Biomedical Engineering and Bioengineering Commons^™

Identification And Characterization Of Two Novel Kcnh2 Mutations Contributing To Long Qt Syndrome, Anthony Owusu-Mensah, Jacqueline Treat, Joyce Bernardi, Ryan Pfeiffer, Robert Goodrow, Bright Tsevi, Victoria Lam, Michel Audette, Jonathan M. Cordeiro, Makarand Deo

Electrical & Computer Engineering Faculty Publications

We identified two different inherited mutations in KCNH2 gene, or human ether-a-go-go related gene (hERG), which are linked to Long QT Syndrome. The first mutation was in a 1-day-old infant, whereas the second was in a 14-year-old girl. The two KCNH2 mutations were transiently transfected into either human embryonic kidney (HEK) cells or human induced pluripotent stem-cell derived cardiomyocytes. We performed associated multiscale computer simulations to elucidate the arrhythmogenic potentials of the KCNH2 mutations. Genetic screening of the first and second index patients revealed a heterozygous missense mutation in KCNH2, resulting in an amino acid change (P632L) in the …

Cad System For Early Diagnosis Of Diabetic Retinopathy Based On 3d Extracted Imaging Markers., Ahmed Sleman

Electronic Theses and Dissertations

This dissertation makes significant contributions to the field of ophthalmology, addressing the segmentation of retinal layers and the diagnosis of diabetic retinopathy (DR). The first contribution is a novel 3D segmentation approach that leverages the patientspecific anatomy of retinal layers. This approach demonstrates superior accuracy in segmenting all retinal layers from a 3D retinal image compared to current state-of-the-art methods. It also offers enhanced speed, enabling potential clinical applications. The proposed segmentation approach holds great potential for supporting surgical planning and guidance in retinal procedures such as retinal detachment repair or macular hole closure. Surgeons can benefit from the accurate …

Prepubertal Periodontitis In Children: For An Adequate Diagnosis And Optimal Care, F.Z. El Mouatarif, S. Chemlali, M. Hamza, J. Kissa, S. El Arabi

Health Sciences

Prepubertal periodontitis (PP) is a rare and rapid progressive condition found a young cohort of patients that results in destruction of the periodontal support of the primary dentition. Its generalized form, prepubertal periodontitis is often associated with a significant gingival tissue inflammation and fast bone loss with attachment loss leading to the tooth loss. The localized form of PP is characterized by a much more discreet inflammation and slow evolution. It can be associated with a known underlying systemic disease or may occur as part of a recognized syndrome or as an isolated finding. Different treatment modalities can be used …

Focused Ultrasound-Enabled Blood-Based Liquid Biopsy (Sonobiopsy) For Brain Disease Diagnosis, Christopher Pham Pacia

McKelvey School of Engineering Theses & Dissertations

Brain cancer severely threatens human health due to its disruption of neurological function, poor prognosis, and substantial reduction in quality of life. Glioblastoma (GBM) is the most devastating brain cancer; not only is it the most common malignant primary tumor in adults, but also it has a median survival of 14 months with a 5-year survival rate of less than 5%. Despite advances in multidisciplinary treatment that includes surgical resection, radiation therapy, and chemotherapy, almost all patients experience tumor progression and nearly universal mortality within 2 years. However, advances in patient care have suggested that the accurate diagnosis of molecular …

Role Of Machine Learning In Early Diagnosis Of Kidney Diseases., Mohamed Nazih Mohamed Ibrahim Shehata

Electronic Theses and Dissertations

Machine learning (ML) and deep learning (DL) approaches have been used as indispensable tools in modern artificial intelligence-based computer-aided diagnostic (AIbased CAD) systems that can provide non-invasive, early, and accurate diagnosis of a given medical condition. These AI-based CAD systems have proven themselves to be reproducible and have the generalization ability to diagnose new unseen cases with several diseases and medical conditions in different organs (e.g., kidneys, prostate, brain, liver, lung, breast, and bladder). In this dissertation, we will focus on the role of such AI-based CAD systems in early diagnosis of two kidney diseases, namely: acute rejection (AR) post …

An Ensemble Approach For Patient Prognosis Of Head And Neck Tumor Using Multimodal Data, Numan Saeed, Roba Al Majzoub, Ikboljon Sobirov, Mohammad Yaqub

