# American Institute of Mathematical Sciences

July  2008, 4(3): 453-475. doi: 10.3934/jimo.2008.4.453

## An on-line adaptive radiation therapy system for intensity modulated radiation therapy: An application of multi-objective optimization

 1 Dept Elect. Engin. & Computer Science, Case Western Reserve University, Cleveland, OH, United States, United States 2 Department of Radiation Oncology, Duke University Medical Center, Durham, NC, United States, United States

Received  September 2007 Revised  May 2008 Published  July 2008

Radiation therapy (RT) is a non-invasive and highly effective treatment option for Prostate cancer. The goal is to deliver the prescription dose to the tumor (prostate) while minimizing the damages to the surrounding healthy organs namely bladder, rectum, and femoral heads. One major drawback of the conventional RT is that organ positions and shapes vary from day to day and that the original plan that is based on pre-treatment CT images may no longer be appropriate for treatment in subsequent sessions. The usual remedy is to include some margins surrounding the target when planning the treatment. Though this image guided radiation therapy technique allows in-room correction and can eliminate patient setup errors, the uncertainty due to organ deformation still remains. Performing a plan re-optimization will take about 30 minutes which makes it impractical to perform an online correction. In this paper, we develop an Adaptive Radiation Therapy (ART) system for online adaptive IMRT planning to compensate for the internal motion during the course of the prostate cancer treatment. It allows the treatment plan to be quickly modified based on the anatomy-of-the-day.
Citation: Danthai Thongphiew, Vira Chankong, Fang-Fang Yin, Q. Jackie Wu. An on-line adaptive radiation therapy system for intensity modulated radiation therapy: An application of multi-objective optimization. Journal of Industrial & Management Optimization, 2008, 4 (3) : 453-475. doi: 10.3934/jimo.2008.4.453
 [1] Adam Glick, Antonio Mastroberardino. Combined therapy for treating solid tumors with chemotherapy and angiogenic inhibitors. Discrete & Continuous Dynamical Systems - B, 2020  doi: 10.3934/dcdsb.2020343 [2] Sören Bartels, Jakob Keck. Adaptive time stepping in elastoplasticity. Discrete & Continuous Dynamical Systems - S, 2021, 14 (1) : 71-88. doi: 10.3934/dcdss.2020323 [3] Li-Bin Liu, Ying Liang, Jian Zhang, Xiaobing Bao. A robust adaptive grid method for singularly perturbed Burger-Huxley equations. Electronic Research Archive, 2020, 28 (4) : 1439-1457. doi: 10.3934/era.2020076 [4] Hirokazu Ninomiya. Entire solutions of the Allen–Cahn–Nagumo equation in a multi-dimensional space. Discrete & Continuous Dynamical Systems - A, 2021, 41 (1) : 395-412. doi: 10.3934/dcds.2020364 [5] Shun Zhang, Jianlin Jiang, Su Zhang, Yibing Lv, Yuzhen Guo. ADMM-type methods for generalized multi-facility Weber problem. Journal of Industrial & Management Optimization, 2020  doi: 10.3934/jimo.2020171 [6] Ripeng Huang, Shaojian Qu, Xiaoguang Yang, Zhimin Liu. Multi-stage distributionally robust optimization with risk aversion. Journal of Industrial & Management Optimization, 2021, 17 (1) : 233-259. doi: 10.3934/jimo.2019109 [7] Hongguang Ma, Xiang Li. Multi-period hazardous waste collection planning with consideration of risk stability. Journal of Industrial & Management Optimization, 2021, 17 (1) : 393-408. doi: 10.3934/jimo.2019117 [8] Gang Bao, Mingming Zhang, Bin Hu, Peijun Li. An adaptive finite element DtN method for the three-dimensional acoustic scattering problem. Discrete & Continuous Dynamical Systems - B, 2020  doi: 10.3934/dcdsb.2020351 [9] A. M. Elaiw, N. H. AlShamrani, A. Abdel-Aty, H. Dutta. Stability analysis of a general HIV dynamics model with multi-stages of infected cells and two routes of infection. Discrete & Continuous Dynamical Systems - S, 2020  doi: 10.3934/dcdss.2020441 [10] Zuliang Lu, Fei Huang, Xiankui Wu, Lin Li, Shang Liu. Convergence and quasi-optimality of $L^2-$norms based an adaptive finite element method for nonlinear optimal control problems. Electronic Research Archive, 2020, 28 (4) : 1459-1486. doi: 10.3934/era.2020077

2019 Impact Factor: 1.366