Medicine and Health Sciences Commons^™

Heavy Metals In Afforested Mangrove Sediment From The World's Largest Delta: Distributional Mapping, Contamination Status, Risk Assessment And Source Tracing, Md Saifur Rahman, Moshiur Rahman, Yeasmin N Jolly, Md Kamal Hossain, Sanjida Afrin Semme, Bilal Ahamad Paray, Takaomi Arai, Jimmy Yu, M Belal Hossain

Journal Articles

This study aims to assess seasonal and spatial variations, contamination status, ecological risks, and metal sources (Ni, Pb, Cr, Cu, Mn, and Zn) in human-afforested mangrove sediments in a deltaic region. Five sampling locations were sampled during dry and wet seasons. Heavy metal concentrations followed the order: Mn > Zn > Ni > Cr > Cu > Pb. Metal loads, except Cu and Pb, were higher during the dry season, aligning with national and international recommendations. Sediment quality guidelines, contamination factor, geoaccumulation index, enrichment factors, and pollution load index indicated uncontaminated sediment in both seasons. Potential ecological risk assessment showed low risk conditions in all …

Evaluation Of An End-To-End Radiotherapy Treatment Planning Pipeline For Prostate Cancer, Mohammad Daniel El Basha, Court Laurence, Carlos Eduardo Cardenas, Julianne Pollard-Larkin, Steven Frank, David T. Fuentes, Falk Poenisch, Zhiqian H. Yu

Dissertations & Theses (Open Access)

Radiation treatment planning is a crucial and time-intensive process in radiation therapy. This planning involves carefully designing a treatment regimen tailored to a patient’s specific condition, including the type, location, and size of the tumor with reference to surrounding healthy tissues. For prostate cancer, this tumor may be either local, locally advanced with extracapsular involvement, or extend into the pelvic lymph node chain. Automating essential parts of this process would allow for the rapid development of effective treatment plans and better plan optimization to enhance tumor control for better outcomes.

The first objective of this work, to automate the treatment …

Proof-Of-Concept For Converging Beam Small Animal Irradiator, Benjamin Insley

Dissertations & Theses (Open Access)

The Monte Carlo particle simulator TOPAS, the multiphysics solver COMSOL., and

several analytical radiation transport methods were employed to perform an in-depth proof-ofconcept

for a high dose rate, high precision converging beam small animal irradiation platform.

In the first aim of this work, a novel carbon nanotube-based compact X-ray tube optimized for

high output and high directionality was designed and characterized. In the second aim, an

optimization algorithm was developed to customize a collimator geometry for this unique Xray

source to simultaneously maximize the irradiator’s intensity and precision. Then, a full

converging beam irradiator apparatus was fit with a multitude …

Artificial Intelligence Model Predicts Sudden Cardiac Arrest Manifesting With Pulseless Electric Activity Versus Ventricular Fibrillation, Lauri Holmstrom, Bryan Bednarski, Harpriya Chugh, Habiba Aziz, Hoang Nhat Pham, Arayik Sargsyan, Audrey Uy-Evanado, Damini Dey, Angelo Salvucci, Jonathan Jui, Kyndaron Reinier, Piotr J Slomka, Sumeet S Chugh

Journal Articles

BACKGROUND: There is no specific treatment for sudden cardiac arrest (SCA) manifesting as pulseless electric activity (PEA) and survival rates are low; unlike ventricular fibrillation (VF), which is treatable by defibrillation. Development of novel treatments requires fundamental clinical studies, but access to the true initial rhythm has been a limiting factor.

METHODS: Using demographics and detailed clinical variables, we trained and tested an AI model (extreme gradient boosting) to differentiate PEA-SCA versus VF-SCA in a novel setting that provided the true initial rhythm. A subgroup of SCAs are witnessed by emergency medical services personnel, and because the response time is …

Significant Improvement Of Fidelity For Encoded Quantum Bell Pairs At Long And Short-Distance Communication Along With Generalized Circuit, Syed Emad Uddin Shubha, Md Saifur Rahman, M R C Mahdy

Journal Articles

Quantum entanglement is a unique criterion of the quantum realm and an essential tool to secure quantum communication. Ensuring high-fidelity entanglement has always been a challenging task owing to interaction with the hostile channel environment created due to quantum noise and decoherence. Though several methods have been proposed, correcting almost all arbitrary errors is still a gigantic task. As one of the main contributions of this work, a new model for 'large distance communication' has been proposed, which may correct all bit flip errors or other errors quite extensively if proper encoding and subspace measurements are used. To achieve this …

