SU-E-T-642: PTV Is the Voxel-Wise Worst-Case of CTV in Prostate Photon Therapy

Authors


Abstract

Purpose:

To examine the adequacy of the planning target volume (PTV) dose distribution as the worst-case representation of clinical target volume (CTV) dose distribution in prostate volumetric-modulated arc therapy (VMAT) plans.

Methods:

Ten intact prostate cancer cases treated by VMAT at our institution were randomly selected. Isocenter was shifted in the three cardinal directions by a displacement equal to the PTV expansion on the CTV (±3 mm) for a total of six shifted plans per original plan. Rotationally-perturbed plans were generated with a couch rotation of ±1° to simulate patient yaw. The eight perturbed dose distributions were recalculated in the treatment planning system using the same, fixed fluence map as the original plan. The voxel-wise worst-case CTV dose distribution was constructed from the minimum value per voxel from the eight perturbed doses. The resulting dose volume histograms (DVH) were evaluated for statistical correlation between the worst-case CTV and nominal PTV dose distributions based on D95% by Wilcoxon signed-rank test with significance level p ≤ 0.05.

Results:

Inspection demonstrates the PTV DVH in the nominal dose distribution is bounded by the CTV DVH in the worst-case dose distribution. Comparison of D95% for the two dose distributions by Wilcoxon signed-rank test gives p = 0.131. Therefore the null hypothesis cannot be rejected since the difference in median values is not statistically significant.

Conclusion:

The assumption that the nominal dose distribution for PTV represents the worst-case dose distribution for CTV appears valid for the ten plans under examination. Although the worst-case dose distribution is unphysical since the dose per voxel is chosen independently, it serves as a lower bound for the possible CTV coverage. Furthermore, this is consistent with the unphysical nature of the PTV. Minor discrepancies between the two dose distributions are expected since the dose cloud is not strictly static.

Funding Support: NIH/NCI K25CA168984, Eagles Cancer Research Career Development, The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, Mayo ASU Seed Grant, and The Kemper Marley Foundation

Ancillary