Computer Vision Faculty Publications

Accurate prognosis of a tumor can help doctors provide a proper course of treatment and, therefore, save the lives of many. Tradi-tional machine learning algorithms have been eminently useful in crafting prognostic models in the last few decades. Recently, deep learning algorithms have shown significant improvement when developing diag-nosis and prognosis solutions to different healthcare problems. However, most of these solutions rely solely on either imaging or clinical data. Utilizing patient tabular data such as demographics and patient med-ical history alongside imaging data in a multimodal approach to solve a prognosis task has started to gain more interest recently and …

Neuromotor Changes In Participants With A Concussion History Can Be Detected With A Custom Smartphone App, Christopher K. Rhea, Masahiro Yamada, Nikita A. Kuznetsov, Jason T. Jakiela, Chanel T. Lojacono, Scott E. Ross, F. J. Haran, Jason M. Bailie, W. Geoffrey Wright

Rehabilitation Sciences Faculty Publications

Neuromotor dysfunction after a concussion is common, but balance tests used to assess neuromotor dysfunction are typically subjective. Current objective balance tests are either cost- or space-prohibitive, or utilize a static balance protocol, which may mask neuromotor dysfunction due to the simplicity of the task. To address this gap, our team developed an Android-based smartphone app (portable and cost-effective) that uses the sensors in the device (objective) to record movement profiles during a stepping-in-place task (dynamic movement). The purpose of this study was to examine the extent to which our custom smartphone app and protocol could discriminate neuromotor behavior between …

3d Printing In Cardiology: A Review Of Applications And Roles For Advanced Cardiac Imaging, Ellen M. Lindquist, Jordan M. Gosnell, Sana K. Khan, John L. Byl, Weihua Zhou, Jingfeng Jiang, Et. Al.

Michigan Tech Publications

With the rate of cardiovascular diseases in the U.S increasing throughout the years, there is a need for developing more advanced treatment plans that can be tailored to specific patients and scenarios. The development of 3D printing is rapidly gaining acceptance into clinical cardiology.

In this review, key technologies used in 3D printing are briefly summarized, particularly, the use of artificial intelligence (AI), open-source tools like MeshLab and MeshMixer, and 3D printing techniques such as fused deposition molding (FDM) and polyjet are reviewed. The combination of 3D printing, multiple image integration, and augmented reality may greatly enhance data visualization …

A Simple, Realistic Walled Phantom For Intravascular And Intracardiac Applications., Hareem Nisar, John Moore, Roberta Piazza, Efthymios Maneas, Elvis C S Chen, Terry M Peters

Robarts Imaging Publications

PURPOSE: This work aims to develop a simple, anatomically and haptically realistic vascular phantom, compatible with intravascular and intracardiac ultrasound. The low-cost, dual-layered phantom bridges the gap between traditional wall-only and wall-less phantoms by showing both the vessel wall and surrounding tissue in ultrasound imaging. This phantom can better assist clinical tool training, testing of intravascular devices, blood flow studies, and validation of algorithms for intravascular and intracardiac surgical systems.

METHODS: Polyvinyl alcohol cryogel (PVA-c) incorporating a scattering agent was used to obtain vessel and tissue-mimicking materials. Our specific design targeted the inferior vena cava and renal bifurcations which were …

Spatial Heterogeneity Utilization In Ct Images For Lung Nodule Classication, Dmitrii Cherezov

USF Tampa Graduate Theses and Dissertations

Lung cancer (LC) is leading in the number of deaths among the other types of cancer. According to the American Cancer Society, 135,720 deaths during 2020 in the USA will be associated with LC. The patient 5-year survival rate of 16\% was reported in 1986 and 19% in 2019. One of the reasons why survival rate remains low is that the majority of patients diagnosed with cancer had stages III and IV. In contrast, a 5-year survival rate of 70% was reported for patients of stage IA after surgical resection in the National Lung Screening Trial.

CT screening detects a …

Optical Coherence Tomography Application To Alopecia In The Scalp, Elizabeth Melcher

Research Opportunities for Engineering Undergraduates (ROEU) Program 2017-18

Alopecia is the loss of hair, whether it be from the scalp or other regions of the body. Current techniques used to best diagnose and track alopecia are often invasive, requiring a biopsy for results. The use of the OCT, or optical coherence tomography, could drastically improve a patient’s experience in undergoing a diagnosis while proving accurate results. The objective of this study is to develop diagnostic algorithms for the rapid, non-invasive diagnosis of alopecia with OCT. The first step is collecting OCT images of a healthy scalp to understand the anatomical structures with the imaging technique.