The Development Of Artificial Intelligence-Based Tools For Expert Peer Review Of Radiotherapy Treatment Plans, Mary Gronberg

Dissertations & Theses (Open Access)

Creating a patient-specific radiation treatment plan is a time-consuming and operator-dependent manual process. The treatment planner adjusts the planning parameters in a trial-and-error fashion in an effort to balance the competing clinical objectives of tumor coverage and normal tissue sparing. Often, a plan is selected because it meets basic organ at risk dose thresholds for severe toxicity; however, it is evident that a plan with a decreased risk of normal tissue complication probability could be achieved. This discrepancy between “acceptable” and “best possible” plan is magnified if either the physician or treatment planner lacks focal expertise in the disease site. …

Artificial Intelligence Cad Tools In Trauma Imaging: A Scoping Review From The American Society Of Emergency Radiology (Aser) Ai/Ml Expert Panel., David Dreizin, Pedro V Staziaki, Garvit D Khatri, Nicholas M Beckmann, Zhaoyong Feng, Yuanyuan Liang, Zachary S Delproposto, Maximiliano Klug, J Stephen Spann, Nathan Sarkar, Yunting Fu

Journal Articles

BACKGROUND: AI/ML CAD tools can potentially improve outcomes in the high-stakes, high-volume model of trauma radiology. No prior scoping review has been undertaken to comprehensively assess tools in this subspecialty.

PURPOSE: To map the evolution and current state of trauma radiology CAD tools along key dimensions of technology readiness.

METHODS: Following a search of databases, abstract screening, and full-text document review, CAD tool maturity was charted using elements of data curation, performance validation, outcomes research, explainability, user acceptance, and funding patterns. Descriptive statistics were used to illustrate key trends.

RESULTS: A total of 4052 records were screened, and 233 full-text …

Rapid Assessment Of Fish Freshness For Multiple Supply-Chain Nodes Using Multi-Mode Spectroscopy And Fusion-Based Artificial Intelligence, Hossein Kashani Zadeh, Mike Hardy, Mitchell Sueker, Yicong Li, Angelis Tzouchas, Nicholas Mackinnon, Gregory Bearman, Simon A Haughey, Alireza Akhbardeh, Insuck Baek, Chansong Hwang, Jianwei Qin, Amanda M Tabb, Rosalee S Hellberg, Shereen Ismail, Hassan Reza, Fartash Vasefi, Moon Kim, Kouhyar Tavakolian, Christopher T Elliott

Journal Articles

This study is directed towards developing a fast, non-destructive, and easy-to-use handheld multimode spectroscopic system for fish quality assessment. We apply data fusion of visible near infra-red (VIS-NIR) and short wave infra-red (SWIR) reflectance and fluorescence (FL) spectroscopy data features to classify fish from fresh to spoiled condition. Farmed Atlantic and wild coho and chinook salmon and sablefish fillets were measured. Three hundred measurement points on each of four fillets were taken every two days over 14 days for a total of 8400 measurements for each spectral mode. Multiple machine learning techniques including principal component analysis, self-organized maps, linear and …

Treatment Planning Automation For Rectal Cancer Radiotherapy, Kai Huang

Dissertations & Theses (Open Access)

Background

Rectal cancer is a common type of cancer. There is an acute health disparity across the globe where a significant population of the world lack adequate access to radiotherapy treatments which is a part of the standard of care for rectal cancers. Safe radiotherapy treatments require specialized planning expertise and are time-consuming and labor-intensive to produce.

