Approaches to four-dimensional intensity modulated radiation therapy planning with fraction constraints

Delal Dink, Purdue University

Abstract

Cancer is the second leading cause of death in the US preceded by cardiac disease. Almost all cancer patients depend on radiation therapy sometime throughout their treatment. Intensity modulated radiation therapy is a state-of-the-art method of delivering radiation that maximizes radiation exposure of the tumor and avoids excessive coverage of the surrounding healthy structures of the body. When image-guided radiation therapy starts to emerge as the future of radiation treatment, it opens the doors to the inside of the irradiated human body. It enlightens the radiation oncologist on the behavior of the tumor and the surrounding organs during the delivery and throughout the treatment as the body starts to respond to the therapy. The improvements in the technology encourage the oncologists to build on the years of experience and to adapt the practice accordingly. This project develops a method to link the information gained from the technology to the act of radiation delivery. The evolving data in imaging technology demonstrates that there is significant amount of organ movement during the delivery and noteworthy anatomical changes between the deliveries. While encountering these uncertainties, it is the responsibility of the therapy planners to make sure that every day plan obeys the dosage limits as well as the aggregated doses achieved at the end of the therapy. Hence, the planning problem is a scheduling problem that involves temporal uncertainties and it offers a new application for the scheduling principles employed by engineers for years. This dissertation proposes a novel rolling horizon strategy where daily and cumulative dose considerations are addressed and the plan is adapted routinely by incorporating the temporal anatomical changes of the patient. Furthermore, robustness of the algorithm is enhanced by temporal beam transformations. In addition to demonstrating the great impact of adaptive therapy planning, the method promises escalated tumor dose and better spared healthy organs as well.

Degree

Ph.D.

Advisors

Reklaitis, Purdue University.

Subject Area

Chemical engineering|Medical imaging|Oncology|Biophysics

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