title: Clinical use of computed tomographic perfusion for the diagnosis and prediction of lesion growth in acute ischemic stroke.
abstract: BACKGROUND
  Computed tomography perfusion (CTP) mapping in research centers correlates well with diffusion-weighted imaging (DWI) lesions and may accurately differentiate the infarct core from ischemic penumbra. The value of CTP in real-world clinical practice has not been fully established. We investigated the yield of CTP-derived cerebral blood volume (CBV) and mean transient time (MTT) for the detection of cerebral ischemia and ischemic penumbra in a sample of acute ischemic stroke (AIS) patients.
  
  
  METHODS
  We studied 165 patients with initial clinical symptoms suggestive of AIS. All patients had an initial noncontrast head CT, CTP, CT angiogram (CTA), and follow-up magnetic resonance imaging (MRI) of the brain. The obtained perfusion images were used for image processing. CBV, MTT, and DWI lesion volumes were visually estimated and manually traced. Statistical analysis was conducted using R and SAS software.
  
  
  RESULTS
  All normal DWI sequences had normal CBV and MTT studies (N = 89). Seventy-three patients had acute DWI lesions. CBV was abnormal in 23.3% and MTT was abnormal in 42.5% of these patients. There was a high specificity (91.8%) but poor sensitivity (40.0%) for MTT maps predicting positive DWI. The Spearman correlation was significant between MTT and DWI lesions (ρ = 0.66; P > .0001) only for abnormal MTT and DWI lesions >0 cc. CBV lesions did not correlate with final DWI.
  
  
  CONCLUSIONS
  In real-world use, acute imaging with CTP did not predict stroke or DWI lesions with sufficient accuracy. Our findings argue against the use of CTP for screening AIS patients until real-world implementations match the accuracy reported from specialized research centers.
authors.affiliation: Department of Neurology, University of New Mexico, Albuquerque. Electronic address: bhuisagarate@salud.unm.edu.
authors.forename: Branko N
authors.initials: BN
authors.lastname: Huisa
authors.affiliation: Kaiser Permanente, San Diego.
authors.forename: William P
authors.initials: WP
authors.lastname: Neil
authors.affiliation: Clinical Translational Center, University of New Mexico, Albuquerque.
authors.forename: Ronald
authors.initials: R
authors.lastname: Schrader
authors.affiliation: Department of Neurology, Cedars Sinai Medical Center, Los Angeles.
authors.forename: Marcel
authors.initials: M
authors.lastname: Maya
authors.affiliation: Department of Neurology, Cedars Sinai Medical Center, Los Angeles.
authors.forename: Benedict
authors.initials: B
authors.lastname: Pereira
authors.affiliation: Scripps La Jolla Medical Center, La Jolla, California.
authors.forename: Nhu T
authors.initials: NT
authors.lastname: Bruce
authors.affiliation: Department of Neurology, Cedars Sinai Medical Center, Los Angeles.
authors.forename: Patrick D
authors.initials: PD
authors.lastname: Lyden
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001783:Blood Flow Velocity / Q000502:physiology; D001810:Blood Volume; D002545:Brain Ischemia / Q000175:diagnosis* / Q000000981:diagnostic imaging; D002533:Cerebral Angiography; D002544:Cerebral Infarction / Q000175:diagnosis / Q000000981:diagnostic imaging; D002560:Cerebrovascular Circulation; D038524:Diffusion Magnetic Resonance Imaging; D018450:Disease Progression; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D018810:Magnetic Resonance Angiography; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D020521:Stroke / Q000175:diagnosis* / Q000000981:diagnostic imaging; D014057:Tomography, X-Ray Computed / Q000379:methods*; D016896:Treatment Outcome