title: Fully automated derivation of coronary artery calcium scores and cardiovascular risk assessment from contrast medium-enhanced coronary CT angiography studies.
abstract: OBJECTIVE
  Performance evaluation of a fully automated system for calculating computed tomography (CT) coronary artery calcium scores from contrast medium-enhanced coronary CT angiography (cCTA) studies.
  
  
  METHODS
  One hundred and twenty-seven patients (58 ± 11 years, 71 men) who had undergone cCTA as well as an unenhanced CT calcium scoring study where included. Calcium scores were computed from cCTA by an automated image processing algorithm and compared with calcium scores obtained by standard manual assessment of unenhanced CT calcium scoring studies. Results were compared vis-a-vis (1) absolute calcium score values, (2) age-, gender- and race-dependent percentiles, and (3) commonly used calcium score risk classification categories.
  
  
  RESULTS
  One hundred and nineteen out of 127 (93.7%) studies were successfully processed. Mean Agatston calcium score values obtained by traditional non-contrast CT calcium scoring studies and derived from contrast medium-enhanced cCTA did not significantly differ (235.6 ± 430.5 vs 262.0 ± 499.5; P > 0.05). Calcium score risk categories and Multi-Ethnic Study of Atherosclerosis (MESA) percentiles showed very high correlation (Spearman rank correlation coefficient = 0.97, P < 0.0001/0.95, P < 0.0001) between the two approaches.
  
  
  CONCLUSIONS
  Calcium score values automatically computed from cCTA are highly correlated with standard unenhanced CT calcium scoring studies. These results suggest a radiation dose- and time-saving potential when deriving calcium scores from cCTA studies without a preceding unenhanced CT calcium scoring study.
authors.affiliation: Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Drive, Charleston, SC 29425-2260, USA.
authors.forename: Ullrich
authors.initials: U
authors.lastname: Ebersberger
authors.forename: Dov
authors.initials: D
authors.lastname: Eilot
authors.forename: Roman
authors.initials: R
authors.lastname: Goldenberg
authors.forename: Alon
authors.initials: A
authors.lastname: Lev
authors.forename: J Reid
authors.initials: JR
authors.lastname: Spears
authors.forename: Garrett W
authors.initials: GW
authors.lastname: Rowe
authors.forename: Nicholas Y
authors.initials: NY
authors.lastname: Gallagher
authors.forename: William T
authors.initials: WT
authors.lastname: Halligan
authors.forename: Philipp
authors.initials: P
authors.lastname: Blanke
authors.forename: Marcus R
authors.initials: MR
authors.lastname: Makowski
authors.forename: Aleksander W
authors.initials: AW
authors.lastname: Krazinski
authors.forename: Justin R
authors.initials: JR
authors.lastname: Silverman
authors.forename: Fabian
authors.initials: F
authors.lastname: Bamberg
authors.forename: Alexander W
authors.initials: AW
authors.lastname: Leber
authors.forename: Ellen
authors.initials: E
authors.lastname: Hoffmann
authors.forename: U Joseph
authors.initials: UJ
authors.lastname: Schoepf
mesh_terms: D000465:Algorithms; D002114:Calcinosis / Q000150:complications / Q000000981:diagnostic imaging*; D003287:Contrast Media; D017023:Coronary Angiography / Q000379:methods*; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging* / Q000209:etiology; D005260:Female; D006801:Humans; D007472:Iohexol / Q000031:analogs & derivatives*; D008297:Male; D008875:Middle Aged; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012307:Risk Factors; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D003287:Contrast Media; D007472:Iohexol; C038192:iopromide