Difference between revisions of "A Multi-Objective optimization Framework for Treatment Planning of permanent Prostate Branchytheraphy"
(New page: '''Cyrus Angelo Selga''' Thesis (M.S. Industrial Engineering)--University of the Philippines Diliman.-2010 '''Abstract''' According to statistics from the Department of Health, prostate...)
m (A MULTI-OBJECTIVE OPTIMIZATION FRAMEWORK FOR TREATMENT PLANNING OF PERMANENT PROSTATE BRACHYTHERAPY moved to A Multi-Objective optimization Framework for Treatment Planning of permanent Prostate Branchytheraphy)
Revision as of 23:32, 6 September 2011
Cyrus Angelo Selga
Thesis (M.S. Industrial Engineering)--University of the Philippines Diliman.-2010
According to statistics from the Department of Health, prostate cancer is the 2nd leading cancer case among Filipino men. An effective treatment strategy is radiation therapy, wherein radiation is delivered to the prostate while attempting to minimize exposure to the nearly organs. Radiation therapy can be delivered either through an external nean or internally using radionuclide sources, the latter technique being called brachytherapy. An important step in brachytherapy is the treatment planning stage wherein the source positions are optimized in order to achieve a quality treatment plan. Quality however, involves several dimensions and previous research efforts used the a priori decision-making approach, particularly the weighted-sum method. This approach, unfortunately, does not allow the decision-maker to gain an insight into the tradeoff relationships among the different treatment objectives. In this paper, an a posteriori multi-objective optimization framework is proposed. The model is solved using the Normal-Boundary Intersection technique, which has been extended to accommodate both the a posteriori approach and its integration with the a priori approach. Software implementation used and open-source solver from the Computational Infrastructure for Operations research. Results from actual patient data provided by the Urology Center of the Philippines show that multiple quality treatment plans which use less resources compared to manual planning can be obtained. Further research in algorithm runtime is acquired in order to generate the whole set of treatment plans within the time frame of manual planning.