title: Technical Note: MRI only prostate radiotherapy planning using the statistical decomposition algorithm.
abstract: OBJECTIVE
  In order to enable a magnetic resonance imaging (MRI) only workflow in radiotherapy treatment planning, methods are required for generating Hounsfield unit (HU) maps (i.e., synthetic computed tomography, sCT) for dose calculations, directly from MRI. The Statistical Decomposition Algorithm (SDA) is a method for automatically generating sCT images from a single MR image volume, based on automatic tissue classification in combination with a model trained using a multimodal template material. This study compares dose calculations between sCT generated by the SDA and conventional CT in the male pelvic region.
  
  
  METHODS
  The study comprised ten prostate cancer patients, for whom a 3D T2 weighted MRI and a conventional planning CT were acquired. For each patient, sCT images were generated from the acquired MRI using the SDA. In order to decouple the effect of variations in patient geometry between imaging modalities from the effect of uncertainties in the SDA, the conventional CT was nonrigidly registered to the MRI to assure that their geometries were well aligned. For each patient, a volumetric modulated arc therapy plan was created for the registered CT (rCT) and recalculated for both the sCT and the conventional CT. The results were evaluated using several methods, including mean average error (MAE), a set of dose-volume histogram parameters, and a restrictive gamma criterion (2% local dose/1 mm).
  
  
  RESULTS
  The MAE within the body contour was 36.5 ± 4.1 (1 s.d.) HU between sCT and rCT. Average mean absorbed dose difference to target was 0.0% ± 0.2% (1 s.d.) between sCT and rCT, whereas it was -0.3% ± 0.3% (1 s.d.) between CT and rCT. The average gamma pass rate was 99.9% for sCT vs rCT, whereas it was 90.3% for CT vs rCT.
  
  
  CONCLUSIONS
  The SDA enables a highly accurate MRI only workflow in prostate radiotherapy planning. The dosimetric uncertainties originating from the SDA appear negligible and are notably lower than the uncertainties introduced by variations in patient geometry between imaging sessions.
authors.affiliation: Department of Medical Radiation Physics, Lund University, Malmö 205 02, Sweden and Spectronic Medical AB, Helsingborg 254 67, Sweden.
authors.forename: Carl
authors.initials: C
authors.lastname: Siversson
authors.affiliation: Spectronic Medical AB, Helsingborg 254 67, Sweden; Department of Radiation Physics, Skåne University Hospital, Lund 214 28, Sweden; and Department of Medical Radiation Physics, Lund University, Lund 214 28, Sweden.
authors.forename: Fredrik
authors.initials: F
authors.lastname: Nordström
authors.affiliation: Spectronic Medical AB, Helsingborg 254 67, Sweden.
authors.forename: Terese
authors.initials: T
authors.lastname: Nilsson
authors.affiliation: Department of Radiation Sciences, Umeå University, Umeå 901 85, Sweden.
authors.forename: Tufve
authors.initials: T
authors.lastname: Nyholm
authors.affiliation: Department of Radiation Sciences, Umeå University, Umeå 901 85, Sweden.
authors.forename: Joakim
authors.initials: J
authors.lastname: Jonsson
authors.affiliation: Department of Oncology, Skåne University Hospital, Lund University, Lund 214 28, Sweden.
authors.forename: Adalsteinn
authors.initials: A
authors.lastname: Gunnlaugsson
authors.affiliation: Department of Medical Radiation Physics, Lund University, Malmö 205 02, Sweden.
authors.forename: Lars E
authors.initials: LE
authors.lastname: Olsson
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed