title: Accuracy of perfusion-CT in predicting malignant middle cerebral artery brain infarction.
abstract: BACKGROUND
  We performed a prospective study on patients with middle cerebral artery(MCA) ischemic stroke to evaluate the accuracy of perfusion-CT imaging(PCT) to predict the development of malignant brain infarction (MBI).
  
  
  METHODS
  106 patients(women 37 %, mean age 65 years)underwent native cranial computed tomography (CCT), CT angiography(CTA) and PCT after a median of 2 h after stroke onset. We assessed the patency of the MCA and the area of tissue ischemia (AIT)according to cerebral blood flow(CBF), cerebral blood volume (CBV) and time-to-peak (TTP)maps. Optimum sensitivity, specificity,positive (PPV) and negative predictive values (NPV) were calculated for the end-point MBI (= midline shift > 5 mm or decompressive surgery) by means of receiver operating characteristics(ROC).
  
  
  RESULTS
  20 patients (19 %)developed a MBI. In these patients,a larger AIT was found in all perfusion maps as compared to the remaining patients (p < 0.001). All perfusion maps had a very high NPV (95.4-98.4 %), a high sensitivity (85-95 %) and specificity (71.6-77.9 %) and only a moderate PPV (44-47.4 %). Best prediction was found for CBF maps with AIT of > 27.9 % of the hemisphere.
  
  
  CONCLUSIONS
  PCT allows the discrimination of patients without a relevant risk for MBI from those having a 50 % risk of MBI development. Due to the high sensitivity and specificity, PCT is a reliable tool in detecting MBI. Because of PCT's better availability, it is the method of choice at present for an early risk stratification of acute stroke patients.
authors.affiliation: Dept. of Neurology, University Hospital of Muenster, Albert-Schweitzer-Strasse 33, 48129 Muenster, Germany. dittrir@gmx.de
authors.forename: R
authors.initials: R
authors.lastname: Dittrich
authors.forename: S P
authors.initials: SP
authors.lastname: Kloska
authors.forename: T
authors.initials: T
authors.lastname: Fischer
authors.forename: E
authors.initials: E
authors.lastname: Nam
authors.forename: M A
authors.initials: MA
authors.lastname: Ritter
authors.forename: P
authors.initials: P
authors.lastname: Seidensticker
authors.forename: W
authors.initials: W
authors.lastname: Heindel
authors.forename: D G
authors.initials: DG
authors.lastname: Nabavi
authors.forename: E B
authors.initials: EB
authors.lastname: Ringelstein
mesh_terms: D000328:Adult; D000368:Aged; D001921:Brain / Q000098:blood supply / Q000000981:diagnostic imaging / Q000473:pathology; D020520:Brain Infarction / Q000000981:diagnostic imaging* / Q000473:pathology* / Q000503:physiopathology; D002533:Cerebral Angiography / Q000379:methods / Q000706:statistics & numerical data*; D002560:Cerebrovascular Circulation / Q000502:physiology; D003287:Contrast Media; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D020244:Infarction, Middle Cerebral Artery / Q000000981:diagnostic imaging* / Q000473:pathology* / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D020768:Middle Cerebral Artery / Q000000981:diagnostic imaging / Q000473:pathology / Q000503:physiopathology; D011237:Predictive Value of Tests; D011379:Prognosis; D012307:Risk Factors; D014057:Tomography, X-Ray Computed / Q000379:methods / Q000706:statistics & numerical data*
chemical_list: D003287:Contrast Media