Purpose:

To alleviate the health disparity and promote the safe and quality use of radiotherapy in treating rectal cancers, the entire treatment planning process needs to be automated. The purpose of this project is to develop automated solutions for the treatment planning process …

Multiparametric Magnetic Resonance Imaging Artificial Intelligence Pipeline For Oropharyngeal Cancer Radiotherapy Treatment Guidance, Kareem Wahid

Dissertations & Theses (Open Access)

Oropharyngeal cancer (OPC) is a widespread disease and one of the few domestic cancers that is rising in incidence. Radiographic images are crucial for assessment of OPC and aid in radiotherapy (RT) treatment. However, RT planning with conventional imaging approaches requires operator-dependent tumor segmentation, which is the primary source of treatment error. Further, OPC expresses differential tumor/node mid-RT response (rapid response) rates, resulting in significant differences between planned and delivered RT dose. Finally, clinical outcomes for OPC patients can also be variable, which warrants the investigation of prognostic models. Multiparametric MRI (mpMRI) techniques that incorporate simultaneous anatomical and functional information …

The Safe And Effective Clinical Deployment Of Artificial Intelligence Tools, Kelly Nealon

Dissertations & Theses (Open Access)

18 million new cancer cases are diagnosed each year. Roughly half of these patients will be treated with radiation therapy, a complex technique that requires an interdisciplinary team of clinical staff and expensive equipment to be delivered safely. Cancer centers in Low- and Middle-Income Countries (LMIC) have an especially difficult time meeting the demands of radiation therapy as the complexity of treatment techniques increase, with only 37% of patients in these regions having access to the care they need. Artificial Intelligence (AI) based tools are being developed to simplify the treatment planning and quality assurance processes to increase the number …

Automating The Radiation Therapy Treatment Planning Process For Pediatric Patients With Medulloblastoma, Soleil Hernandez

Dissertations & Theses (Open Access)

Over the past 50 years, pediatric cancer 5-year survival rates increased from 20% to 80% in high-income countries, however, these trends have not been mirrored in low-and-middle-income countries (LMICs). This is due in part to delayed diagnosis, higher rates of advanced disease at presentation and a growing lack of access to high quality medical personnel and technology necessary to deliver complex treatments.

The long-term goal of this study was to alleviate demanding workflows and increase global access to high-quality pediatric radiation therapy by harnessing the power of artificial intelligence to automate the radiation therapy treatment planning process for pediatric patients …

Lessons Learned From Interdisciplinary Efforts To Combat Covid-19 Misinformation: Development Of Agile Integrative Methods From Behavioral Science, Data Science, And Implementation Science, Sahiti Myneni, Paula Cuccaro, Sarah Montgomery, Vivek Pakanati, Jinni Tang, Tavleen Singh, Olivia Dominguez, Trevor Cohen, Belinda Reininger, Lara S Savas, Maria E Fernandez

Journal Articles

BACKGROUND: Despite increasing awareness about and advances in addressing social media misinformation, the free flow of false COVID-19 information has continued, affecting individuals' preventive behaviors, including masking, testing, and vaccine uptake.

OBJECTIVE: In this paper, we describe our multidisciplinary efforts with a specific focus on methods to (1) gather community needs, (2) develop interventions, and (3) conduct large-scale agile and rapid community assessments to examine and combat COVID-19 misinformation.

METHODS: We used the Intervention Mapping framework to perform community needs assessment and develop theory-informed interventions. To supplement these rapid and responsive efforts through large-scale online social listening, we developed a …

Quantifying The Magnitude Of Total Dose Deviation Caused By Various Sources Of Error Among Iroc Phantom Irradiation Results, Sharbacha S. Edward

Dissertations & Theses (Open Access)

The Imaging and Radiation Oncology Core (IROC) phantoms are used as an end-to-end test of an institution’s radiotherapy processes, and for clinical trial credentialing. Phantoms are treated like patients, and evaluation of the doses received by the thermoluminescent dosimeters (TLDs) inside the phantom, reflects the accuracy with which an institution can image, plan and irradiate a phantom or patient. Recent phantom results show that among the hundreds of various IROC phantoms irradiated annually, 8-17% of institutions fail this test. The purpose of this work was to investigate the various types of errors that may occur during the treatment process and …

A Novel Qkd Approach To Enhance Iiot Privacy And Computational Knacks, Kranthi Kumar Singamaneni, Gaurav Dhiman, Sapna Juneja, Ghulam Muhammad, Salman A Alqahtani, John Zaki

Journal Articles

The industry-based internet of things (IIoT) describes how IIoT devices enhance and extend their capabilities for production amenities, security, and efficacy. IIoT establishes an enterprise-to-enterprise setup that means industries have several factories and manufacturing units that are dependent on other sectors for their services and products. In this context, individual industries need to share their information with other external sectors in a shared environment which may not be secure. The capability to examine and inspect such large-scale information and perform analytical protection over the large volumes of personal and organizational information demands authentication and confidentiality so that the total data …

