Genetic algorithm based deliverable segments optimization for static intensity-modulated radiotherapy
Genetic algorithm based deliverable segments optimization for static intensity-modulated radiotherapy
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DOI：
10.1088/0031-9155/48/20/007
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发表时间：
2003-10-21
影响因子：
3.5
通讯作者：
Yao, DZ
中科院分区：
文献类型：
--
作者：
Li, YJ;Yao, J;Yao, DZ
The static delivery technique (also called step-and-shoot technique) has been widely used in intensity-modulated radiotherapy (IMRT) because of the simple delivery and easy quality assurance. Conventional static IMRT consists of two steps: first to calculate the intensity-modulated beam profiles using an inverse planning algorithm, and then to translate these profiles into a series of uniform segments using a leaf-sequencing tool. In order to simplify the procedure and shorten the treatment time of the static mode, an efficient technique, called genetic algorithm based deliverable segments optimization (GADSO), is developed in our work, which combines these two steps into one. Taking the pre-defined beams and the total number of segments per treatment as input, the number of segments for each beam, the segment shapes and weights are determined automatically. A group of interim modulated beam profiles quickly calculated using a conjugate gradient (CG) method are used to determine the segment number for each beam and to initialize segment shapes. A modified genetic algorithm based on a two-dimensional binary coding scheme is used to optimize the segment shapes, and a CG method is used to optimize the segment weights. The physical characters of a multileaf collimator, such as the leaves interdigitation limitation and leaves maximum over-travel distance, are incorporated into the optimization. The algorithm is applied to some examples and the results demonstrate that GADSO is able to produce highly conformal dose distributions using 20-30 deliverable segments per treatment within a clinically acceptable computation time.
