title: The utility of deformable image registration for small artery visualisation in contrast-enhanced whole body MR angiography.
abstract: OBJECTIVE
  An investigation was carried out into the effect of three image registration techniques on the diagnostic image quality of contrast-enhanced magnetic resonance angiography (CE-MRA) images.
  
  
  METHODS
  Whole-body CE-MRA data from the lower legs of 27 patients recruited onto a study of asymptomatic atherosclerosis were processed using three deformable image registration algorithms. The resultant diagnostic image quality was evaluated qualitatively in a clinical evaluation by four expert observers, and quantitatively by measuring contrast-to-noise ratios and volumes of blood vessels, and assessing the techniques' ability to correct for varying degrees of motion.
  
  
  RESULTS
  The first registration algorithm ('AIR') introduced significant stenosis-mimicking artefacts into the blood vessels' appearance, observed both qualitatively (clinical evaluation) and quantitatively (vessel volume measurements). The two other algorithms ('Slicer' and 'SEMI'), based on the normalised mutual information (NMI) concept and designed specifically to deal with variations in signal intensity as found in contrast-enhanced image data, did not suffer from this serious issue but were rather found to significantly improve the diagnostic image quality both qualitatively and quantitatively, and demonstrated a significantly improved ability to deal with the common problem of patient motion.
  
  
  CONCLUSIONS
  This work highlights both the significant benefits to be gained through the use of suitable registration algorithms and the deleterious effects of an inappropriate choice of algorithm for contrast-enhanced MRI data. The maximum benefit was found in the lower legs, where the small arterial vessel diameters and propensity for leg movement during image acquisitions posed considerable problems in making accurate diagnoses from the un-registered images.
authors.affiliation: National Centre for Advanced Medical Imaging (CAMI), St. James's Hospital/School of Medicine, Trinity College Dublin, Ireland.
authors.forename: Daniel
authors.initials: D
authors.lastname: Foley
authors.affiliation: Medical Ultrasound Physics Group, School of Physics/IEO & FOCAS Institutes, Dublin Institute of Technology, Kevin's Street, Dublin 8, Ireland.
authors.forename: Jacinta E
authors.initials: JE
authors.lastname: Browne
authors.affiliation: Centre for Medical Image Computing, Department of Medical Physics and Bioengineering, University College London, UK; Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China.
authors.forename: Xiahai
authors.initials: X
authors.lastname: Zhuang
authors.affiliation: National Centre for Advanced Medical Imaging (CAMI), St. James's Hospital/School of Medicine, Trinity College Dublin, Ireland.
authors.forename: Barry
authors.initials: B
authors.lastname: Sheane
authors.affiliation: National Centre for Advanced Medical Imaging (CAMI), St. James's Hospital/School of Medicine, Trinity College Dublin, Ireland.
authors.forename: Dearbhail
authors.initials: D
authors.lastname: O'Driscoll
authors.affiliation: National Centre for Advanced Medical Imaging (CAMI), St. James's Hospital/School of Medicine, Trinity College Dublin, Ireland.
authors.forename: Daniel
authors.initials: D
authors.lastname: Cannon
authors.affiliation: National Centre for Advanced Medical Imaging (CAMI), St. James's Hospital/School of Medicine, Trinity College Dublin, Ireland.
authors.forename: Niall
authors.initials: N
authors.lastname: Sheehy
authors.affiliation: National Centre for Advanced Medical Imaging (CAMI), St. James's Hospital/School of Medicine, Trinity College Dublin, Ireland.
authors.forename: James F
authors.initials: JF
authors.lastname: Meaney
authors.affiliation: National Centre for Advanced Medical Imaging (CAMI), St. James's Hospital/School of Medicine, Trinity College Dublin, Ireland. Electronic address: faganan@tcd.ie.
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Fagan
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D001158:Arteries / Q000473:pathology*; D050197:Atherosclerosis / Q000175:diagnosis / Q000473:pathology*; D003251:Constriction, Pathologic; D003287:Contrast Media / Q000737:chemistry*; D003952:Diagnostic Imaging / Q000379:methods; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007866:Leg / Q000473:pathology; D018810:Magnetic Resonance Angiography / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008875:Middle Aged; D009068:Movement; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results
chemical_list: D003287:Contrast Media
keywords: Atherosclerosis; Contrast-enhanced; Deformable image registration; Normalised mutual information; Peripheral arterial disease; Whole body MR angiography