Generalization In Quantum Machine Learning From Few Training Data, Matthias C Caro, Hsin-Yuan Huang, M Cerezo, Kunal Sharma, Andrew Sornborger, Lukasz Cincio, Patrick J Coles

Journal Articles

Modern quantum machine learning (QML) methods involve variationally optimizing a parameterized quantum circuit on a training data set, and subsequently making predictions on a testing data set (i.e., generalizing). In this work, we provide a comprehensive study of generalization performance in QML after training on a limited number N of training data points. We show that the generalization error of a quantum machine learning model with T trainable gates scales at worst as [Formula: see text]. When only K ≪ T gates have undergone substantial change in the optimization process, we prove that the generalization error improves to [Formula: see …

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

Dissertations & 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 …

Development Of Graphical Models And Statistical Physics Motivated Approaches To Genomic Investigations, Yashwanth Lagisetty

Dissertations & Theses (Open Access)

Identifying genes involved in disease pathology has been a goal of genomic research since the early days of the field. However, as technology improves and the body of research grows, we are faced with more questions than answers. Among these is the pressing matter of our incomplete understanding of the genetic underpinnings of complex diseases. Many hypotheses offer explanations as to why direct and independent analyses of variants, as done in genome-wide association studies (GWAS), may not fully elucidate disease genetics. These range from pointing out flaws in statistical testing to invoking the complex dynamics of epigenetic processes. In the …

Leveraging Single Cell Technologies For The Characterization And Treatment Of Refractory Pancreatic Cancer, Maria Monberg

Dissertations & Theses (Open Access)

Heterogeneity is a hallmark of cancer, and the advent of multimodal single-cell technologies has helped uncover heterogeneity in a high-throughput manner in different cancers across varied contexts at an unprecedented resolution. In an effort to improve precision medicine approaches in pancreatic ductal adenocarcinoma (PDAC), a highly lethal malignancy with a mere 11% 5-year survival rate, this dissertation focuses on first questioning the assumptions of the most basic models used to study PDAC via multimodal single-cell characterization methods at multiple levels of biological organization (scCNVseq and snATACseq for DNA assays, scRNAseq for transcriptomics, and paired protein assays such as multiplexed immunofluorescence …

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

Dissertations & 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 …

Modeling Of Cns Cancer With A Focus On The Immune Component, Daniel Zamler

Dissertations & Theses (Open Access)

The knowledge surrounding cancers of the central nervous system remains poorly developed, in particular with regard to the immune component. The works contained in this thesis look at craniopharyngioma, glioblastoma, and several forms of brain metastasis. While some attention is given to the tumor cells themselves, as well as the patient setting which these studies model, the immune component of disease progression and treatment plays a strong role in each and is the primary focus of the works contained.

Craniopharyngioma is a relatively rare tumor in adults. Although histologically benign, it can be locally aggressive and may require additional therapeutic …

The Importance Of Dna Repair Capacity To (And A Model To Predict) Cell Radiosensitivity To Ions, David B. Flint, David B. Flint

Dissertations & Theses (Open Access)

Radiation therapy with ions has a number of advantages over conventional radiation therapy with photons, including favorable depth-dose distributions, greater relative biological effectiveness (RBE) and a lesser dependence on a number of biological factors known to affect radiosensitivity to photons, including DNA repair capacity. Thus, it is expected that an additional benefit of using ions is that they mitigate the great heterogeneities in treatment responses commonly observed in photon therapies.

However, by analyzing the cell survival of human cancer cell lines exposed to clinically relevant photon, proton, and carbon ion beams, we show there is not significantly less relative variability …

Advancement Of A 3d Computational Phantom And Its Age Scaling Methodologies For Retrospective Dose Reconstruction Studies, Aashish Gupta

Dissertations & Theses (Open Access)

We have used a 3D age-scalable computational phantom for over two decades for retrospective dose reconstruction studies of childhood cancer survivors (CCS) treated with 2D historic radiotherapy (RT). However, our phantom and its age scaling functions (ASF) must be updated so that it can be used in studies that include survivors treated with contemporary RT. We aimed to implement our phantom and its age scaling functions in DICOM format and determine the feasibility of applying our ASFs to accurately scale the whole-body CT-based anatomies.

