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Full-Text Articles in Health and Medical Physics

Theory, Experiments, And Image Recovery Algorithms For X-Ray Interferometry, Hunter C. Meyer Mar 2026

Theory, Experiments, And Image Recovery Algorithms For X-Ray Interferometry, Hunter C. Meyer

LSU Doctoral Dissertations

Purpose: X-ray grating interferometry is a form of X-ray phase contrast imaging capable of simultaneously measuring attenuation, differential-phase, and dark-field images arising from X-ray absorption, refraction, and small-angle scattering, respectively. These additional contrast mechanisms have potential clinical and industrial applications, particularly for lung tissue characterization and disease identification. As grating interferometers approach clinical viability, key challenges include reducing X-ray dose, mitigating mechanical instability, and correcting spectral artifacts resulting from beam hardening.

Methods: The modulated phase grating interferometer (MPGI) is a potential solution for reducing X-ray dose by eliminating the analyzer grating used in alternative interferometer designs, including the Talbot-Lau interferometer …


Dose Calculation And Prediction Methods For Gamma Knife Stereotactic Radiosurgery, Payton Hayes Stone Apr 2023

Dose Calculation And Prediction Methods For Gamma Knife Stereotactic Radiosurgery, Payton Hayes Stone

LSU Doctoral Dissertations

Implementation of automation routines leveraging deep learning (DL) methods has been a growing topic of interest. The focus of this work is on the Gamma Knife (GK) workflow, specifically the approximation of dose distributions from GK plan parameters and the prediction of dose distributions using DL. These works contribute towards the larger goal of treatment plan prediction and are seen as intermediate steps towards that end. The approximation of dose distributions was motivated by the closed nature of the GK system, which causes complications with the evaluation of the predictions made by the DL models. The approximation utilizes a superposition …


Towards Optimizing Quality Assurance Outcomes Of Knowledge-Based Radiation Therapy Treatment Plans Using Machine Learning, Phillip Douglas Hardenbergh Wall May 2020

Towards Optimizing Quality Assurance Outcomes Of Knowledge-Based Radiation Therapy Treatment Plans Using Machine Learning, Phillip Douglas Hardenbergh Wall

LSU Doctoral Dissertations

Knowledge-based planning (KBP) techniques have been shown to provide improvements in plan quality, consistency, and efficiency for advanced radiation therapies such as volumetric modulated arc therapy (VMAT). While the potential clinical benefits of KBP methods are generally well known, comparatively less is understood regarding the impact of using these systems on resulting plan complexity and pre-treatment quality assurance (QA) measurements, especially for in-house KBP systems. Therefore, the overarching purpose of this work was to assess QA implications with using an in-house KBP system and explore data-driven methods for mitigating increased plan complexity and QA error rates without compromising dosimetric plan …


Stray Radiation Dose From X-Ray And Proton Beam Radiation Therapies, Christopher William Schneider Jun 2019

Stray Radiation Dose From X-Ray And Proton Beam Radiation Therapies, Christopher William Schneider

LSU Doctoral Dissertations

The growing population of cancer survivors at risk of radiation induced side-effects is a public health concern. These side-effects include serious conditions such as second cancers, the majority of which occur outside of the primary treatment volume. Radiotherapy treatment planning systems systematically underestimate the dose to tissues out-of-field. Attempts to predict and reduce the risks of radiogenic side effects require accurate and personalized knowledge of the out-of-field radiation dose to patients. The long-term goal of this research is to provide clinical and research tools necessary to reduce the risk of radiotherapy side effects and improve the health outcomes of radiotherapy …


Computational Feasibility Of Simulating Whole-Organ Vascular Networks And Their Response To Injury, William Patrick Donahue May 2019

Computational Feasibility Of Simulating Whole-Organ Vascular Networks And Their Response To Injury, William Patrick Donahue

LSU Doctoral Dissertations

Healthy vasculature is critical to sustaining the function of normal tissues in the human body. Radiation therapy for cancer causes injury of the vasculature of non-cancerous tissues. These changes have been associated with potentially deadly conditions such as necrosis of the brain tissue. There are currently no computational methods to study the effects of radiation vascular injury in whole-organ vasculatures because of the large number of vessels involved. The goal of this work was to test the feasibility of simulating radiation damage to whole-brain vascular networks and calculate the resulting change in blood flow. To accomplish this, we developed algorithms …


Framework For Algorithmically Optimizing Longitudinal Health Outcomes: Examples In Cancer Radiotherapy And Occupational Radiation Protection, Lydia Joyce Wilson May 2019

Framework For Algorithmically Optimizing Longitudinal Health Outcomes: Examples In Cancer Radiotherapy And Occupational Radiation Protection, Lydia Joyce Wilson

LSU Doctoral Dissertations

Background: Advancements in the treatment of non-infectious disease have enabled survival rates to steadily increase in recent decades (e.g., diabetes, heart disease, and cancer). Epidemiological studies have revealed that the treatments for these diseases can have life-threatening and/or life–altering effects. Thus, realizing the full beneficial potential of advanced treatments necessitates new tools to algorithmically consider all major components of the health outcome, including benefit and detriment. The goal of this dissertation was to develop a framework for improving projected health outcomes following planned radiation exposures in consideration of all beneficial and detrimental, early and late, and fatal and non-fatal …


Endorectal Digital Prostate Tomosynthesis, Joseph Robert Steiner May 2018

Endorectal Digital Prostate Tomosynthesis, Joseph Robert Steiner

LSU Doctoral Dissertations

Several areas of prostate cancer (PCa) management, such as imaging permanent brachytherapy implants or small, aggressive lesions, benefit from high image resolution. Current PCa imaging methods can have inadequate resolution for imaging these areas. Endorectal digital prostate tomosynthesis (endoDPT), an imaging method that combines an external x-ray source and an endorectal x-ray sensor, can produce three-dimensional images of the prostate region that have high image resolution compared to typical methods. This high resolution may improve PCa management and increase positive outcomes in affected men.

This dissertation presents the initial development of endoDPT, including system design, image quality assessment, and examples …


Development And Applications Of A Real-Time Magnetic Electron Energy Spectrometer For Use With Medical Linear Accelerators, Paul Ethan Maggi Dec 2017

Development And Applications Of A Real-Time Magnetic Electron Energy Spectrometer For Use With Medical Linear Accelerators, Paul Ethan Maggi

LSU Doctoral Dissertations

Purpose – This work presents a design for a real-time electron energy spectrometer, and provides data analysis methods and characterization of the real-time system. This system is intended for use with medical linear accelerators (linacs). The goal is 1 Hz acquisition of the energy range 4-25 MeV, reconstructed in 0.1 MeV increments.

Methods – Our spectrometer uses a nominal 0.54 T permanent magnet block as the dispersive element and scintillating fibers coupled to a CCD camera as the position sensitive detector. A broad electron beam produced by a linac is collimated by a 6.35 mm dimeter aperture at the entrance …