Organizational Unit:

Wallace H. Coulter Department of Biomedical Engineering

Permanent Link

https://hdl.handle.net/1853/70757

Research Organization Registry ID

https://ror.org/02j15s898

Description

The joint Georgia Tech and Emory department was established in 1997

Parent Organization

Organizational Unit

College of Engineering

ArchiveSpace Name Record

https://finding-aids.library.gatech.edu/agents/corporate_entities/1129

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Publication Search Results

Now showing 1 - 10 of 1236

Leveraging Notch Signaling and Small Molecules in New Treatments for Myocardial Infarction

(Georgia Institute of Technology, 2024-12-08) Robeson, Matthew James

C-kit+ Cardiac progenitor cells have been widely investigated over the last two decades as a potential therapeutic for myocardial infarction (MI). While these cells were originally thought to contribute to the formation of new cardiomyocytes, we now know that CPCs are primarily and endothelial cell type. However, research from our lab and others has demonstrated that these cells still have a reparative benefit when implanted in vivo following MI, contributing to a reduction in fibrosis and revascularization around the infarct, primarily mediated by the release of paracrine factors including miRNA. Studies from our lab and others have demonstrated the importance of the highly conserved developmental signaling pathway known as Notch within these CPCs, but to present, an extensive study on the mechanistics of Notch signaling in the CPC niche has not been performed. By stimulating CPCs with each of the four canonical Notch ligands, I demonstrate changes in gene expression profile and cellular function that highlight the importance of ligand discrimination in Notch signaling in CPCs. Additionally, I develop an injectable hydrogel capable of stimulating Notch and show the potential benefits for implantation in an in vivo model of MI in a rat heart. I also investigated the striated muscle protein MG53 and its E3 ligase dead mutant MG53-C14A, a potential therapeutic for MI that provides provides protection against ischemic damage but also contributes to insulin resistance within the heart.
Computational Imaging-Based Prognostic and Predictive Biomarkers for Oropharyngeal Cancer

(Georgia Institute of Technology, 2024-12-03) Song, Bolin

It is estimated that 54,540 adults in the United States will be diagnosed with oropharyngeal squamous cell carcinoma (OPSCC) in 2024, 70% of which will be related to human papillomavirus (HPV+). HPV+ OPSCC differs from HPV-negative (HPV-) OPSCC, which is associated with tobacco and alcohol use, in terms of disease aggressiveness and response to treatment. These differences have led to different treatment paradigms, which requires separate risk stratification strategies for the two cancer entities to guide treatment planning. Chemoradiation is a common therapeutic regimen for p16+ OPSCC. However, adding chemotherapy can increase treatment-related toxicity, a particular concern for patients who are at low risk of disease recurrence. This underscores the need to develop predictive biomarkers to identify low-risk OPSCC patients who may not benefit from chemotherapy and could avoid such toxic treatments without compromising their outcomes. The prognosis of p16+ OPSCC is highly influenced by the characteristics of both the primary tumor (PT) and metastatic cervical lymph nodes (LN). Although AI-based prognostic biomarkers focusing on pathology and radiology have been developed independently for head and neck cancers, the integration of PT and metastatic cervical LN across radiology and pathology remains unexplored. The objective of this thesis is to develop and validate four computational workflows. Firstly, we develop a prognostic tool for OPSCC risk stratifications taking HPV status into account. Secondly, we developed an predictive CT biomarker to identify early-stage OPSCC candidates who will not benefit from chemotherapy, thus suitable for treatment tailoring. Thirdly we investigated a deep learning model integrating PT and metastatic cervical LN to risk-stratify OPSCC patients into low- vs high-risk groups based on disease-free survival, overall survival and locoregional failure. Finally, we investigated the prognostic value of an multimodal AI approach, termed the swin-transformer-based multimodal and multi-region data fusion framework (SMuRF), to predict outcomes of OPSCC.
Real-time tool development for neural dynamic adaptive control

