title: Improved quality of computed tomography substitute derived from magnetic resonance (MR) data by incorporation of spatial information--potential application for MR-only radiotherapy and attenuation correction in positron emission tomography.
abstract: BACKGROUND
  Estimation of computed tomography (CT) equivalent data, i.e. a substitute CT (s-CT), from magnetic resonance (MR) images is a prerequisite both for attenuation correction of positron emission tomography (PET) data acquired with a PET/MR scanner and for dose calculations in an MR-only radiotherapy workflow. It has previously been shown that it is possible to estimate Hounsfield numbers based on MR image intensities, using ultra short echo-time imaging and Gaussian mixture regression (GMR). In the present pilot study we investigate the possibility to also include spatial information in the GMR, with the aim to improve the quality of the s-CT.
  
  
  METHODS
  MR and CT data for nine patients were used in the present study. For each patient, GMR models were created from the other eight patients, including either both UTE image intensities and spatial information on a voxel by voxel level, or only UTE image intensities. The models were used to create s-CT images for each respective patient.
  
  
  RESULTS
  The inclusion of spatial information in the GMR model improved the accuracy of the estimated s-CT. The improvement was most pronounced in smaller, complicated anatomical regions as the inner ear and post-nasal cavities.
  
  
  CONCLUSIONS
  This pilot study shows that inclusion of spatial information in GMR models to convert MR data to CT equivalent images is feasible. The accuracy of the s-CT is improved and the spatial information could make it possible to create a general model for the conversion applicable to the whole body.
authors.affiliation: Department of Radiation Sciences, Umeå University , Umeå , Sweden.
authors.forename: Adam
authors.initials: A
authors.lastname: Johansson
authors.forename: Anders
authors.initials: A
authors.lastname: Garpebring
authors.forename: Mikael
authors.initials: M
authors.lastname: Karlsson
authors.forename: Thomas
authors.initials: T
authors.lastname: Asklund
authors.forename: Tufve
authors.initials: T
authors.lastname: Nyholm
mesh_terms: D001918:Brachytherapy; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008962:Models, Theoretical; D009369:Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy; D010865:Pilot Projects; D049268:Positron-Emission Tomography; D011379:Prognosis; D058996:Quality Improvement; D011880:Radiotherapy Planning, Computer-Assisted; D061089:Radiotherapy, Image-Guided; D012044:Regression Analysis; D012307:Risk Factors; D014057:Tomography, X-Ray Computed; D047368:Tumor Burden