Z-score mapping method for extracting hypoattenuation areas of hyperacute stroke in unenhanced CT

• Published in: Academic radiology Vol. 17; no. 1; p. 84
• Main Authors: Takahashi, Noriyuki, Tsai, Du-Yih, Lee, Yongbum, Kinoshita, Toshibumi, Ishii, Kiyoshi
• Format: Journal Article
• Language: English
• Published: United States 01.01.2010
• Subjects: Acute Disease; Aged; Aged, 80 and over; Algorithms; Artificial Intelligence; Cluster Analysis; Contrast Media; Female; Humans; Male; Middle Aged; Pattern Recognition, Automated - methods; Radiographic Image Enhancement - methods; Radiographic Image Interpretation, Computer-Assisted - methods; Reproducibility of Results; Sensitivity and Specificity; Stroke - diagnostic imaging; Tomography, X-Ray Computed - methods
• ISSN: 1878-4046
• DOI: 10.1016/j.acra.2009.07.011

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. 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. 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. 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.