Graduation Year

2026

Document Type

Dissertation

Degree

Ph.D.

Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department

Physics

Major Professor

Jacqueline Andreozzi, Ph.D.

Co-Major Professor

Ghanim Ullah, Ph.D.

Committee Member

Eduardo Moros, Ph.D.

Committee Member

Ibrahim Oraqait, Ph.D.

Committee Member

Iman Washington, Ph.D.

Keywords

dosimetry, medicine, optics, photonics

Abstract

Cherenkov radiation imaging is a burgeoning field of optical imaging that has become a promising, non-invasive, technique that allows the visualization of radiation delivery during external beam radiotherapy. This form of imaging has opened the door to real-time and retrospective treatment verification and sparked a plethora of research aimed at improving the utility. This dissertation investigates possible clinical implementations and limitations of Cherenkov radiation imaging within a high-throughput cancer clinic serving a diverse patient population. The central motivation is the need to advance Cherenkov radiation imaging as a reliable tool for clinical use by improving its quantitative accuracy and applicability across a range of realistic treatment conditions. It begins by examining patient-specific factors that influence signal formation, particularly the role of skin pigmentation, and develops a calibration framework to improve agreement between Cherenkov emission and delivered dose. Building on this, the work explores the use of Cherenkov imaging for treatment verification in complex delivery scenarios, focusing on bilateral breast radiotherapy, where accurate assessment of beam geometry is important to prevent overlapping beams that can cause increased dose to a particularly important area of the chest. Additional studies investigate how common clinical practices and environmental conditions, such as the common use of sheet bolus and variations in temperature, influence the detected optical signal. Together, these efforts aim to better characterize the factors that affect Cherenkov imaging in common clinical practice. By doing so, this dissertation helps to establish a more complete framework for Cherenkov imagery interpretation and supports the technology’s integration as a robust method for treatment verification in modern radiation oncology.

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