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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhu Lin Zhou Ling-hong Wang Zhuo-yu |
| Copyright Year | 2007 |
| Description | Author affiliation: Sch. of Biomed. Eng., Southern Med. Univ., Guangzhou (Zhu Lin; Zhou Ling-hong; Wang Zhuo-yu) |
| Abstract | This paper analyzed and compared the two kinds of objective function which based on dose and equivalent uniform dose (EUD).Both of them were applied to optimize the IMRT plan for lung cancer. The prescription dose for target was 80Gy, the tolerance dose for organ at risk and normal tissue were 30Gy and 50Gy. Genetic algorithm was selected and the population size, number of generation, mutation rate and crossover frequency were severally 101, 100, 0.008, 0.8. There were five beam orientations: 0deg, 45deg, 90deg, 130deg and 315deg. It was found that EUD-based criteria provided better target coverage and was capable of improving the sparing of critical structure beyond the specified requirements. The penalty function led to much-improved target dose homogeneity. The calculated equivalent uniform dose for organ at risk, normal tissue and tumor were 8.27Gy, 34.96Gy and 84.13Gy. The corresponding data for the dose-based plan were 14.10Gy, 35.20Gy and 90.12Gy. Equivalent uniform dose based objective function need only a small number of parameters and allowed exploration of a much larger universe of solutions. It had nice derivability and convexity. It also could be a surrogate of biologic index such as tumor control probability and normal tissue complication probability. |
| Starting Page | 1169 |
| Ending Page | 1172 |
| File Size | 295148 |
| Page Count | 4 |
| File Format | |
| ISBN | 1424411203 |
| DOI | 10.1109/ICBBE.2007.302 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-07-06 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Constraint optimization Lungs Genetic mutations Biological tissues Frequency Biological control systems Neoplasms Biomedical engineering Cancer Genetic algorithms |
| Content Type | Text |
| Resource Type | Article |
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