title: Implementation of a novel algorithm for generating synthetic CT images from magnetic resonance imaging data sets for prostate cancer radiation therapy.
abstract: OBJECTIVE
  To describe and evaluate a method for generating synthetic computed tomography (synCT) images from magnetic resonance simulation (MR-SIM) data for accurate digitally reconstructed radiograph (DRR) generation and dose calculations in prostate cancer radiation therapy.
  
  
  METHODS
  A retrospective evaluation was performed in 9 prostate cancer patients who had undergone MR-SIM in addition to CT simulation (CT-SIM). MR-SIM data were used to generate synCT images by using a novel, voxel-based weighted summation approach. A subset of patients was used for weight optimization, and the number of patients to use during optimization was determined. Hounsfield unit (HU) differences between CT-SIM and synCT images were analyzed via mean absolute error (MAE). Original, CT-based treatment plans were mapped onto synCTs. DRRs were generated, and agreement between CT and synCT-generated DRRs was evaluated via Dice similarity coefficient (DSC). Dose was recalculated, and dose-volume metrics and gamma analysis were used to evaluate resulting treatment plans.
  
  
  RESULTS
  Full field-of-view synCT MAE across all patients was 74.3 ± 10.9 HU with differences from CTs of 2.0 ± 8.1 HU and 11.9 ± 46.7 HU for soft tissue structures (prostate, bladder, and rectum) and femoral bones, respectively. Calculated DSCs for anterior-posterior and lateral DRRs were 0.90 ± 0.04 and 0.92 ± 0.05, respectively. Differences in D99%, mean dose, and maximum dose to the clinical target volume from CT-SIM dose calculations were 0.75% ± 0.35%, 0.63% ± 0.34%, and 0.54% ± 0.33%, respectively, for synCT-generated plans. Gamma analysis (2%/2 mm dose difference/distance to agreement) revealed pass rates of 99.9% ± 0.1% (range, 99.7%-100%).
  
  
  CONCLUSIONS
  Generated synCTs enabled accurate DRR generation and dose computation for prostate MR-only simulation. Dose recalculated on synCTs agreed well with original planning distributions. Further validation using a larger patient cohort is warranted.
authors.affiliation: Department of Radiation Oncology, Henry Ford Health System, Detroit, Michigan. Electronic address: jkim8@hfhs.org.
authors.forename: Joshua
authors.initials: J
authors.lastname: Kim
authors.affiliation: Department of Radiation Oncology, Henry Ford Health System, Detroit, Michigan.
authors.forename: Carri
authors.initials: C
authors.lastname: Glide-Hurst
authors.affiliation: Department of Radiation Oncology, Henry Ford Health System, Detroit, Michigan.
authors.forename: Anthony
authors.initials: A
authors.lastname: Doemer
authors.affiliation: Department of Radiation Oncology, Henry Ford Health System, Detroit, Michigan.
authors.forename: Ning
authors.initials: N
authors.lastname: Wen
authors.affiliation: Department of Radiation Oncology, Henry Ford Health System, Detroit, Michigan.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Movsas
authors.affiliation: Department of Radiation Oncology, Henry Ford Health System, Detroit, Michigan.
authors.forename: Indrin J
authors.initials: IJ
authors.lastname: Chetty
mesh_terms: D000465:Algorithms; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed / Q000379:methods*