title: A new genetic algorithm technique in optimization of permanent 125I prostate implants.
abstract: Real time optimized treatment planning at the time of the implant is desirable for ultrasound-guided transperineal 125I permanent prostate implants. Currently available optimization algorithms are too slow to be used in the operating room. The goal of this work is to develop a robust optimization algorithm, which is suitable for such application. Three different genetic algorithms (sGA, sureGA and securGA) were developed and compared in terms of the number of function evaluations and the corresponding fitness. The optimized dose distribution was achieved by searching the best seed distribution through the minimization of a cost function. The cost function included constraints on the periphery dose of the planned target volume, the dose uniformity within the target volume, and the dose to the critical structure. Adjustment between the peripheral dose, the dose uniformity and critical structure dose can be achieved by varying the weighting factors in the cost function. All plans were evaluated in terms of the dose nonuniformity ratio, the conformation number and the dose volume histograms. Among these three GA algorithms, the securGA provided the best performance. Within 2500 function evaluations, the near optimum results were obtained. For a large target volume (5 cm x 4 cm x 4.5 cm) including urethra with 20 needles, the computer time needed for the optimization was less than 5 min on a HP735 workstation. The results showed that once the best set of parameters was found, they were applicable for all sizes of prostate volume. For a fixed needle geometry, the optimized plan showed much better dose distribution than that of nonoptimized plan. If the critical structure was considered in the optimization, the dose to the critical structure could be minimized. In the cases of irregular and skewed needle geometry, the optimized treatment plans were almost as good as ideal needle geometry. It is concluded that this new genetic algorithm (securGA) allows for an efficient and rapid optimization of dose distribution, which is suitable for real time treatment planning optimization for ultrasound-guided prostate implant.
authors.affiliation: Department of Radiation Oncology, SUNY at Stony Brook 11794-7028, USA. jyang@randoc.som.sunysb.edu
authors.forename: G
authors.initials: G
authors.lastname: Yang
authors.forename: L E
authors.initials: LE
authors.lastname: Reinstein
authors.forename: S
authors.initials: S
authors.lastname: Pai
authors.forename: Z
authors.initials: Z
authors.lastname: Xu
authors.forename: D L
authors.initials: DL
authors.lastname: Carroll
mesh_terms: D000465:Algorithms; D001918:Brachytherapy / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D007457:Iodine Radioisotopes / Q000627:therapeutic use*; D008297:Male; D008957:Models, Genetic; D011471:Prostatic Neoplasms / Q000473:pathology / Q000532:radiotherapy*; D011880:Radiotherapy Planning, Computer-Assisted; D014465:Ultrasonics; D014521:Urethra / Q000528:radiation effects
chemical_list: D007457:Iodine Radioisotopes