title: Fully automated postprocessing carries a risk of substantial overestimation of perfusion deficits in acute stroke magnetic resonance imaging.
abstract: OBJECTIVE
  Due to the risk of rater bias and time restrictions in clinical practice, an automated approach to delineation of hypoperfused tissue in patients with acute ischemic stroke would be preferred to a manual one. We tested the hypothesis that existing software solutions, on account of numerous artifacts, produce hypoperfused tissue even in a cohort of patients with no ischemia.
  
  
  METHODS
  Thirty-nine patients, all admitted for exclusion of cerebral ischemia or hemorrhage and without a final diagnosis of stroke imaged between September 2008 and May 2009 were included in the study. Using 3 different software packages (PerfScape/NeuroScape, PMA and Stroketool), perfusion maps of mean transit time, cerebral blood flow and T(max) were created for each patient. Three different thresholds were applied to each parameter map, and subsequent volumes of hypoperfused tissue were calculated.
  
  
  RESULTS
  The median volume of hypoperfused tissue for all the subjects was 92.9 ml (interquartile range, IQR: 13.3-323.4 ml) when calculated by PerfScape/NeuroScape, 30.42 ml (IQR: 13.9-71.4 ml) when calculated by PMA and 78.71 ml (IQR: 40.3-140.8 ml) when calculated by Stroketool. The volumes derived via the different software applications mostly showed only a weak-to-moderate association with each other (Spearman's correlation coefficient between 0.02 and 0.76).
  
  
  CONCLUSIONS
  Although automated protocols show promise, the programs Stroketool, PerfScape and PMA require substantial improvement in order to be able to automatically and reliably differentiate between patients with a credible region of ischemia-related hypoperfusion and those without.
authors.affiliation: Center for Stroke Research Berlin, Charité - University Medicine Berlin, Germany. ivana.galinovic@charite.de
authors.forename: Ivana
authors.initials: I
authors.lastname: Galinovic
authors.forename: Peter
authors.initials: P
authors.lastname: Brunecker
authors.forename: Ann-Christin
authors.initials: AC
authors.lastname: Ostwaldt
authors.forename: Carina
authors.initials: C
authors.lastname: Soemmer
authors.forename: Benjamin
authors.initials: B
authors.lastname: Hotter
authors.forename: Jochen B
authors.initials: JB
authors.lastname: Fiebach
mesh_terms: D000328:Adult; D000368:Aged; D016477:Artifacts; D057205:Automation, Laboratory; D002560:Cerebrovascular Circulation; D005260:Female; D005858:Germany; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D018810:Magnetic Resonance Angiography; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012984:Software; D020521:Stroke / Q000175:diagnosis* / Q000473:pathology / Q000503:physiopathology