(Georgia Institute of Technology, 2024-07-27) Kate, Sai Pradeep

Brain activity is inherently noisy and dynamic with hidden brain states affecting our behavior response to external sensory input. With the rapid acceleration of tools developed for monitoring the behavior response and recording neuronal population, we can develop a variety of real-time tools for monitoring animal behavior and controlling neurons. In this study, we have used open source tools to develop two pipelines that can be utilized for observing the behavior response of animals and for closed-loop feedback control of neural populations in real-time. Deeplabcut was used for monitoring the behavior, and the State Space Linear Dynamical Systems approach was used for the dynamic feedback control of neural population. The objective of building both these set-ups is to have low-cost, open source tools that can be used for the adaptive control of neurons under different experimental conditions.
Cathepsin and CTGF-mediated Vascular Remodeling and Altered Arterial Mechanics in Sickle Cell Disease and Peripheral Arterial Disease

(Georgia Institute of Technology, 2024-07-27) Omojola, Victor

Arterial stiffening is an underlying mechanism of cardiovascular disease (CVD) which is the leading cause of death in the world, accounting for 32.1% of deaths in 2015. Stiffening of the large arteries—peripheral arterial disease (PAD)—doubles cardiovascular mortality in older individuals. CVD may primarily affect older adults; however in sickle cell disease, the impacts of CVD are seen in early childhood—11% of children with SCD are at risk of having an ischemic stroke before age 20. Sickle cell disease (SCD) is the most common inherited blood disorder, and is a health disparity, affecting approximately 1 in 500 African-Americans. In SCD, it has been observed that cysteine cathepsin expression is increased in the arterial wall. Other work implicates cathepsins in pathological arterial remodeling in other cardiovascular diseases. The objective of this work is to characterize how cysteine cathepsins and thrombospondin-1 contribute to SCD-mediated arterial remodeling and PAD. In Aim 1, a murine SCD transgenic mouse model will be used to mechanically characterize the lifelong arterial remodeling that occurs in SCD. In Aim 2, we will determine the markers that mediate SCD-remodeling by using chimeric SCD and cathepsin knockout mouse lines and mechanical tests. Histological methods will be used to further characterize the impacts of arterial remodeling by cathepsin expression or the TSP-1/CTGF pathway. In Aim 3, the utility of inhibiting the TSP-1/CTGF pathway in protecting vascular integrity will be explored in TSP-1 knockout animals. Ultimately the mechanisms explored in the proposed studies will advance current knowledge about the progression of SCD and PAD vascular remodeling, and the development of therapies that exploit these complex interactions to protect against or prevent destructive vascular remodeling.
Electrospun Hydrogel Based Drug Delivery System for Immune Regeneration in a Cleft Palate Mice Model

(Georgia Institute of Technology, 2024-07-27) Iyer, Keerthana Srini

Cleft palate is a developmental birth defect, defined by an abnormal space or gap formed in the upper lip or palate. This condition has high mortality rate if not treated early. Surgical correction is the current practice in the clinical field, however this comes with the risk of a secondary surgery in these patients. Wound healing takes place in a bacteria laden environment, hence increasing complications and hampers tissue regeneration. There have been many studies proving the efficacy of biomaterials as an alternative treatment plan for patients with cleft palate. Building on this finding, we developed a novel electrospun hydrogel material composed of PEGylated norbornene and thiolated hyaluronate. Developed using photo click chemistry, these materials provide an excellent scaffold for tissue regeneration, while doubling as a drug delivery carrier. The tunability of these materials facilitates in the development of a more robust material for the application of cleft palate repair, making it a potent strategy for wound healing.
Computational Structural Stress Analysis of Acute Uncomplicated Type B Aortic Dissection Using Fluid Structure Interaction

(Georgia Institute of Technology, 2024-07-25) Agarwal, Rishika

In this study, Uncomplicated Type B Aortic Dissection (un-TBAD) is investigated using Fluid-Structure Interaction (FSI) approach. The focus is to understand the correlation and dynamics between the wall stress and the rate of growth of aortic wall, in the presence of the aorta. Patient-specific geometry was created using CT scans through segmentation. Two different meshing techniques were used for both the solid and fluid meshes: hexahedral and tetrahedral. The Computational Fluid Dynamics (CFD) analysis, using the Windkessel model, was used to calculate the non- uniform pressure distribution in the aorta which was then used as the input for the Finite Element Analysis (FEA). Recent follow up scans were used, and logarithmic strain was calculated to quantify the growth rate. Statistical methods were then used to perform spatial analysis and linear regression to derive the direct relation between the wall stress and the growth rate of the aorta. The FSI results pointed towards a pressure difference in False Lumen (FL) and True Lumen (TL) of the aorta. The study also established that higher wall stress results in the rapid growth rate of the aorta. Overall, this research provides a detailed analysis of TBAD progression providing valuable insight into biomechanical factors triggering aortic growth. The study also highlights the potential of FSI analysis to the overall understanding of disease taking step towards a better patient outcome.
Array design and development for steerable robotic guidewire

