SU-F-T-352: Development of a Knowledge Based Automatic Lung IMRT Planning Algorithm with Non-Coplanar Beams.

PURPOSE: To improve the robustness of a knowledge based automatic lung IMRT planning method and to further validate the reliability of this algorithm by utilizing for the planning of clinical cases with non-coplanar beams. METHODS: A lung IMRT planning method which automatically determines both plan optimization objectives and beam configurations with non-coplanar beams has been reported previously. A beam efficiency index map is constructed to guide beam angle selection in this algorithm. This index takes into account both the dose contributions from individual beams and the combined effect of multiple beams which is represented by a beam separation score. We studied the effect of this beam separation score on plan quality and determined the optimal weight for this score.14 clinical plans were re-planned with the knowledge-based algorithm. Significant dosimetric metrics for the PTV and OARs in the automatic plans are compared with those in the clinical plans by the two-sample t-test. In addition, a composite dosimetric quality index was defined to obtain the relationship between the plan quality and the beam separation score. RESULTS: On average, we observed more than 15% reduction on conformity index and homogeneity index for PTV and V40 , V60 for heart while an 8% and 3% increase on V5 , V20 for lungs, respectively. The variation curve of the composite index as a function of angle spread score shows that 0.6 is the best value for the weight of the beam separation score. CONCLUSION: Optimal value for beam angle spread score in automatic lung IMRT planning is obtained. With this value, model can result in statistically the "best" achievable plans. This method can potentially improve the quality and planning efficiency for IMRT plans with no-coplanar angles.

Duke Scholars

Author Qingrong Wu Radiation Oncology