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Author ORCID Identifier

https://orcid.org/0009-0007-8084-0438

Date Available

10-30-2026

Year of Publication

2026

Document Type

Doctoral Dissertation

Degree Name

Doctor of Philosophy (PhD)

College

Medicine

Department/School/Program

Radiation Medicine

Faculty

Damodar Pokhrel

Faculty

Ali Soleimani-Meigooni

Abstract

Annually, about two million people are diagnosed with cancer in the United States alone, with nearly half receiving radiation therapy during their course of treatment. Advances in radiation therapy focuses on widening the therapeutic window by maximizing the tumor local control while minimizing normal tissue toxicities. Since the 1950s, spatially fractionated radiotherapy (SFRT) has been a niche treatment technique for treating large, unresectable tumors while sparing the skin tissue. Unlike conventional radiation therapy, which delivers a uniform dose to the tumor, SFRT utilizes an alternating pattern of high- and low-dose irradiation regions. However, significant challenges and knowledge gaps remain, most notably the lack of guidance and standardization in radiation physics and dosimetry as well as the incomplete knowledge of the underlying radiobiology of SFRT.

This thesis aims to improve understanding of the radiobiology of SFRT and to identify best practices in SFRT planning, evaluation, and delivery. First, we address the lack of standardization and clinical protocols within the SFRT community. By modeling our clinic’s outcome data, we developed a clinical protocol that will serve as a framework for other centers to use when treating SFRT patients. Second, we investigated the optimal geometric parameters for SFRT delivery in an in vitro study. We aim to provide an evidence-based rationale for selecting specific SFRT patterns over others. Finally, we introduce novel clinical techniques for SFRT planning and delivery to widen the therapeutic window.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2026.197

Archival?

Archival

Funding Information

This project was partially supported by pilot funding provided by the University of Kentucky Markey Cancer Center's Support Grant (P30 CA177558) and the Department of Radiation Medicine, which enabled services from the Biostatistics Shared Resource Facility, whose services were used in the conduct of this project.

Available for download on Friday, October 30, 2026

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