研究生: |
陳孟君 Chen, Meng-Chun |
---|---|
論文名稱: |
Beam Angle and Fluence Map Optimization Model in Intensity Modulated Radiation Therapy 強度調控放射治療之射束角度及強度最佳化模式 |
指導教授: |
溫于平
Wen, Ue-Pyng |
口試委員: | |
學位類別: |
碩士 Master |
系所名稱: |
工學院 - 工業工程與工程管理學系 Department of Industrial Engineering and Engineering Management |
論文出版年: | 2009 |
畢業學年度: | 97 |
語文別: | 英文 |
論文頁數: | 44 |
中文關鍵詞: | 最佳化 、強度調控放射治療 、射束角度 、調強圖譜 、劑量-體積限制 、混合整數規劃 |
外文關鍵詞: | Optimization, Intensity Modulated Radiation Therapy (IMRT), Beam Angle, Fluence Map, Dose-volume Constraint, Mixed Integer Programming |
相關次數: | 點閱:2 下載:0 |
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放射線療法為常見的癌症治療方式。強度調控放射治療(Intensity Modulated Radiation Therapy, IMRT)是近年以來新發展的技術,它可以藉由調節射束強度,將高劑量集中在癌細胞上,並且同時減少周圍組織的劑量。IMRT治療計畫的優劣取決於射束方向及其射束強度,然而,在目前的放射治療中,最適射束角度的選取是依據治療物理師的經驗及直覺。
為了提供治療物理師最佳化治療計畫、減少計算時間及增加治療品質,本論文首先以分割方法去計算在每個voxel中,從不同射束角度所累積的劑量,然後使用混合整數規劃方法同時最佳化射束角度及其強度,另外,我們也將劑量-體積及臨床上不選取對角的經驗加入限制式。最後,與目前最佳化治療計畫進行比較,實驗結果證明本研究所提出的方法於重要器官所接收到的劑量及計算時間皆有明顯的改善。
Currently, radiation therapy is a common treatment for some specific tumors in the treatments of cancer. Intensity modulated radiation therapy (IMRT) is a widely adopted new radiation therapy tool in recently years, which can deliver high radiation doses to the tumor while reducing sparing of surrounding normal tissues by modulate radiation intensity across beams. The optimal IMRT treatment planning depends on the collection of directions and corresponding intensities. However, in current practice of IMRT, beam angle selection is accomplished by a trial-and-error approach based on the treatment planner’s experience or intuition.
In this thesis, in order to assist the planner to optimize IMRT treatment planning efficiently, reduce the computational time and improve the quality of the treatment, we code a program to pre-calculate the radiation dose in each voxel by the form of discretization. We then present a mathematical model to optimize beam angle and fluence map simultaneously by mixed integer programming approach. In addition, we consider the practical experience of the planner and dose-volume constraints in the proposed model to improve the quality of the treatment. According to the results of the experiment, we show that the performance of our method to solve IMRT treatment planning is better than previous works in decreasing radiation dose of organs at risk and computational time.
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