In the implementation study, we developed Python scripts that model the phantom and ASFs in a …

Automation Of Radiation Treatment Planning For Cervical Cancer, Dong Joo Rhee

Dissertations & Theses (Open Access)

Cervical cancer is one of the most common cancer in low- and middle-income countries (LMICs). The mortality rate can be reduced if radiation treatment becomes widely available. However, due to the lack of radiation treatment facilities and human resources, many cervical cancer patients in Africa are not able to receive timely treatments or advanced therapies. To increase the availability of radiation treatment in low-and middle-income countries (LMICs) including African countries, many attempts have been made to reduce the cost of medical linear accelerators. However, increasing the number of treatment machines would not instantly resolve the issues, as there would be …

Identification And Characterization Of De Novo Germline Tp53 Mutation Carriers In Families With Li-Fraumeni Syndrome, Carlos C. Vera Recio

Dissertations & Theses (Open Access)

Li-Fraumeni syndrome (LFS) is an inherited cancer syndrome caused by a deleterious mutation in TP53. An estimated 48% of LFS patients present due to a de novo mutation (DNM) in TP53. The knowledge of DNM status, DNM or familial mutation (FM), of an LFS patient requires genetic testing of both parents which is often inaccessible, making de novo LFS patients difficult to study. Famdenovo.TP53 is a Mendelian Risk prediction model used to predict DNM status of TP53 mutation carriers based on the cancer-family history and several input genetic parameters, including disease-gene penetrance. The good predictive performance of Famdenovo.TP53 was demonstrated …

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

Dissertations & 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 …

Biases And Blind-Spots In Genome-Wide Crispr-Cas9 Knockout Screens, Merve Dede

Dissertations & Theses (Open Access)

Adaptation of the bacterial CRISPR-Cas9 system to mammalian cells revolutionized the field of functional genomics, enabling genome-scale genetic perturbations to study essential genes, whose loss of function results in a severe fitness defect. There are two types of essential genes in a cell. Core essential genes are absolutely required for growth and proliferation in every cell type. On the other hand, context-dependent essential genes become essential in an environmental or genetic context. The concept of context-dependent gene essentiality is particularly important in cancer, since killing cancer cells selectively without harming surrounding healthy tissue remains a major challenge. The toxicity of …

A Fully-Automated, Deep Learning-Based Framework For Ct-Based Localization, Segmentation, Verification And Planning Of Metastatic Vertebrae, Tucker Netherton, Tucker James Netherton

Dissertations & Theses (Open Access)

Palliative radiotherapy is an effective treatment for the palliation of symptoms caused by vertebral metastases. Visible evidence of disease is localized on medical images as part of the treatment planning process. However, complicating factors such as time pressures, anatomic variants in the spine, and similarities in adjacent vertebrae are associated with wrong level treatments of the spine. In addition, erroneous manual contouring of anatomic structures is a major failure mode in radiotherapy treatment planning.

The purpose of this study is to mitigate the challenges associated with treatment planning of the spine by automating the treatment planning process for three-dimensional conformal …

Development Of Quantitative Ultrasound-Mediated Molecular Imaging Of The Tumor Microenvironment, Trevor Mitcham

Dissertations & Theses (Open Access)

While conventional diagnostic imaging modalities provide anatomical information to clinicians, these techniques are not sensitive to critical physiological processes. In order to properly classify cancer, it is necessary to investigate noninvasive methods which can provide insight into these processes, allowing clinicians to determine personalized therapeutic options. Therefore, molecular imaging is focused on visualization and characterization of biomarkers within the tumor microenvironment (TME), which can then be combined with the anatomical information provided from diagnostic imaging.

Two such biomarkers of interest are blood oxygen saturation (SO₂) and cell receptor expression. SO₂ is a measure of the fraction of …

Cortical Dynamics Of Language, Kiefer Forseth

Dissertations & Theses (Open Access)

The human capability for fluent speech profoundly directs inter-personal communication and, by extension, self-expression. Language is lost in millions of people each year due to trauma, stroke, neurodegeneration, and neoplasms with devastating impact to social interaction and quality of life. The following investigations were designed to elucidate the neurobiological foundation of speech production, building towards a universal cognitive model of language in the brain. Understanding the dynamical mechanisms supporting cortical network behavior will significantly advance the understanding of how both focal and disconnection injuries yield neurological deficits, informing the development of therapeutic approaches.