Room: Davidson Ballroom A
Purpose: We proposed a linear energy transfer (LET) guided robust optimization for intensity modulated proton therapy (IMPT). The method simultaneously considers the tumor and OAR LET and physical dose distributions, and patient setup and proton beam range uncertainties.
Methods: 17 patients with head and neck cancer were included in the retrospective study. Four organs-at-risk (OARs): cord, brain stem, brain, and oral cavity, were considered in the plan optimization. Three algorithms: voxel-wise worst-case robust optimization (RO), robust optimization with LET distribution constraints to OARs only (denoted RO(BS)), and LET-guided robust optimization to redistribute high LET distribution from OARs to tumors (LETRO) were used to generate IMPT plans. All three methods considered 9 uncertainty scenarios to evaluate plan robustness. The dose-volume histogram (DVH) indices, such as clinical target volume (CTV) D95% and D5%-D95%, cord Dmax, brain stem Dmax, brain Dmax, and oral cavity Dmean, were calculated. Plan robustness was quantified using the DVH band method. Similar dosimetric indices were derived for LET distributions. The Wilcoxon signed rank test was performed to measure the statistical significance of the difference among the three algorithms.
Results: Compared with RO and RO(BS), LETRO provided significantly better CTV LET distribution, while preserving the comparable physical dose distributions and plan robustness of CTV. LETRO achieved significantly better LET distributions in cord, brain, and oral cavity compared with RO. Compared with RO(BS), LETRO achieved comparable physical dose distribution in cord, brain, and oral cavity, and had better LET distribution in brain stem.
Conclusion: LETRO outperformed RO and RO(BS) algorithms, which optimized the LET and physical dose distributions simultaneously. It redistributed high LET from OARs to tumors to improve the biological killing of tumor cells without sacrificing the physical dose distributions and plan robustness. The LETRO has potentials to deliver a biologically optimized proton therapy for head and neck cancer.
Funding Support, Disclosures, and Conflict of Interest: This research was supported by the National Cancer Institute (NCI) Career Developmental Award K25CA168984, Arizona Biomedical Research Commission Investigator Award, t the Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, and the Kemper Marley Foundation. The authors have no relevant conflicts of interest to disclose.