Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons^™

From Mathematics To Medicine: A Practical Primer On Topological Data Analysis (Tda) And The Development Of Related Analytic Tools For The Functional Discovery Of Latent Structure In Fmri Data, Andrew Salch, Adam Regalski, Hassan Abdallah, Raviteja Suryadevara, Michael J. Catanzaro, Vaibhav A. Diwadkar

Mathematics Faculty Research Publications

fMRI is the preeminent method for collecting signals from the human brain in vivo, for using these signals in the service of functional discovery, and relating these discoveries to anatomical structure. Numerous computational and mathematical techniques have been deployed to extract information from the fMRI signal. Yet, the application of Topological Data Analyses (TDA) remain limited to certain sub-areas such as connectomics (that is, with summarized versions of fMRI data). While connectomics is a natural and important area of application of TDA, applications of TDA in the service of extracting structure from the (non-summarized) fMRI data itself are heretofore nonexistent. …

Quantifying Phosphatidylethanol From Blood Samples, James V. Defrancesco, Majid Afshar

Chemistry: Faculty Publications and Other Works

Disclosed herein is a method for quantifying phosphatidylethanol (“ PEth ”), direct ethanol biomarker, from a blood sample using gas chromatography mass spectrometry. The method disclosed herein is useful for diagnosing acute and chronic alcohol abuse.

Soft Lithographic Replication Of High Length-Scale Micropillars From Laser-Ablated Fused-Silica Templates, Jason Pitts

University Honors Theses

Soft lithography is a well-established route to wafer-scale reproduction of micro- and nanoscale features in a wide variety of materials. Nevertheless, micron length scales have yet to be explored, despite the potential utility of such structures. Here, polymer micropillars of 6-12 μm length, approximately 0.5-1.5 μm wide at 10 μm spacing are reproduced from a polydimethylsiloxane (PDMS) mold made from patterned cellulose acetate (CA). The patterned CA was cast from a rigid fused silica template machined by a pulsed femtosecond laser. Pore topographic features were successfully reproduced in Norland Optical Adhesive (NOA), polycaprolactone (PCL), Nafion, acrylonitrile butadiene styrene (ABS), and …

Deep Learning Predicts Chromosomal Instability From Histopathology Images, Zhuoran Xu, Akanksha Verma, Uska Naveed, Samuel F. Bakhoum, Pegah Khosravi, Olivier Elemento

Publications and Research

Chromosomal instability (CIN) is a hallmark of human cancer yet not readily testable for patients with cancer in routine clinical setting. In this study, we sought to explore whether CIN status can be predicted using ubiquitously available hematoxylin and eosin histology through a deep learning-based model. When applied to a cohort of 1,010 patients with breast cancer (Training set: n = 858, Test set: n = 152) from The Cancer Genome Atlas where 485 patients have high CIN status, our model accurately classified CIN status, achieving an area under the curve of 0.822 with 81.2% sensitivity and 68.7% specificity in …

Validation Of A Respiratory Gating System For Automated Delivery Of The Deep Inspiration Breath-Hold Technique, Michael G. Stock

LSU Master's Theses

Purpose: To validate the performance of a respiratory gating system for the automated delivery of the deep inspiration breath-hold (DIBH) technique.

Methods: The gating system utilized an automatic gating interface (Elekta Response) which connected a marker-based respiratory motion monitoring system to the linear accelerator control system. The gating system was characterized dosimetrically and temporally using two distinct approaches. Central-axis output and energy constancy were evaluated across 8 beam-matched linear accelerators. Additionally, a representative set of 5 treatment plans were delivered both non-gated and gated to a 2D diode array (MapCHECK). The respiratory motion monitoring system optically tracked a reflective marker …

Research Focus: Pattern Recognition

In The Loop

A CDM health informatics team joins a global race to advance COVID-19 diagnostics through X-ray insights.

