Volume 8, Issue 5 (9-2020)                   IJRSM 2020, 8(5): 55-66 | Back to browse issues page

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moghadasi Z, Mowlavi A A, Zibandeh Gorji M, Mohammadi S. Using PSO algorithm optimization for planning 103Pd seeds brachytherapy positions. IJRSM 2020; 8 (5) :55-66
URL: http://rsm.kashanu.ac.ir/article-1-522-en.html
Payame Noor University, Mashhad Branch
Abstract:   (1271 Views)
Radiation therapy, is one of the treatments for cancer. Brachytherapy is a radiotherapeutic technique that a sealed radiation source is placed inside or next to the tissue and has become a mainstream treatment option for cancer. Achieving maximum dose to the gland as well as minimum injury to the adjacent tissues is a basic principle in radiation therapy. Sources configuration must be designed in such a way that the dose distribution agrees with treatment planning and the prescribed dose. Exact evaluation is necessary to avoid excessive dose to other organs especially organs at risk. Optimization algorithms are applied in preplanning treatment. The aim is to deliver a desire dose in the border of tumor while all of the points inside the tumor receive the absorbed dose more than the dose border values. The accuracy of optimization and finding the best position of seeds is so important in treatment planning. We used PSO algorithm to optimize the places of 103Pd seeds which are applied in the prostate brachytherapy. The algorithm was performed for desired tumor shape in various conditions. In circle and ellipsoid tumor with 5 and 40 desire seeds, more than 90% of points of border receive the prescribed dose. Moreover, the optimized characteristics of seeds and their best positions were determined. The results show that the PSO algorithm can be used for optimizing the position of interstitial implantation brachytherapy that so many seeds used. Distribution dose and isodose curve were studied to assurance delivering adequate dose to target volume while keeping healthy tissues. Few parameters, easy implementation and fast convergence around the global answer are advantages of this algorithm.
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Type of Study: Research | Subject: Special

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