title: Improving the prediction of final infarct size in acute stroke with bolus delay-corrected perfusion MRI measures.
abstract: OBJECTIVE
  To investigate whether bolus delay-corrected dynamic susceptibility contrast (DSC) perfusion MRI measures allowed a more accurate estimation of eventual infarct volume in 14 acute stroke patients using a predictive tissue classifier algorithm.
  
  
  METHODS
  Tissue classification was performed using a expectation maximization and k-means clustering algorithm utilizing diffusion and T2 measures (diffusion-weighted imaging [DWI], apparent diffusion coefficient [ADC], and T2) combined with uncorrected perfusion measures cerebral blood flow ((CBF) and mean transit time [MTT]), bolus delay-corrected perfusion measures (cCBF and cMTT), and bolus delay-corrected perfusion indices (cCBF and cMTT with bolus delay).
  
  
  RESULTS
  The mean similarity index (SI), a kappa-based correlation statistic reflecting the pixel-by-pixel classification agreement between predicted and 30-day T2 lesion volumes, were 0.55 +/- 0.19, 0.61 +/- 0.15 (P < 0.02) and 0.60 +/- 0.17 (P <0.03), respectively. Spearman's correlation coefficients, comparing predicted and final lesion volumes were 0.56 (P < 0.05), 0.70 (P < 0.01), and 0.84 (P < 0.001), respectively. We found a more significant correlation between predicted infarct volumes derived from bolus delay-corrected perfusion measures than from conventional perfusion measures when combined with diffusion measures and compared with final lesion volumes measured on 30-day T2 MRI scans.
  
  
  CONCLUSIONS
  Bolus delay-corrected perfusion measures enable an improved prediction of infarct evolution and evaluation of the hemodynamic status of neuronal tissue in acute stroke.
authors.affiliation: Centre for Magnetic Resonance, University of Queensland, Brisbane, Australia. Stephen.Rose@cmr.uq.edu.au
authors.forename: Stephen E
authors.initials: SE
authors.lastname: Rose
authors.forename: Andrew L
authors.initials: AL
authors.lastname: Janke
authors.forename: Mark
authors.initials: M
authors.lastname: Griffin
authors.forename: Mark W
authors.initials: MW
authors.lastname: Strudwick
authors.forename: Simon
authors.initials: S
authors.lastname: Finnigan
authors.forename: James
authors.initials: J
authors.lastname: Semple
authors.forename: Jonathan B
authors.initials: JB
authors.lastname: Chalk
mesh_terms: D000208:Acute Disease; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001783:Blood Flow Velocity; D001810:Blood Volume; D002560:Cerebrovascular Circulation; D038524:Diffusion Magnetic Resonance Imaging; D005260:Female; D006801:Humans; D020244:Infarction, Middle Cerebral Artery / Q000175:diagnosis* / Q000473:pathology / Q000503:physiopathology; D018810:Magnetic Resonance Angiography; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests