Program Information
How to Create a Robust Knowledge Based Rapidplan Model for Patients with Postoperation of Cervix Cancer?
C Ma1*, (1) Shandong Cancer Hospital and Institute, Jinan, Shandong Province
Presentations
SU-I-GPD-T-362 (Sunday, July 30, 2017) 3:00 PM - 6:00 PM Room: Exhibit Hall
Purpose: To demonstrate the feasibility of using a knowledge-based rapidplan model to generate new cervical intensity modulated radiation therapy (IMRT) plans.
Methods: A database of 113 cervical IMRT treatment plans were assembled to create a knowledge-based IMRT rapidplan model. Another 20 clinical cases were randomly selected to test the model. A comparision of the difference in the dose-volume histograms(DVH) between the semiautomated treatment plans and the original treatment plans were analyzed.
Results: On average, the new knowledge-based rapidplans are capable of achieving very comparable planning target volume coverage as the original plan, to within 1% as evaluated for D98, D95, and D1. Similarly, the dose to the rectum, the bladder and femoral heads are also comparable to the original plans. For the rectum, the mean and standard deviation of the dose percentage differences for D20, D30, and D50 are3.79%±8.31%, 4.00%±9.87%, and 1.52±10.89%, respectively. For the bladder, the mean and standard deviation of the dose percentage differences for D20, D30, and D50 are -2.43%±9.40%, -2.03%±10.17% and -2.94%±12.30%, respectively. For the femoral heads, the mean and standard deviation of the dose percentage differences for the left and right are 3.15%±18.29% and -3.18%±13.79%. A negative percentage difference indicates that the new plan has greater dose sparing as compared to the original plan.
Conclusion: We demonstrate a knowledge-based IMRT model can improve the efficiency of the treatment planning process while ensuring that high quality plans are developed.
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