(Georgia Institute of Technology, 2024-07-25) Olomodosi, Adeoye Oluwatunmise

Approximately 4 million people with peripheral artery disease (PAD) present with critical limb ischemia each year, posing significant health risks including limb loss, exacerbating other comorbidities, and increasing risk of mortality. Urgent revascularization procedures are required for 1-2 patients per 10000 per year, however, navigating through occlusions in affected arteries, especially chronic total occlusions (CTOs), can be challenging, with failure rates up to 20% or greater depending on navigator’s experience. Minimally-invasive (i.e. endovascular) revascularization is preferable due to decreased recovery time and increased risk of complications associated with open surgery. However, 40% of people with PAD also have chronic total occlusions (CTOs), resulting in >20% of revascularization procedures failing when CTOs are present. A steerable robotic guidewire with integrated forward-viewing imaging capabilities would allow the guidewire to navigate through tortuous vasculature and facilitate crossing CTOs in revascularization procedures that currently fail due to inability to route the guidewire. The robotic steering capabilities of the guidewire can be leveraged for 3D synthetic aperture imaging with a simplified, low element count, forward-viewing 2D array on the tip of the mechanically-steered guidewire. Images can then be formed using a hybrid beamforming approach, with focal delays calculated for each element on the tip of the guidewire and for each physical location to which the robotically-steered guidewire is steered. Unlike synthetic aperture imaging with a steerable guidewire having only a single element transducer, an array with even a small number of elements can allow estimation of blood flow and physiological motion in vivo. A miniature, low element count 2D array transducer with 9 total elements (3 × 3) having total dimensions of 1.5 mm × 1.5 mm was designed to operate at 17 MHz. A proof-of-concept 2D array transducer was fabricated and characterized acoustically. The developed array was then used to image a wire target, a peripheral stent, and an ex vivo porcine iliac artery. Images were formed using the described synthetic aperture beamforming strategy. Acoustic characterization showed a mean resonance frequency of 17.6 MHz and a -6 dB bandwidth of 35%. Lateral and axial resolution were 0.271 mm and 0.122 mm, respectively, and an increase in SNR of 4.8 dB was observed for the 2D array relative to the single element case. The first 2D array imaging system utilizing both mechanical and electronic steering for guidewire-based imaging was developed and demonstrated. A 2D array imaging system operating on the tip of the mechanically-steered guidewire provides improved frame rate and increases field of view relative to a single element transducer. To facilitate crossing CTOs, we propose a flexible, robotically steerable guidewire with an ultrasound transducer at the tip for procedural guidance. A miniature 2D array imaging transducer was developed and characterized for this application. The presented studies demonstrate i.) the fabrication of the aforementioned mechanically-steered 2D array transducer, ii.) image formation approach for the mechanically-steered system, iii.) the imaging experiments to demonstrate imaging performance in phantoms, and iv.) opportunities for future research and development. Results of this study suggest that this device could image occluded vascular regions to allow interventionalists to advance the guidewire beyond CTOs, which could improve procedural outcomes for PAD patients. Facilitating safer navigation through chronic total occlusions could ultimately reduce procedural risk and improve overall patient outcomes following peripheral endovascular revascularization.
Gait signatures: data-driven discovery of individual-specific neuromechanical dynamics

(Georgia Institute of Technology, 2024-07-17) Winner, Taniel S.