Pediatric Leukemia: Diagnosis To Treatment–A Review, Samantha C. Bernard, Ehab H. Abdelsamad, Paisley A. Johnson, Daniel L. Chapman, Madhukiran Parvathaneni

Faculty Works

Leukemia is cancer of the blood and bone marrow, it is the most common cancer found in children and is found to be more than one fourth of pediatric cancers. It causes white blood cells to become abnormal and the body to become weak. This deficiency in the immune system reduces the body's ability to fight infection or simple airborne illnesses, causing extensive treatment of common pathogens and cancer treatment. The present review covers all topics, from diagnosis to treatment of pediatric leukemia, as well as the stages of growth and physiological changes throughout the process. As leukemia has a …

Early Assessment Of Burn Severity In Human Tissue With Multi-Wavelength Spatial Frequency Domain Imaging, Chien Sing Poon

Browse all Theses and Dissertations

Burn injuries such as thermal burns, which are caused by contact with flames, hot liquids, hot surfaces, and other sources of high heat as well as chemical burns and electrical burns, affects at least 500,000 people in the United States, to which 45,000 of them require medical treatment and 3,500 of them result in death. It has also been reported that in the United States alone, fire results in a death approximately every three hours and an injury every 33 minutes. Early knowledge about burn severity can lead to improved outcome for patients. In this study, the changes in optical …

Probabilistic Ensemble Fuzzy Artmap Optimization Using Hierarchical Parallel Genetic Algorithms

Faculty of Engineering University of Malaya

In this study, a comprehensive methodology for overcoming the design problem of the Fuzzy ARTMAP neural network is proposed. The issues addressed are the sequence of training data for supervised learning and optimum parameter tuning for parameters such as baseline vigilance. A genetic algorithm search heuristic was chosen to solve this multi-objective optimization problem. To further augment the ARTMAP's pattern classification ability, multiple ARTMAPs were optimized via genetic algorithm and assembled into a classifier ensemble. An optimal ensemble was realized by the inter-classifier diversity of its constituents. This was achieved by mitigating convergence in the genetic algorithms by employing a …

Affect Classification Using Genetic-Optimized Ensembles Of Fuzzy Artmaps

Faculty of Engineering University of Malaya

Training neural networks in distinguishing different emotions from physiological signals frequently involves fuzzy definitions of each affective state. In addition, manual design of classification tasks often uses sub-optimum classifier parameter settings, leading to average classification performance. In this study, an attempt to create a framework for multi-layered optimization of an ensemble of classifiers to maximize the system's ability to learn and classify affect, and to minimize human involvement in setting optimum parameters for the classification system is proposed. Using fuzzy adaptive resonance theory mapping (ARTMAP) as the classifier template, genetic algorithms (GAs) were employed to perform exhaustive search for the …

Scanning In Situ Spectroscopy Pplatform For Imaging Surgical Breast Tissue Specimens, Venkataramanan Krishnaswamy, Ashley M. Laughney, Wendy A. Wells, Keith D. Paulsen, Brian W. Pogue

Dartmouth Scholarship

A non-contact localized spectroscopic imaging platform has been developed and optimized to scan 1 x 1 cm² square regions of surgically resected breast tissue specimens with ~150-micron resolution. A color corrected, image-space telecentric scanning design maintained a consistent sampling geometry and uniform spot size across the entire imaging field. Theoretical modeling in ZEMAX allowed estimation of the spot size, which is equal at both the center and extreme positions of the field with ~5% variation across the designed waveband, indicating excellent color correction. The spot sizes at the center and an extreme field position were also measured experimentally using the …

Automated Point-Of-Care Image Processing Methodology For The Diagnosis Of Malaria, Michael B. Jorgensen

Master's Theses

Malaria has profoundly influenced human history for over four thousand years and despite numerous attempts at eradication, the prevention, diagnosis, and treatment of malaria have been largely ineffective. More than five hundred million people are affected by malaria every year resulting in over one million deaths. Drug resistance development by the parasite has diminished the effectiveness of numerous treatment options due, in part, to overtreatment of negative patients based on insufficient clinical algorithms and diagnostic methods. The goal of this research was to develop an image analysis algorithm to diagnose malaria with a high degree of sensitivity and specificity in …

Diagnosis Of Systemic Inflammation Using Transendothelial Electrical Resistance And Low-Temperature Co-Fired Ceramic Materials, William L. Mercke