Optimal Analytical Methods For High Accuracy Cardiac Disease Classification And Treatment Based On Ecg Data, Jianwei Zheng

Computational and Data Sciences (PhD) Dissertations

This work constitutes six projects. In the first project, a newly inaugurated research database for 12-lead electrocardiogram signals was created under the auspices of Chapman University and Shaoxing People's Hospital (Shaoxing Hospital Zhejiang University School of Medicine). This database aims to enable the scientific community in conducting new studies on arrhythmia and other cardiovascular conditions. In the second project, we created a new 12-lead ECG database under the auspices of Chapman University and Ningbo First Hospital of Zhejiang University that aims to provide high quality data enabling detection of the distinctions between idiopathic ventricular arrhythmia from right ventricular outflow tract …

App Development For Wearable Sensors, Connor Pittman, Christopher Chappie, Patrick A. Tetreault

Thinking Matters Symposium

The objective of this research project was to create a wearable device that monitors bodily functions for the user to view on their smartphone. Sensor data is processed using the Arduino Nano 33 BLE microcontroller. The sensors used in this project include: proximity, temperature, humidity, heart rate, pressure, and skin impedance. This project takes advantage of the Arduino's Bluetooth low energy (BLE) capabilities so that all the data can be transmitted to a smartphone. This presentation shows the challenges faced during the project and how they were overcome. Some of these challenges include: programming, how heart rate sensors work, and …

C37: Evaluation Of The Diagnostic Efficacy Of Saliva For Detection Of Dengue Antibodies- An Elisa Study, Vidya Gurram Shankar

Annual Research Symposium

No abstract provided.

A High-Precision Machine Learning Algorithm To Classify Left And Right Outflow Tract Ventricular Tachycardia, Jianwei Zhang, Guohua Fu, Islam Abudayyeh, Magdi Yacoub, Anthony Chang, William Feaster, Louis Ehwerhemuepha, Hesham El-Askary, Xianfeng Du, Bin He, Mingjun Feng, Yibo Yu, Binhao Wang, Jing Liu, Hai Yao, Hulmin Chu, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Introduction: Multiple algorithms based on 12-lead ECG measurements have been proposed to identify the right ventricular outflow tract (RVOT) and left ventricular outflow tract (LVOT) locations from which ventricular tachycardia (VT) and frequent premature ventricular complex (PVC) originate. However, a clinical-grade machine learning algorithm that automatically analyzes characteristics of 12-lead ECGs and predicts RVOT or LVOT origins of VT and PVC is not currently available. The effective ablation sites of RVOT and LVOT, confirmed by a successful ablation procedure, provide evidence to create RVOT and LVOT labels for the machine learning model.

Methods: We randomly sampled training, validation, and testing …

The Potential Of Raman Spectroscopy In The Diagnosis Of Dysplastic And Malignant Oral Lesions, Ola Ibrahim, M. Toner, Steven Flint, Hugh Byrne, Fiona Lyng

Articles

Early diagnosis, treatment and/or surveillance of oral premalignant lesions are important in preventing progression to oral squamous cell carcinoma (OSCC). The current gold standard is through histopathological diagnosis, which is limited by inter and intra observer and sampling errors. The objective of this work was to use Raman spectroscopy to discriminate between benign, mild, moderate and severe dysplasia and OSCC in formalin fixed paraffin preserved (FFPP) tissues. The study included 72 different pathologies from which 17 were benign lesions, 20 mildly dysplastic, 20 moderately dysplastic, 10 severely dysplastic and 5 invasive OSCC. The glass substrate and paraffin wax background were …

Biomedical Applications Of Vibrational Spectroscopy: Oral Cancer Diagnostics, Hugh Byrne, Isha Behl, Genecy Calado, Ola Ibrahim, M. Toner, Sheila Galvin, Claire M. Healy, Steven Flint, Fiona Lyng

Articles

Vibrational spectroscopy, based on either infrared absorption or Raman scattering, has attracted increasing attention for biomedical applications. Proof of concept explorations for diagnosis of oral potentially malignant disorders and cancer are reviewed, and recent advances critically appraised. Specific examples of applications of Raman microspectroscopy for analysis of histological, cytological and saliva samples are presented for illustrative purposes, and the future prospects, ultimately for routine, chairside in vivo screening are discussed.

Resident Heart Rate Variability During Cataract Surgery, Ahmad Baiyasi, Shibandri Das, Ferris Bayasi, Faisal Ridha Al-Timimi

Medical Student Research Symposium

Purpose: To evaluate ophthalmology resident anxiousness and cardiovascular response by tracking resident heart rate (HR) when performing cataract surgery during their last year of residency.

