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Intensity-Modulated Radiation Therapy (IMRT) mathematically forms a large-scale optimization problem. The development of an IMRT plan is computationally expensive resulting in time-consuming, inefficient, and difficult to develop high-quality IMRT plans. By combining prior knowledge with proposed novel measures derived from both Overlap Volume Histogram (OVH) descriptors and Dose Volume Histograms (DVHs), a novel quality control method for IMRT planning is proposed to assure the high quality of IMRT plan. Clinical approved nasopharyngeal IMRT plans were employed for the experiments, where the reference plan is firstly retrieved from IMRT plan database for each query case by using measures derived from both OVH descriptors and DVHs. Then the DVHs of the reference plan are served as additional goals for the IMRT plan re-optimization. The experimental results show that the proposed method can effectively pick out those IMRT plans, whose quality could be improved substantially (i.e. the doses of their Clinical Targets Volume (CTV) could be effectively increased) and the dose of their Organs at Risk (OARs) could be reduced after the IMRT plan has being re-optimized. In conclusion, the proposed methods can effectively guarantee the high quality of the IMRT planning.

A study of quality control method for IMRT planning based on prior knowledge and novel measures derived from both OVHs and DVHs