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Robustness of Biological Dose Distribution in Intensity Modulated Carbon Ion Therapy: A Monte Carlo Study

N Qin

N Qin*, X Jia , The University of Texas Southwestern Medical Center, Dallas, TX


SU-I-GPD-T-180 (Sunday, July 30, 2017) 3:00 PM - 6:00 PM Room: Exhibit Hall

Purpose: Because of highly conformal dose distribution and sharp dose fall off at the tumor boundary in particle therapy, robustness is an important aspect when evaluating the quality of a treatment plan. Comparing to proton therapy, robustness of a carbon ion therapy plan is less examined. In addition, biological effect in carbon beams may exert impact on the plan robustness. In this study, we investigate the robustness of intensity modulated carbon therapy (IMCT) plans with respect to setup errors and stopping power ratio (SPR) uncertainties.

Methods: A prostate cancer patient treated with two laterally opposed fields was investigated. A well-tested in-house developed GPU-accelerated Monte Carlo (MC) engine for carbon therapy was used for pencil-beam dose calculation. A treatment plan was generated via inverse biological plan optimization. Assuming 3% SPR uncertainty and setup errors of 2 mm in magnitude with 26 different directions, biological doses of the treatment plan were recalculated for all testing scenarios. Impact on dose volume histograms (DVHs) of these uncertainties was investigated by comparing with the original DVHs.

Results: We calculated relative variation of CTV D95 of biological dose. For setup errors, D95 varied from -2.3% to 1.1% depending on the shift direction. A much bigger impact was observed for SPR uncertainties. D95 varied from -14.1% to 3.8%. This can be ascribed to the fact that SPR variation affects the range of each pencil beam and the height of each pristine Bragg peak. The components of mixed radiation at each voxel in CTV were also changed, causing significant variation in biological dose.

Conclusion: Biological aspect in carbon ion therapy reduces IMCT plan robustness, particularly with respect to SPR uncertainty. Simply adding margin to CTV may not be sufficient. It is necessary to include robustness considerations into treatment plan optimization.

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