Methods: A prospective analysis of 31 cataract cases, completed by three residents (two females and one male), at the Kresge Eye Institute in August and September 2020 was performed. Inclusion criteria for cases included all cataract cases performed by PGY-4 residents at the Kresge Eye Institute who downloaded the Heart Graph app supported by iOS. Residents with android mobile devices were excluded from the study. Informed consent was obtained from all residents who utilized the …

Developing A New Analytical Model For Combatting Crises: A Comprehensive Review, Seth Spire

Research Awards

As the world emerges from the COVID-19 pandemic, it is critical to reflect on the lessons learned and prepare for potential future health crises. While data analytics and artificial intelligence (AI) played a pivotal role in managing the pandemic, there is much room for improvement and further use. This study examines the current state of data science tools employed during COVID-19, evaluating their advantages, limitations, and challenges in their broader implementation. We also review literature on future directions for AI in healthcare. Our findings highlight significant challenges, including difficulties in accessing usable data and common distrust of AI models for …

Adaptive Physics-Based Non-Rigid Registration For Immersive Image-Guided Neuronavigation Systems, Fotis Drakopoulos, Christos Tsolakis, Angelos Angelopoulos, Yixun Liu, Chengjun Yao, Kyriaki Rafailia Kavazidi, Nikolaos Foroglou, Andrey Fedorov, Sarah Frisken, Ron Kikinis, Alexandra Golby, Nikos Chrisochoides

Computer Science Faculty Publications

Objective: In image-guided neurosurgery, co-registered preoperative anatomical, functional, and diffusion tensor imaging can be used to facilitate a safe resection of brain tumors in eloquent areas of the brain. However, the brain deforms during surgery, particularly in the presence of tumor resection. Non-Rigid Registration (NRR) of the preoperative image data can be used to create a registered image that captures the deformation in the intraoperative image while maintaining the quality of the preoperative image. Using clinical data, this paper reports the results of a comparison of the accuracy and performance among several non-rigid registration methods for handling brain deformation. A …

Impact Of Hemodynamic Vortex Spatial And Temporal Characteristics On Analysis Of Intracranial Aneurysms, Kevin W. Sunderland

Dissertations, Master's Theses and Master's Reports

Subarachnoid hemorrhage is a potentially devastating pathological condition in which bleeding occurs into the space surrounding the brain. One of the prominent sources of subarachnoid hemorrhage are intracranial aneurysms (IA): degenerative, irregular expansions of area(s) of the cerebral vasculature. In the event of IA rupture, the resultant subarachnoid hemorrhage ends in patient mortality occurring in ~50% of cases, with survivors enduring significant neurological damage with physical or cognitive impairment. The seriousness of IA rupture drives a degree of clinical interest in understanding these conditions that promote both the development and possible rupture of the vascular malformations. Current metrics for the …

Tri-Molybdenum Phosphide (Mo3P) And Multi-Walled Carbon Nanotube Junctions For Volatile Organic Compounds (Vocs) Detection, Baleeswaraiah Muchharla, Praveen Malali, Brenna Daniel, Alireza Kondori, Mohammad Asadi, Wei Cao, Hani E. Elsayed-Ali, Mickaël Castro, Mehran Elahi, Adetayo Adedeji, Kishor Kumar Sadasivuni, Muni Raj Mauya, Kapil Kumar, Abdennaceur Karoui, Bijandra Kumar

Electrical & Computer Engineering Faculty Publications

Detection and analysis of volatile organic compounds’ (VOCs) biomarkers lead to improvement in healthcare diagnosis and other applications such as chemical threat detection and food quality control. Here, we report on tri-molybdenum phosphide (Mo₃P) and multi- walled carbon nanotube (MWCNT) junction-based vapor quantum resistive sensors (vQRSs), which exhibit more than one order of magni- tude higher sensitivity and superior selectivity for biomarkers in comparison to pristine MWCNT junctions based vQRSs. Transmission electron microscope/scanning tunneling electron microscope with energy dispersive x-ray spectroscopy, x-ray diffraction, and x-ray photo- electron spectroscopy studies reveal the crystallinity and the presence of Mo and …

Biocompatible And Multifunctional Trityl Spin Probes For Electron Paramagnetic Resonance Spectroscopy, Teresa D. Gluth

Graduate Theses, Dissertations, and Problem Reports (ETD)

The primary objective of my thesis was to develop and utilize a biocompatible multifunctional trityl spin probe for concurrent measurement of pO₂, pH_e, and [P_i] in vivo by electron paramagnetic resonance (EPR) spectroscopy (Chapter 2). My first goal was to synthesize the proposed probe we are terming HOPE71. Secondly, HOPE71 was characterized by X-band and L-band EPR spectroscopy. Next, the biocompatibility of HOPE71 was assessed through an albumin binding test, cytotoxicity assays, and in vivo intravenous tolerance. Then, the use of HOPE71 to measure the target parameters was demonstrated in a breast cancer …

