Radiation Medicine Commons^™

A Framework For Digital Energy Modulation And Translation In Projectional X-Ray Imaging, Richard R. Wargo

Theses and Dissertations

In projectional X-ray imaging, acquisition energy fundamentally influences subject contrast, image noise, and radiation dose. While dual-energy techniques exploit spectral differences to optimize contrast and enable material separation, acquiring multiple images of the same anatomy often requires additional exposures and increased system complexity.

This dissertation presents a framework for digital energy modulation (DEM), in which computational models are trained to translate projection images between energy domains without requiring additional X-ray acquisitions. DEM is conceived as a generalizable strategy for controlled contrast modulation in projection imaging, with potential applications in image optimization, radiation therapy alignment, and dual-energy applications.

The framework was …

Implementation Of Tg-351 Reference Dosimetry For A 6 Mv Photon Beam In An Mr-Guided Radiotherapy System, Nicholas A. Castellano Jr.

Theses and Dissertations

Magnetic resonance guided radiation therapy (MRgRT) combines magnetic resonance imaging (MRI) and radiation therapy to enable the visualization of anatomy in real time during treatment. The presence of a magnetic field in MRgRT affects charged particle radiation and detector responses, necessitating changes to traditional reference dosimetry procedures. The American Association of Physicists in Medicine (AAPM) Task Group 351 (TG-351) provides a formalism for reference dosimetry in MRgRT. In this study, the TG 351 formalism is used to perform reference dosimetry for a 6 MV flattening filter-free (FFF) photon beam from a Viewray MRIdian MR-Linac radiation therapy system. Beam quality determination, …

Characterization Of A Solid-State Detector For Dosimetry In The Diagnostic Energy Range With Verification Via Monte Carlo Estimation Of Average Breast Dose In Mammography, Areej Aljabal

Theses and Dissertations

This dissertation aims to develop a simplified QA metric for estimating radiation dose in mammography. This metric, the Mid-Breast Dose (MDB) Index, maybe be proposed as an alternative dose index, consistent with average glandular dose (AGD), for routine QA. MBD was obtained using “Phantom mid-point Air Kerma (AK) measurement” for conventional mammography. The advantage of this method is that MBD can be measured directly without requiring multiple conversion factors. The accuracy of clinical measurements in computing the MBD was assessed by comparing it with the AGD estimated by the Dance formalism experimentally and Monte Carlo simulation.

MBD methodology relies on …

Characterization And Investigation Of Cold Atmospheric Plasma And Its Effects On Cancer Cell Biology, Thomas M. Ritrosky

Theses and Dissertations

Modern cancer treatment uses radiation therapy in over 50% of patient cases. It is an e↵ective way of treating tumors because the mechanisms of cell killing are well known through the damage that ionizing radiation does to DNA. The amount of radiation can be tracked through measuring the dose of the clinical photon or electron beam used. However, there are limitations in the usage of radiation therapy, for example, a tumor can create hypoxic areas that become radioresistant leading to complete ine↵ectiveness of further radiation treatment. This project looks into the application of cold atmospheric plasma as an adjuvant therapy …

A Learning Health System For Radiation Oncology, Rishabh Kapoor

Theses and Dissertations

The proposed research aims to address the challenges faced by clinical data science researchers in radiation oncology accessing, integrating, and analyzing heterogeneous data from various sources. The research presents a scalable intelligent infrastructure, called the Health Information Gateway and Exchange (HINGE), which captures and structures data from multiple sources into a knowledge base with semantically interlinked entities. This infrastructure enables researchers to mine novel associations and gather relevant knowledge for personalized clinical outcomes.

The dissertation discusses the design framework and implementation of HINGE, which abstracts structured data from treatment planning systems, treatment management systems, and electronic health records. It utilizes …

A Method For Predicting Dose Changes For Hn Treatment Using Surface Imaging, Sarah E. Holler

Theses and Dissertations

Head and neck cancer is commonly treated with a six- to seven-week course of radiotherapy, during which a patient’s anatomy may change substantially, due to target reduction or weight loss. Anatomical changes lead to reduction in treatment quality due to decreased setup reproducibility and altered dose deposition compared to the original plan. Few clinics have developed a standard method for triggering resimulation and replan due to anatomic changes. This work investigates a new method for determining when to resimulate and replan HNC patients by utilizing their topographic anatomical changes to predict differences in planned versus delivered dose distributions. The first …

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. …