title: Hemodynamic segmentation of MR perfusion images in patients with unilateral carotid stenosis using independent component analysis.
abstract: OBJECTIVE
  To assess spatiotemporal patterns of local perfusion in MR brain perfusion images for patients with unilateral carotid stenosis.
  
  
  METHODS
  MR perfusion images acquired from 12 patients with unilateral carotid stenosis were retrospectively segmented using independent component analysis. Regions of interest selected from the segmentation results were used to measure the time to peak (TTP), time to maximum of the residue curve (Tmax), and mean transit time (MTT) for arteries and brain parenchyma on normal and stenotic sides.
  
  
  RESULTS
  The tissue types that can be identified in segmentation results include normal artery, artery with proximal stenosis, normal brain parenchyma, delayed-perfusion brain parenchyma, vein and sinus, choroid plexus, cerebrospinal fluid, and leukoaraiosis. Concentration-time curves measured on normal and stenotic artery regions can be modeled as two arterial input functions. Unilateral carotid stenosis associated with either middle cerebral artery stenosis or poor collateral circulation at the circle of Willis resulted in increased differences of brain parenchyma TTP, Tmax, and MTT between normal and stenotic sides.
  
  
  CONCLUSIONS
  Independent component analysis on perfusion images of patients with unilateral carotid stenosis provides useful spatiotemporal information regarding blood supply to arteries and local perfusion of brain parenchyma.
authors.affiliation: Department of Biomedical Imaging and Radiological Sciences, National Yang Ming University, and Department of Radilogy, Taipei Veterans General Hospital, Taipei, Taiwan.
authors.forename: Yi-Hsuan
authors.initials: YH
authors.lastname: Kao
authors.forename: Michael Mu-Huo
authors.initials: MM
authors.lastname: Teng
authors.forename: Kuo-Ching
authors.initials: KC
authors.lastname: Liu
authors.forename: Io-Pong
authors.initials: IP
authors.lastname: Lam
authors.forename: Yu-Ching
authors.initials: YC
authors.lastname: Lin
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001783:Blood Flow Velocity; D016893:Carotid Stenosis / Q000150:complications / Q000175:diagnosis*; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D018487:Ventricular Dysfunction, Left / Q000175:diagnosis* / Q000209:etiology