The Influence Of The Psychophysical Assessment Paradigm On Pitch Discrimination For Adults (And A Pilot Sample Of Children), Ashley G. Flagge, Lucile Puranen, Madhuri S. Mulekar

Ashley Flagge Publications

Pitch discrimination ability has been of research interest due to its potential relationship to language and literacy. However, assessment protocols for pitch discrimination have varied widely. Prior studies with both children and adults have produced conflicting performance findings across different pitch discrimination research paradigms, though they have consistently shown that discrimination accuracy is based on the psychophysical assessment method applied. In the present study, we examined pitch discrimination performance among convenience samples of 19 adult women and ten female children across six different adaptive psychophysical measurement conditions. We found pitch discrimination performance in both groups to be impacted by the …

The Enlightening Role Of Explainable Artificial Intelligence In Chronic Wound Classification, Salih Sarp, Murat Kuzlu, Emmanuel Wilson, Umit Cali, Ozgur Guler

Engineering Technology Faculty Publications

Artificial Intelligence (AI) has been among the most emerging research and industrial application fields, especially in the healthcare domain, but operated as a black-box model with a limited understanding of its inner working over the past decades. AI algorithms are, in large part, built on weights calculated as a result of large matrix multiplications. It is typically hard to interpret and debug the computationally intensive processes. Explainable Artificial Intelligence (XAI) aims to solve black-box and hard-to-debug approaches through the use of various techniques and tools. In this study, XAI techniques are applied to chronic wound classification. The proposed model classifies …

A Deep Learning U-Net For Detecting And Segmenting Liver Tumors, Vidhya Cardozo

Theses and Dissertations

Visualization of liver tumors on simulation CT scans is challenging even with contrast-enhancement, due to the sensitivity of the contrast enhancement to the timing of the CT acquisition. Image registration to magnetic resonance imaging (MRI) can be helpful for delineation, but differences in patient position, liver shape and volume, and the lack of anatomical landmarks between the two image sets makes the task difficult. This study develops a U-Net based neural network for automated liver and tumor segmentation for purposes of radiotherapy treatment planning. Non-contrast simulation based abdominal CT axial scans of 52 patients with primary liver tumors were utilized. …

Nebulizer-Based Systems To Improve Pharmaceutical Aerosol Delivery To The Lungs, Benjamin M. Spence

Theses and Dissertations

Combining vibrating mesh nebulizers with additional new technologies leads to substantial improvements in pharmaceutical aerosol delivery to the lungs across therapeutic administration methods. In this dissertation, streamlined components, aerosol administration synchronization, and/or Excipient Enhanced Growth (EEG) technologies were utilized to develop and test several novel devices and aerosol delivery systems. The first focus of this work was to improve the poor delivery efficiency, e.g., 3.6% of nominal dose (Dugernier et al. 2017), of aerosolized medication administration to adult human subjects concurrent with high flow nasal cannula (HFNC) therapy, a form of continuous-flow non-invasive ventilation (NIV). The developed Low-Volume Mixer-Heater (LVMH) …

Live Cell Biomass Tracking For Basic, Translational, And Clinical Research, Graeme Murray

Theses and Dissertations

Single cell mass is tightly regulated throughout generations and the cell cycle, making it an important marker of cell health. Abnormal changes in cell size can be the first indication of dysfunction in response to environmental stimuli such as cytotoxic drugs. Described here is the further development of high-speed live cell interferometry (HSLCI) to concurrently measure the changes in single cell mass of thousands of cells over time. Critically, the high-throughput nature of HSLCI provides realistic pictures of tumor heterogeneity. This throughput enabled HSLCI to correctly predict in vivo carboplatin sensitivity of three triple negative breast cancer patient derived xenografts, …

Harnessing Acoustic Streaming For Bioanalysis In Microfluidics, Xiaojun Li

Graduate Theses, Dissertations, and Problem Reports (ETD)

In the past few decades, microfluidic technology has been developed rapidly in both fabrication methods and multifunctionality integrations, making it a powerful tool for a wider variety of biological applications. The device fabrication method has expanded from conventional polymer-based micro devices to 3D-printed micro devices, and allows multiple functions such as electric, optic, magnetic and acoustic to be integrated on a single platform. This dissertation focuses on method development of acoustic streaming-based microfluidics in bioanalysis such as immunoassay, enzyme kinetics and DNA fragmentation analysis. In this dissertation, a micromixer was developed based on acoustic streaming generated from sharp-edge structure vibration …

