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Program Information

Robustness in Hypoxia-Guided IMRT Planning


A Roy

A Roy1*, O Nohadani2 , (1) Bowling Green State University, Bowling Green, OH, (2) Northwestern Univ, Evanston, IL

Presentations

SU-F-605-3 (Sunday, July 30, 2017) 2:05 PM - 3:00 PM Room: 605


Purpose: To investigate the inclusion of hypoxia and reoxygenation information into IMRT planning. A robust planning framework is compared to current clinical practices for a prostate cancer case.

Methods: Hypoxia reduces radiosensitivity of cells. Current practice to overcome this limited efficacy of treatment includes dose escalations to hypoxic tumor subregions by modifying the prescribed dose by a scaling factor based on initial PET scans. This factor remains constant throughout the treatment. In order to leverage reoxygenation of hypoxic cells, we employ a time-dependent scaling factor. The changes in reoxygenation are driven by perfusion and angiogenesis and their progression is uncertain. Therefore, we model the scaling factor to reside in a time-dependent uncertainty set. When mid-treatment PET scans are available, this set is updated to incorporate this observation. A robust optimization model with a time-dependent uncertainty set is solved for a finite set of clinically realistic scenarios.

Results: Weekly EUD are computed for all three plans: the robust plan shows an average improvement of 30% compared to the equal dose per fraction plan, which ignores hypoxia, and 4% compared to escalated plans, which neglects reoxygenation. For organ sparing, bladder and rectum D15 for the robust plan remains within 4% of the equal dose per fraction plan under nominal and worst-case conditions (deviating progression of reoxygenation than assumed), whereas the escalated plan increases bladder D15 by 11% and rectum by 19%.

Conclusion: It is possible to leverage reoxygenation information in order to produce temporally uniform dose distributions, which is the objective of fractionation. The uncertain progression can be modeled via a robust framework that improves plans by reducing dose to critical organs without sacrificing target coverage.


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