title: Z-score mapping method for extracting hypoattenuation areas of hyperacute stroke in unenhanced CT.
abstract: OBJECTIVE
  The purpose of this study was to develop a z-score mapping method on the basis of a voxel-by-voxel analysis to visualize hypoattenuation areas of hyperacute stroke on unenhanced computed tomographic (CT) images.
  
  
  METHODS
  The algorithm of the developed method consisted of five main steps: anatomic standardization, the construction of a normal reference database, calculation of the z scores, the elimination of false-positive areas, and the extraction of hypoattenuation areas. The obtained z-score map was then superimposed on the original CT images for identifying hypoattenuation areas of hyperacute stroke on the unenhanced CT images. The method was applied to 21 patients with infarctions of the middle cerebral artery territory <3 hours after symptom onset. The performance of the method was evaluated using receiver-operating characteristic analysis.
  
  
  RESULTS
  Hypoattenuation regions could be significantly distinguished from normal regions by z-score values (P < .0001). The area under the receiver-operating characteristic curve for distinction between 68 hypoattenuation regions and 142 normal regions was 0.834.
  
  
  CONCLUSIONS
  The developed method has the potential to accurately indicate high-signal intensity areas corresponding to hypoattenuation areas on CT images in the hyperacute stage of stroke.
authors.affiliation: Department of Radiological Technology, Graduate School of Health Sciences, Niigata University, Chuou-ku, Niigata, 951-8518, Japan. b07b401b@mail.cc.niigata-u.ac.jp
authors.forename: Noriyuki
authors.initials: N
authors.lastname: Takahashi
authors.forename: Du-Yih
authors.initials: DY
authors.lastname: Tsai
authors.forename: Yongbum
authors.initials: Y
authors.lastname: Lee
authors.forename: Toshibumi
authors.initials: T
authors.lastname: Kinoshita
authors.forename: Kiyoshi
authors.initials: K
authors.lastname: Ishii
mesh_terms: D000208:Acute Disease; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D003287:Contrast Media; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D020521:Stroke / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D003287:Contrast Media