Program Information
Anaysis of the Impact of Setup Uncertainties On Dose to the Organs at the Risk and Plan Robustness Using Normal Tissue Complication Probability in Passive Scattering Proton Beam Therapy
J Wang*, Y Li , X Zhang , H Li , M Gillin , X Zhu , N Sahoo , MD Anderson Cancer Ctr., Houston, TX
Presentations
SU-I-GPD-T-179 (Sunday, July 30, 2017) 3:00 PM - 6:00 PM Room: Exhibit Hall
Purpose: To quantify the effects of setup uncertainties on the dose to organs at risk (OAR) and plan robustness in passive scattering proton therapy treatment plans using NTCP model.
Methods: The dose distributions of passive scattering plans for four previously treated brain patients were calculated in Eclipse treatment planning system applying ±3 mm shift of the isocenter in x, y and z directions to account for setup uncertainties. An empirical variable RBE model was used to calculate BED distributions (Dose x RBE). Both physical dose and BED distributions were exported into Computation Environment for Radiotherapy Research (CERR) to calculate the NTCP of all these plans using Lyman-Kutcher-Burman model for the brainstem, whole brain and other OAR in the brain. The changes in NTCP (ΔNTCP) were evaluated as a metric to quantify the effect of setup uncertainties on OAR doses and plan robustness.
Results: Among the four patients, ΔNTCP for brainstem was in the range of 0.3 to 2% (8% to 37% relative increase) using the physical dose distribution, and 0.8 to 2 % (8% to 224% relative increase)for the BED distribution. The ΔNTCP were found to be negligibly small for the whole brain. The ΔNTCP with BED distribution was seen close to 1% for spinal cord for one case and 1.8% for the right hippocampus for another case with smaller changes for the physical dose distribution. The observed small ΔNTCP in the plans is attributed to the design of robust nominal plans where the OAR doses were kept well below their tolerance and are not being affected by the setup uncertainties.
Conclusion: It is found that NTCP model can be useful to evaluate the plan robustness under setup uncertainties. This model can also be applied to study the plan robustness under range and RBE uncertainties and to compare competing plans.
Funding Support, Disclosures, and Conflict of Interest: Varian
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