title: Automated subtraction CT angiography for visualization of the whole brain vasculature: a feasibility study.
abstract: OBJECTIVE
  To develop an automated computed tomography angiography (CTA) imaging protocol that allows visualization of the whole brain vasculature and evaluate the clinical usefulness of the technique for delineation of intracranial vessels in patients with cerebrovascular disorders.
  
  
  METHODS
  We prospectively included 100 patients who underwent automated subtraction CTA for suspected cerebrovascular disorders. The nonenhanced and contrast enhanced scans were obtained with the same table feeding speed. The x-ray tube start angles of the two scans were matched to enable accurate registration and subtraction of the CTA datasets. Subtracted CTA datasets were reformatted as three-dimensional volume rendering and maximum intensity projection images for further review. Two independent readers assessed the quality of subtraction and delineation of intracranial vessels. The visibility of ophthalmic arteries was also assessed.
  
  
  RESULTS
  Subtraction was successful in all patients. The image quality of bone removal was rated excellent in 95 patients, with no or minimal bone remnants. Incomplete bone removal was observed in five patients because of severe motions between the scans. In 97 of 100 patients, arterial segments at the circle of Willis could be clearly visualized. Excellent delineation of bilateral ophthalmic arteries was possible in 81 of 100 patients.
  
  
  CONCLUSIONS
  The whole brain vasculature would be clearly visualized by using the optimized automated CTA protocol. Our automated, single-source, dual-energy subtraction CTA protocol is a fully automated subtraction method that is capable of delineating major intracranial vessels as well as very small arteries.
authors.affiliation: Department of Neurology, The First Affiliated Hospital, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, 400016 Chongqing, China.
authors.forename: Qi
authors.initials: Q
authors.lastname: Li
authors.forename: Fajin
authors.initials: F
authors.lastname: Lv
authors.forename: Youdong
authors.initials: Y
authors.lastname: Wei
authors.forename: Tianyou
authors.initials: T
authors.lastname: Luo
authors.forename: Peng
authors.initials: P
authors.lastname: Xie
mesh_terms: D000465:Algorithms; D015901:Angiography, Digital Subtraction / Q000379:methods*; D002533:Cerebral Angiography / Q000379:methods*; D002536:Cerebral Arteries / Q000000981:diagnostic imaging*; D002561:Cerebrovascular Disorders / Q000000981:diagnostic imaging*; D005240:Feasibility Studies; 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; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: Brain vasculature; CT angiography; bone subtraction; single source CT