Genetic algorithm based deliverable segments optimization for static intensity-modulated radiotherapy

被引:27
作者
Li, YJ
Yao, J
Yao, DZ
机构
[1] Univ Elect Sci & Technol China, Sch Life Sci & Technol, Chengdu 610054, Peoples R China
[2] Topslane Inc, Pleasant Hill, CA 94523 USA
关键词
MULTIPLE LOCAL MINIMA; MULTILEAF COLLIMATOR; DOSE OPTIMIZATION; IMRT; CONSTRAINTS; MODEL; TIME;
D O I
10.1088/0031-9155/48/20/007
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
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.
引用
收藏
页码:3353 / 3374
页数:22
相关论文
共 42 条
[1]   Optimization of intensity modulated radiotherapy under constraints for static and dynamic MLC delivery [J].
Alber, M ;
Nüsslin, F .
PHYSICS IN MEDICINE AND BIOLOGY, 2001, 46 (12) :3229-3239
[2]   The use of mixed-integer programming for inverse treatment planning with pre-defined field segments [J].
Bednarz, G ;
Michalski, D ;
Houser, C ;
Huq, MS ;
Xiao, Y ;
Anne, PR ;
Galvin, JM .
PHYSICS IN MEDICINE AND BIOLOGY, 2002, 47 (13) :2235-2245
[3]  
Börgers C, 1999, INVERSE PROBL, V15, P1115, DOI 10.1088/0266-5611/15/5/301
[4]   X-RAY FIELD COMPENSATION WITH MULTILEAF COLLIMATORS [J].
BORTFELD, TR ;
KAHLER, DL ;
WALDRON, TJ ;
BOYER, AL .
INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 1994, 28 (03) :723-730
[5]   Hardware-sensitive optimization for intensity modulated radiotherapy [J].
Cho, PS ;
Marks, RJ .
PHYSICS IN MEDICINE AND BIOLOGY, 2000, 45 (02) :429-440
[6]   A multiobjective gradient-based dose optimization algorithm for external beam conformal radiotherapy [J].
Cotrutz, C ;
Lahanas, M ;
Kappas, C ;
Baltas, D .
PHYSICS IN MEDICINE AND BIOLOGY, 2001, 46 (08) :2161-2175
[7]   Minimizing delivery time and monitor units in static IMRT by leaf-sequencing [J].
Crooks, SM ;
McAven, LF ;
Robinson, DF ;
Xing, L .
PHYSICS IN MEDICINE AND BIOLOGY, 2002, 47 (17) :3105-3116
[8]   Multiple local minima in radiotherapy optimization problems with dose-volume constraints [J].
Deasy, JO .
MEDICAL PHYSICS, 1997, 24 (07) :1157-1161
[9]  
DELAMAZA M, 1993, PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON GENETIC ALGORITHMS, P124
[10]   Genetic and geometric optimization of three-dimensional radiation therapy treatment planning [J].
Ezzell, GA .
MEDICAL PHYSICS, 1996, 23 (03) :293-305