Author Type

Graduate Student

Date of Award

2019

Document Type

Thesis

Publication Status

Version of Record

Submission Date

October 2026

Thesis/Dissertation Advisor [Chair]

Shang, Charles

Thesis/Dissertation Co-Chair

Leventouri, Theodora

Abstract

The accuracy of proton dose computation in the treatment planning system relies on the conversion from the Hounsfield units (HU) of each voxel in the patient CT scan to the proton stopping power ratio (SPR). The aim of this study is to investigate the potential improvement in determining proton SPR using single energy computed tomography (SECT) to reduce the uncertainty in predicting the proton range in patients. Factors which may cause CT number variations in the calibration curve have been examined. The HU-SPR calibration curve was determined based on HU of human body tissues using the stoichiometric method. The uncertainties in SPR were divided into two major categories: The inherent uncertainty, and the CT number uncertainty. The root mean square errors of the inherent uncertainties were estimated 0.02%, 0.61% and 0.26% for lung tissues, soft tissues (excluding Thyroid), and bone tissues, respectively. The total uncertainties due to the inherent uncertainty and CT imaging errors were estimated 1.50%. The average calibration curve of two sized phantoms (head and body) were used in the treatment planning system to mitigate beam hardening effect through the attenuating media. A higher accuracy of the SPR prediction using the stoichiometric method is suggested through comparison with the predicted SPRs that derived from the direct calibration approach.

Extent

59 p.

Comments

Includes bibliography.|Thesis (M.S.)--Florida Atlantic University, 2019.|FAU Electronic Theses and Dissertations Collection|Includes bibliography.

Identifier

FA00013374

Format

pdf

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