Date of Award

2025

Degree Type

Dissertation

Degree Name

Doctor of Philosophy in Physics

Specialization

Biological Physics

Department

Physics

First Advisor

Michael Antosh

Abstract

Proton radiation therapy offers a highly precise method for cancer treatment, theoretically providing superior dose deposition characteristics compared to conventional X-ray radiation therapy. Its steep and finite dose fall-off region allows for superior tumor coverage while reducing, though not eliminating, dose to surrounding healthy tissue. However, its full potential is limited by range uncertainties, particularly those arising from the reliance on X-ray-based imaging methods called computed tomography (CT) for proton-based treatment. CT image Hounsfield Units (HU) must be converted to stopping power ratios (SPR) as these ratios are the clinically relevant value for accurately planning particle interactions during proton therapy. This conversion introduces uncertainties that necessitate larger error margins, ultimately reducing the precision and effectiveness of proton therapy.

This research specifically focuses on reducing uncertainties in HU-to-SPR conversion by developing a novel proton-based computed tomography (pCT) methodology that directly measures proton beam energy loss. Instead of relying on Bragg peak locations, this approach determines water-equivalent thickness (WET) through beam spread measurements. Monte Carlo simulations model the spot size of dual-energy proton beams passing through various materials, generating calibration curves for WET and material composition estimation. An algorithm then identifies the most-likely material traversed, constructs a sinogram, applies filtering, and back-projects the data to generate a CT slice.

The results demonstrate that proton energy loss can be directly measured through spot profile analysis. This leads to the conclusion that by further improving this method, uncertainties associated with HU-to-SPR conversion can be eliminated, as a pCT image generated using this approach would directly measure energy loss, which is inherently related to SPR. This method has the potential to improve proton therapy treatment planning and enhance patients’ clinical outcomes.

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