Theses and Dissertations--Chemical and Materials Engineering

Systemic inflammation involves a complex array of cytokines that can result in organ dysfunction. Mortality remains high despite the vast amount of research conducted to find an effective biomarker. The cause of systemic inflammation can be broad and non-specific; therefore, this research investigates using transendothelial electrical resistance (TEER) measurements to better define systemic inflammatory response syndrome (SIRS)/sepsis within a patient. Results show a difference in TEER measurements between healthy individuals and SIRS-rated patients. This research also displays correlations between TEER measurements and biomarkers currently studied with systemic inflammation (tumor necrosis factor-α, C- reactive protein, procalcitonin). Furthermore, this research also presents …

A Dna Computer For Glioblastoma Multiforme Diagnosis And Drug Delivery, Sumaiya F. Hashmi

CMC Senior Theses

Glioblastoma multiforme (GBM) is a debilitating malignant brain tumor with expected patient survival of less than a year and limited responsiveness to most treatments, often requiring biopsy for diagnosis and invasive surgery for treatment. We propose a DNA computer system, consisting of input, computation, and output components, for diagnosis and treatment. The input component will detect the presence of three GBM biomarkers: vascular endothelial growth factor (VEGF), caveolin-1α (CAV), and B2 receptors. The computation component will include indicator segments for each of these genes, and ensure that output is only released if all the biomarkers are present. The output component …

Quantitative, Spectrally-Resolved Intraoperative Fluorescence Imaging, Pablo A. Valdés, Frederic Leblond, Valerie L. Jacobs, Brian C. Wilson, Keith D. Paulsen, David W. Roberts

Dartmouth Scholarship

Intraoperative visual fluorescence imaging (vFI) has emerged as a promising aid to surgical guidance, but does not fully exploit the potential of the fluorescent agents that are currently available. Here, we introduce a quantitative fluorescence imaging (qFI) approach that converts spectrally-resolved data into images of absolute fluorophore concentration pixel-by-pixel across the surgical field of view (FOV). The resulting estimates are linear, accurate, and precise relative to true values, and spectral decomposition of multiple fluorophores is also achieved. Experiments with protoporphyrin IX in a glioma rodent model demonstrate in vivo quantitative and spectrally-resolved fluorescence imaging of infiltrating tumor margins for the …

A Digital X-Ray Tomosynthesis Coupled Near Infrared Spectral Tomography System For Dual-Modality Breast Imaging, Venkataramanan Krishnaswamy, Kelly E. Michaelsen, Brian W. Pogue, Steven P. Poplack, Ian Shaw, Ken Defrietas, Ken Brooks, Keith D. Paulsen

Dartmouth Scholarship

A Near Infrared Spectral Tomography (NIRST) system has been developed and integrated into a commercial Digital Breast Tomosynthesis (DBT) scanner to allow structural and functional imaging of breast in vivo. The NIRST instrument uses an 8-wavelength continuous wave (CW) laser-based scanning source assembly and a 75-element silicon photodiode solid-state detector panel to produce dense spectral and spatial projection data from which spectrally constrained 3D tomographic images of tissue chromophores are produced. Integration of the optical imaging system into the DBT scanner allows direct co-registration of the optical and DBT images, while also facilitating the synergistic use of x-ray contrast as …

Prostate Cancer Biomarker Identification: A Comparative Study, Wenjuan Jiang

Computational Modeling & Simulation Engineering Theses & Dissertations

With the current development of proteomics techniques, the discovery of potential molecular biomarkers for early detection of prostate cancer has been greatly improved. In this thesis, we implemented five classifiers including the support vector machine (SVM), Bayesian Classifier, Decision Tree, Random Forest and the Multilayer perceptron (MLP) to test their effectiveness in prostate cancer biomarker identification using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) tissue imaging data. The classifiers were utilized to discriminate cancer mass spectra from normal ones for the data collected at the Eastern Virginia Medical School (EVMS). There are 94 7 spectra from normal tissues and 27 from …

Methodology Development For Three-Dimensional Mr-Guided Near Infrared Spectroscopy Of Breast Tumors, Colin M. Carpenter, Subhadra Srinivasan, Brian W. Pogue, Keith D. Paulsen

Dartmouth Scholarship

Combined Magnetic Resonance (MR) and Near Infrared Spectroscopy (NIRS) has been proposed as a unique method to quantify hemodynamics, water content, and cellular size and packing density of breast tumors, as these tissue constituents can be quantified with increased resolution and overlaid on the structural features identified by the MR. However, the choices in how to reconstruct and visualize this information can have a dramatic impact on the feasibility of implementing this modality in the clinic. This is especially true in 3 dimensions, as there is often limited optical sampling of the breast tissue, and methods need to accurately reflect …