J. Chen1, Y. Yang2, H. Feng1,3, C. E. Vargas1, N. Y. Yu1, J. C. M. Rwigema1, S. R. Keole1, S. A. Vora1, J. Shen1, and W. Liu1; 1Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ, 2Department of Radiation Oncology, the University of Miami, Miami, FL, 3College of Mechanical and Power Engineering, China Three Gorges University, Yichang, Hubei, China
Purpose/Objective(s): Historically, spot scanning proton therapy (SSPT) treatment planning utilizes dose volume constraints and linear-energy-transfer (LET) volume constraints separately to balance tumor control and organs-at-risk (OARs) protection. However, the synergistic biological effects between dose and LET should also be considered in the treatment planning. DLVH was constructed with physical dose (Gy) and LET (keV/µm) as independent variables. The normalized volume of the structure was projected as iso-volume lines in the dose-LET plane. DLVH depicts the complex interplay between the dose and LET distribution. Recent studies highlight the correlation between adverse events (AEs) and dose LET volume constraints (DLVCs) derived from dose DLVH-based AE study in prostate cancer treated with SSPT. We thus propose a novel DLVC-based robust optimization (DLVCRO) method for SSPT in treating prostate cancer to obtain a desirable joint dose and LET distribution to minimize AEs. Materials/
Methods: DLVCRO treats DLVC as soft constraints that control the shapes of the DLVH curves. It redistributes the overlap of high LET and dose from OARs to targets in a user defined way. Four prostate cancer patients were included in this retrospective study. Rectum, bladder, and femoral head were considered. DLVCRO is compared with the conventional robust optimization (RO) method. Plan robustness was quantified using the worst-case analysis method. Analogous to dose-volume histogram (DVH) indices, the xBD (the product of per voxel dose and LET)-volume histogram (xBDVH) indices characterizing the joint dose/LET distributions are also used. The Wilcoxon signed rank test was performed to measure statistical significance. Results: In the nominal scenario, DLVCRO significantly reduced xBD distributions in the rectum, bladder, and femoral head compared with RO (rectum: xBD_max: 178.85 vs 188.01, P=.038; bladder: xBD_max: 131.35 vs 146.67 P=.048; left femoral head: xBD_max:51.78 vs 54.47 P=.055 and had comparable plan robustness and physical dose in all OARs and targets, CTV: xBD_max: 228.66 vs 227.63 P=.394; xBD_mean: 162.64 vs 164.43 P=.409. Conclusion: DLVCRO simultaneously optimizes LET and physical dose distributions robustly. It upgrades 2D DVH-based to 3D DLVH-based treatment planning to adjust dose/LET distributions simultaneously to reduce AEs. DLVCRO is potentially a powerful tool to improve patient outcomes in SSPT.
