Research On Treatment Planning Algorithm Of Seed Implant Brachytherapy For Thoracic And Abdominal Tumors

This research takes the key technologies of an algorithm for inverse treatment planning in radioactive seeds implantation for tumors in the chest and abdomen as research object,proposes an algorithm for dose planning based on Inverse Planning Simulated Annealing(IPSA)algorithm framework,the dose received by Organs at Risk(OAR)and the number of needles were further optimized.It aims at improving the reliability and accuracy of inverse treatment planning in radioactive seeds implantation for tumors in the chest and abdomen.The main research contents and achievements of this study are as follows:Firstly,a dose planning method based on inverse planning simulated annealing algorithm is proposed.Through the demand for dose distribution in PTV and the analysis of the principle of simulated annealing algorithm,constructing a combination of three kinds of dose parameters of the evaluation function,designing three different kinds of state transition strategy,establishing a seeds management methods and determining the key parameter values according to the experimental data and the optimization theory.The algorithm is superior to the successful surgical plan in clinical practice through the verification of real cases.It can achieve the dose requirements for tumor inactivation,while reducing cold zone(low dose area)and hot zone(high dose area).Secondly,the optimization strategies for the dose received by OAR and the number of needles are proposed.For the dose received by organs at risk,two optimization strategies of single organ at risk and multiple organs at risk were adopted in according to the actual situation.An adaptive adjustment weight algorithm was proposed,which could well adapt to tumors and organs at risk with different shapes,volumes and locations.A range combination strategy was adopted for optimizing the number of needles and a second simulated annealing algorithm was used to further optimize the dose planning.It is verified by real cases that the algorithm is superior to traditional simulated annealing and clinical successful surgical planning.It could reduce the dose received by organs at risk and the number of puncture needles while ensuring the dose requirements of tumor.Finally,a dose planning system was developed.The system mainly included image processing,dose planning and result storage function modules,which could generate seeds distribution scheme according to CT(Computed Tomography)images and then assist doctors to make clinical planning.An algorithm for generating new data sets is designed,which can generate new data sets according to original cases.which verified the stability and execution efficiency of the system.The stability and efficiency of the system are verified.