title: Exploratory Study of 4D versus 3D Robust Optimization in Intensity Modulated Proton Therapy for Lung Cancer.
abstract: OBJECTIVE
  The purpose of this study was to compare the impact of uncertainties and interplay on 3-dimensional (3D) and 4D robustly optimized intensity modulated proton therapy (IMPT) plans for lung cancer in an exploratory methodology study.
  
  
  METHODS
  IMPT plans were created for 11 nonrandomly selected non-small cell lung cancer (NSCLC) cases: 3D robustly optimized plans on average CTs with internal gross tumor volume density overridden to irradiate internal target volume, and 4D robustly optimized plans on 4D computed tomography (CT) to irradiate clinical target volume (CTV). Regular fractionation (66 Gy [relative biological effectiveness; RBE] in 33 fractions) was considered. In 4D optimization, the CTV of individual phases received nonuniform doses to achieve a uniform cumulative dose. The root-mean-square dose-volume histograms (RVH) measured the sensitivity of the dose to uncertainties, and the areas under the RVH curve (AUCs) were used to evaluate plan robustness. Dose evaluation software modeled time-dependent spot delivery to incorporate interplay effect with randomized starting phases of each field per fraction. Dose-volume histogram (DVH) indices comparing CTV coverage, homogeneity, and normal tissue sparing were evaluated using Wilcoxon signed rank test.
  
  
  RESULTS
  4D robust optimization plans led to smaller AUC for CTV (14.26 vs 18.61, respectively; P=.001), better CTV coverage (Gy [RBE]) (D95% CTV: 60.6 vs 55.2, respectively; P=.001), and better CTV homogeneity (D5%-D95% CTV: 10.3 vs 17.7, respectively; P=.002) in the face of uncertainties. With interplay effect considered, 4D robust optimization produced plans with better target coverage (D95% CTV: 64.5 vs 63.8, respectively; P=.0068), comparable target homogeneity, and comparable normal tissue protection. The benefits from 4D robust optimization were most obvious for the 2 typical stage III lung cancer patients.
  
  
  CONCLUSIONS
  Our exploratory methodology study showed that, compared to 3D robust optimization, 4D robust optimization produced significantly more robust and interplay-effect-resistant plans for targets with comparable dose distributions for normal tissues. A further study with a larger and more realistic patient population is warranted to generalize the conclusions.
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona. Electronic address: Liu.Wei@mayo.edu.
authors.forename: Wei
authors.initials: W
authors.lastname: Liu
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
authors.forename: Steven E
authors.initials: SE
authors.lastname: Schild
authors.affiliation: Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, Houston, Texas.
authors.forename: Joe Y
authors.initials: JY
authors.lastname: Chang
authors.affiliation: Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, Houston, Texas.
authors.forename: Zhongxing
authors.initials: Z
authors.lastname: Liao
authors.affiliation: Division of Health Sciences Research, Mayo Clinic Arizona, Phoenix, Arizona.
authors.forename: Yu-Hui
authors.initials: YH
authors.lastname: Chang
authors.affiliation: Department of Radiation Physics, the University of Texas MD Anderson Cancer Center, Houston, Texas.
authors.forename: Zhifei
authors.initials: Z
authors.lastname: Wen
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
authors.forename: Jiajian
authors.initials: J
authors.lastname: Shen
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
authors.forename: Joshua B
authors.initials: JB
authors.lastname: Stoker
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
authors.forename: Xiaoning
authors.initials: X
authors.lastname: Ding
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
authors.forename: Yanle
authors.initials: Y
authors.lastname: Hu
authors.affiliation: Department of Radiation Physics, the University of Texas MD Anderson Cancer Center, Houston, Texas.
authors.forename: Narayan
authors.initials: N
authors.lastname: Sahoo
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Rochester, Rochester, Minnesota.
authors.forename: Michael G
authors.initials: MG
authors.lastname: Herman
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
authors.forename: Carlos
authors.initials: C
authors.lastname: Vargas
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
authors.forename: Sameer
authors.initials: S
authors.lastname: Keole
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
authors.forename: William
authors.initials: W
authors.lastname: Wong
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
authors.forename: Martin
authors.initials: M
authors.lastname: Bues
mesh_terms: D019540:Area Under Curve; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging / Q000473:pathology / Q000532:radiotherapy*; D019583:Dose Fractionation, Radiation; D056973:Four-Dimensional Computed Tomography; D006801:Humans; D021621:Imaging, Three-Dimensional; D008175:Lung Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology / Q000532:radiotherapy*; D009068:Movement; D058958:Organs at Risk; D061766:Proton Therapy / Q000379:methods*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*; D012062:Relative Biological Effectiveness; D012119:Respiration; D012189:Retrospective Studies; D047368:Tumor Burden; D035501:Uncertainty