Carbon Dots As Artificial Peroxidases For Analytical Applications, Shih-Chun Wei, Yang-Wei Lin, Huan-Tsung Chang

Journal of Food and Drug Analysis

Nanozymes have become attractive in analytical and biomedical fields, mainly because of their low cost, long shelf life, and less environmental sensitivity. Particularly, nanozymes formed from nanomaterials having high surface area and rich active sites are interesting since their activities can be tuned through carefully controlling their size, morphology, and surface properties. This review article focuses on preparation of carbon dots (C dots) possessing peroxidase-like activity and their analytical applications. We highlight the important roles of the oxidation states and surface residues of C dots and their nanocomposites with metal, metal oxides, or metal sulfides playing on determining their specificity …

Predicting Postoperative Delirium Risk For Intracranial Surgery: A Statistical Machine Learning Approach, Juliet Aygun, Alaina Bartfeld, Sahana Rayan

The Journal of Purdue Undergraduate Research

No abstract provided.

A Neutrosophic Clinical Decision-Making System For Cardiovascular Diseases Risk Analysis, Florentin Smarandache, Shaista Habib, Wardat-Us- Salam, M. Arif Butt, Muhammad Akram

Branch Mathematics and Statistics Faculty and Staff Publications

Cardiovascular diseases are the leading cause of death worldwide. Early diagnosis of heart disease can reduce this large number of deaths so that treatment can be carried out. Many decision-making systems have been developed, but they are too complex for medical professionals. To target these objectives, we develop an explainable neutrosophic clinical decision-making system for the timely diagnose of cardiovascular disease risk. We make our system transparent and easy to understand with the help of explainable artificial intelligence techniques so that medical professionals can easily adopt this system. Our system is taking thirtyfive symptoms as input parameters, which are, gender, …

Characterization Of Treatment Planning System Photon Beam Modeling Errors In Iroc Houston Phantom Irradiations, Mallory Glenn

Dissertations and Theses (Open Access)

In radiation therapy, proper commissioning of the treatment planning system’s (TPS) dose calculation algorithm is critical because any errors in this process impact all treatment plans prepared in the system. Previously, TPS errors have been identified as a major cause for poor phantom irradiation performance, which may also mean that patients are treated suboptimally. The purpose of this work was to investigate the TPS beam modeling developed by the radiotherapy community to understand where inconsistencies may arise, which variables are most susceptible to variations, and in what way changing these variables can alter dose calculations.

Using the Imaging and Radiation …

A Single-Center Comparison Using Exoskeleton Rehabilitation For Cerebrovascular Accidents And Traumatic Brain Injury In A Cohort Of Hispanic Patients, Lisa R. Trevino, Kristina Vatcheva, Michael E. Auer, Angela Morales, Lama M. Abdurrahman, Sarajova Viswamitra, Annelyn Torres-Reveron

School of Mathematical & Statistical Sciences Faculty Publications

Background Traumatic brain injury (TBI) is one of the leading causes of disability in the United States. The EKSO GT Bionics® (EKSO®) is a robotic exoskeleton approved by the Federal Drug Administration (FDA) for rehabilitation following a cerebrovascular accident (CVA or stroke) and recently received approval for use in patients with TBI. The aim of the study was to examine if the use of exoskeleton rehabilitation in patients with TBI will produce beneficial outcomes.

Methods This retrospective chart-review reports the use of the (EKSO®) robotic device in the rehabilitation of patients with TBI compared to patients with CVA. We utilized …

Mapping Gadolinium Contrast In A Complex Ionic And Photosynthesis Environment Of Pineapple By Near-Infrared And X-Ray Imaging, Subhendra Sarkar, Zoya Vinokur, Chen Xu, Tetiana Soloviova, Amina Shahbaz, Aldona Gjoni

Publications and Research

This work explores the diffusivity of a lanthanide complex, Eovist (Gadolinium-Ethoxy Benzyl Diethylenetriamine pentaacetate) that is stable in neutral media but is not in acidic environment. In the current work an acidic fruit model like pineapple that is rich in transition metals was used and a possible transmetallation reaction among Eovist and transition metal complexes was tested using X-ray imaging. Another goal of this work was to perturb the usual and the unusual photosynthesis systems that pineapple has maintained for millions of years during the evolution of circadian genes for efficient water conservation by dark photosynthesis. To detect such photosynthesis …