Human gait is an important aspect of mobility that impacts the ability to perform everyday activities, safety and quality of life. Changes in gait patterns can have clinical implications, indicating risks for conditions such as osteoarthritis or changes in disease progression. Standard gait evaluation methods often rely on visual observation or subjective selection of discrete gait variables, overlooking continuous data and complex inter-limb and inter-joint spatiotemporal dependencies that underlie gait and impairment. The lack of reliable, quantitative metrics for tracking and assessing individual-specific gait differences can impact rehabilitation prescriptions, and the development of tailored rehabilitation solutions. This thesis introduces a novel, data-driven approach to model the dynamics of human gait, effectively capturing the complex spatiotemporal dependencies between individuals’ joint angles, arising from joint neural and biomechanical constraints (Aim 1). Individual-specific representations of gait dynamics, termed “gait signatures”, provide a holistic method for identifying and quantifying gait differences in both health and disease. I demonstrate that gait signatures in able-bodied individuals remain consistent across a wide range of walking speeds, with speed-induced changes being both predictable and linear (Aim 2). Additionally, I show that gait signatures can track and quantify clinically meaningful changes in stroke survivors’ gait dynamics through two longitudinal gait interventions (Fast and Fast Functional Electrical Stimulation) (Aim 3). Together, these findings underscore the utility of gait signatures as a quantitative tool for enhancing gait analysis in both sports and clinical settings, facilitating the development of personalized rehabilitation treatment plans.
Toward accurate health monitoring through large-scale Photoplethysmography signal from wearable devices

(Georgia Institute of Technology, 2024-07-17) Ding, Cheng

This dissertation presents a comprehensive study on enhancing health monitoring through advanced analysis of photoplethysmography (PPG) signals from wearable devices. As wearable technologies proliferate, there is a significant opportunity to leverage the PPG technology embedded in devices like smartwatches for continuous health monitoring. This research addresses critical challenges in PPG signal utilization for health diagnostics, such as atrial fibrillation (AF) detection, through a combination of novel data augmentation techniques, robust machine learning models, and the development of a large-scale labeled PPG dataset. Firstly, the dissertation introduces a Generative Adversarial Network (GAN)-based technique for data augmentation to tackle the inherent class imbalance in PPG datasets used for AF detection. This approach enhances the generation of synthetic PPG signals by incorporating spectral loss adjustments, which in turn improves the performance of AF classifiers. Secondly, recognizing the limitations of synthesized data, this study compiles a novel dataset of over 8 million real-world PPG records labeled using bedside monitor alarms for AF. A robust learning method tailored to handle the label noise in this large dataset is developed, significantly boosting the accuracy of AF detection. Finally, the dissertation introduces SiamQuality, a foundational model based on a Siamese network architecture that addresses signal quality issues in PPG data. By ensuring that signals of similar physiological states yield similar feature representations, irrespective of their quality, the model sets new standards for reliability in PPG-based health monitoring applications. Collectively, these advancements represent a significant step forward in the utilization of PPG technology for health monitoring, promising to enhance diagnostic capabilities and patient outcomes in real-world settings.
Towards demystifying the “mysterious creatures of the deep”: corticothalamic feedback in sensory processing

(Georgia Institute of Technology, 2024-06-27) Dimwamwa, Elaida

Combining incoming sensory information with expectations from our lived experiences, remarkably and effortlessly, we identify and discriminate between objects on a daily basis. While the neuronal processes underlying our ability to complete such sensory-based tasks are canonically studied as feedforward neuronal pathways, numerous feedback pathways interact with the feedforward pathways to enable us to perceive the world through our senses. Corticothalamic feedback from layer 6 of the cortex (L6CT) is one such process that provides copious inputs back to the thalamus, but its function remains elusive. 40-60% of first-order thalamic inputs derive from L6CT neurons, thus positioning L6CT neurons to play an essential role in thalamocortical sensory signaling for sensory perception, which we elucidate through two studies. Using the somatosensory whisker system of awake, transgenic mice selectively expressing channelrhodopsin-2 in L6CT neurons, we investigate how L6CT neurons modulate thalamic and cortical activity and reveal that L6CT neurons can both enhance and suppress thalamocortical excitability in a manner that is dependent on both the firing rate and synchrony of the L6CT inputs (Chapter 2). We then determine the precise activity patterns of L6CT neurons in mice behaving in a somatosensory detection task and reveal that not only are L6CT neurons sensory responsive in the awake and behaving animal, but that both the sensory response as well as the pre-stimulus synchrony encodes the behavior of the animal (Chapter 3). Taken together, this thesis provides evidence for L6CT neurons as dynamic regulators of thalamocortical excitability that contribute to performance in sensory detection.