questionnaire that was developed by the American Academy of Nursing to identify veterans upon admission to the hospital and thus be able to better care for them during their stay. This campaign has been in effect at the hospital site of this project for nearly 10 years. The questionnaire identifies military history risk factors such as combat history or a diagnosis of post-traumatic …