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A Software Tool for Transition From Conventional to Automatic IMRT Treatment Planning

Ahmed, SBS1*, (1) Aga Khan University Hospital, Karachi, Sindh,

Presentations

(Sunday, 7/14/2019)  

Room: ePoster Forums

Purpose: In this study, we proposed a software plugin which works along the treatment planning systems to aid the automatic IMRT treatment planning of prostate and head and neck cases. The goal of project is to reduce the planning time while maintaining high quality of plans as per clinical standards.

Methods: In first step, a library will be developed by classification of data from previously optimized IMRT treatment plans.Plan properties like volume of PTV and OAR, beam angles, energies and monitor units will serve as limiter and help to make ensembles of treatment plans with similar properties. When a new plan with information of volumes of PTV and OAR will be chosen for automatic treatment planning, the algorithm starts searching for relevant ensemble within the library. The algorithm optimizes its search based on plan properties stated above in similar order, with the most weightage given to volume matching. A conformity analysis tool embedded in algorithm will evaluate the volumes of PTV and OAR of new plan with optimized plans in ensembles. Three plans with best conformity index values will be chosen and there DVH, MLC log files and gantry angles will be exported onto new plan and optimized. After optimization, plan will be evaluated by DVH tool for reference conditions and comparison would be made with previously optimized plans.

Results: It is estimated that, the proposed software solution will substantially reduce the optimization time with very similar and high dosimetry quality.

Conclusion: This system will provide a platform for clinics looking for a transition to automatic IMRT treatment planning from conventional. The long term objective would be to incorporate the artificial intelligence in the proposed toolkit and develop a decision support system for clinicians which will help them to pick the best optimized treatment plan in an efficient manner.

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