title: Measurement in the angiography suite: evaluation of vessel sizing techniques.
abstract: BACKGROUND
  Accurate vessel size measurement is important for neurointervention. Modern angiographic equipment offers various two-dimensional (2D) and 3D measurement methods that have not been systematically evaluated for accuracy and reliability.
  
  
  OBJECTIVE
  To evaluate these methods using anthropomorphic vessel phantoms.
  
  
  METHODS
  Tubing of known sizes (2-5 mm, 1 mm increments) was embedded in 3D-printed skulls to simulate the middle cerebral artery, internal carotid artery, and basilar artery. Each phantom was imaged to gain 3D DSA, 2D DSA, and DynaCT images. Three identical measurement locations were identified on each simulated vessel. Eight measurement methods (four 2D, three 3D, and one DynaCT) were evaluated. Measurements were performed by three independent experienced users on three separate occasions. Intraclass correlation and independent non-parametric analysis were carried out to evaluate the reliability and accuracy of these measurement methods.
  
  
  RESULTS
  Better reliability was noted for the automatic measurement methods than for the corresponding manual measurement methods. The mean differences with the ground truth for all methods ranged from -0.12 to 0.03 with small SEs (0.02-0.03) and SDs (0.10-0.18). The smallest absolute mean differences were achieved in two automatic measurement methods based on 2D manual calibration and 3D images. In comparison with these two methods, results of measurements based on 2D autocalibration were statistically different.
  
  
  CONCLUSIONS
  In our study, automatic analysis using 3D or 2D was the preferred measurement method. Manual calibration on 2D angiograms is necessary to improve the measurement accuracy. It is not known how our results may pertain to other angiographic systems.
authors.affiliation: Department of Neurosurgery, Changhai Hospital, Second Military Medical University, Shanghai, China Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA.
authors.forename: Pengfei
authors.identifier: http://orcid.org/0000-0002-6154-3602
authors.initials: P
authors.lastname: Yang
authors.affiliation: Siemens Medical Solutions, Inc, Hoffman Estates, Illinois, USA.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Schafer
authors.affiliation: Siemens Medical Solutions, Inc, Hoffman Estates, Illinois, USA.
authors.forename: Kevin
authors.initials: K
authors.lastname: Royalty
authors.affiliation: Department of Neurosurgery, University of Wisconsin, Madison, Wisconsin, USA.
authors.forename: Azam
authors.initials: A
authors.lastname: Ahmed
authors.affiliation: Department of Neurosurgery, University of Wisconsin, Madison, Wisconsin, USA.
authors.forename: David
authors.initials: D
authors.lastname: Niemann
authors.affiliation: Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA.
authors.forename: Charles
authors.initials: C
authors.lastname: Strother
mesh_terms: D015901:Angiography, Digital Subtraction / Q000379:methods*; D001488:Basilar Artery / Q000000981:diagnostic imaging; D002343:Carotid Artery, Internal / Q000000981:diagnostic imaging; D002533:Cerebral Angiography / Q000379:methods*; D000072226:Computed Tomography Angiography / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D020768:Middle Cerebral Artery / Q000000981:diagnostic imaging; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D013223:Statistics as Topic
keywords: Artery; Flow Diverter; Stent; Technique