Medical Specialties Commons^™

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 …

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 …