A Robust 4D Treatment Planning Approach for Lung Radiotherapy
C Pokhrel*, E Heath, Ryerson University, Toronto, OntarioSU-E-T-589 Sunday 3:00PM - 6:00PM Room: Exhibit Hall
4D treatment planning optimizes the cumulative dose delivered over the whole respiratory cycle to generate a plan that compensates for a patients individual respiratory motion. However, changes in the time spent in the each respiratory state may render a 4D plan invalid. We introduced and evaluate two robust treatment planning approaches to compensate for respiratory motion.
A 4D optimization method was developed which optimizes the phase-weighted dose distribution. Two robust 4D treatment planning approaches were tested: (1) planning on the average motion pdf (AVE_PDF); and (2) combining 4D plans designed on the "worst case" pdfs (WC_PDF). The sensitivity of nominal and robust 4D treatment plans to respiratory motion variations was tested for two scenarios where respiratory phase weights were modified to model changes in amplitude as well as the relative proportion of the respiratory cycle spent inhaling vs. exhaling.
The DVHs of robust plans show less sensitivity to variation in breathing pattern. Compared to the nominal 4D plan, robust plans improve the V95 by 2 to 6 Gy and CTV min dose by 1 to 5 Gy.
Robust 4D plan can be designed either using average pdf approach or worst case pdf
approach. We find that nominal 4D plans are very sensitive to the variation in respiration pattern while robust 4D plans are less sensitive under the similar changes. As compared to static 4D plan, healthy tissue sparing is also better in robust plan.
Funding Support, Disclosures, and Conflict of Interest: This research is supported by the Natural Sciences and Engineering Research Council of Canada (NSERC).
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