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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 52726 (01)
- University: Sharif University of Technology
- Department: Industrial Engineering
- Advisor(s): Najafi, Mehdi; Rafiee, Majid
- Abstract:
- Nowadays, radiation therapy is one of the most common methods for the cancer treatment. Intensity Modulated Radiation Therapy(IMRT) is a novel technique of radiation therapy that aims to delivere sufficient dose to cancerous tissues while sparing healthy organs. There are various uncertainties in radiation therapy problems, including uncertainty about device setup, device errors, interfraction and intrafraction motions. One of the most important uncertainties is the movement of the tumor during the treatment process(intrafraction motion), as this displacement may cause the cancer tissue to not receive sufficient dose and also to damage the healthy tissue due to a violation of their dose tolerance threshold. Therefore, it may cause irreparable damage to the patient's body. In addition, tumor growth during the treatment process is also of great importance, which can influence the decision about how and how much radiation must be delivered to the patient’s body. This thesis proposes a robust bi-objective optimization model with Conditional Value-at-Risk(C-VaR) constraints and consideration of tumor growth and biologically effect dose. This model takes into account the uncertainty of breast cancer motion due to respiration. The tumor movement in this study was divided into five phases according to the patient's inhale and exhale. The probability of the body being placed in each of these phases as well as the dose received by the target volume and the heart tissue, which is the critical normal tissue, has different values. The purpose of this model is to find the optimal radiation intensity from each beamlet in each treatment session and to obtain the optimal number of treatment fractions. Finally, the proposed model is solved by an efficient heuristic algorithm and its Pareto solution set is produced by the Epsilon constraint method. The results of this Model illustrate the effects of the dose delivered to the target volume and healthy tissues so that the physician can make the best decision according to the patient's condition. Also, the effect of different parameters on the final solution of the model is investigated in order to evaluate the performance of the model under different conditions
- Keywords:
- Fluence Map Optimization ; Intensity Modulated Radiation Therapy (IMRT) ; Robust Optimization ; Conditional Value at Risk ; Heuristic Algorithm ; Treatment Planning
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