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A Plan Quality Metric for Evaluating Knowledge-Based Treatment Plans
V Chanyavanich1*, J Lo2, S Das3, (1) Emory University, ATLANTA, GA, (2) Duke University Medical Center, DURHAM, NC, (3) Duke Univ Medical Center, Durham, NC
SU-E-T-572 Sunday 3:00:00 PM - 6:00:00 PM Room: Exhibit HallPurpose: In prostate IMRT treatment planning, the variation in patient anatomy makes it difficult to estimate a priori the potentially achievable extent of dose reduction possible to the rectum and bladder. We developed a mutual information-based framework to estimate the achievable plan quality for a new patient, prior to any treatment planning or optimization.
Methods: The knowledge-base consists of 250 retrospective prostate IMRT plans. Using these prior plans, twenty query cases were each matched with five cases from the database. We propose a simple DVH plan quality metric (PQ) based on the weighted-sum of the areas under the curve (AUC) of the PTV, rectum and bladder. We evaluate the plan quality of knowledge-based generated plans, and established a correlation between the plan quality and case similarity.
Results: The introduced plan quality metric correlates well (r2 = 0.8) with the mutual similarity between cases. A matched case with high anatomical similarity can be used to produce a new high quality plan. Not surprisingly, a poorly matched case with low degree of anatomical similarity tends to produce a low quality plan, since the adapted fluences from a dissimilar case cannot be modified sufficiently to yield acceptable PTV coverage.
Conclusions: The plan quality metric is well-correlated to the degree of anatomical similarity between a new query case and matched cases. Further work will investigate how to apply this metric to further stratify and select cases for knowledge-based planning.
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