title: Computer-aided stenosis detection at coronary CT angiography: effect on performance of readers with different experience levels.
abstract: OBJECTIVE
  To evaluate the effect of a computer-aided detection (CAD) algorithm for coronary CT angiography (cCTA) on the performance of readers with different experience levels.
  
  
  METHODS
  We studied 50 patients (18 women, 58 ± 11 years) who had undergone cCTA and quantitative coronary angiography (QCA). Eight observers with varying experience levels evaluated all studies for ≥50 % coronary artery stenosis. After 3 months, the same observers re-evaluated all studies, this time guided by a CAD system. Their performance with and without the CAD system (sensitivity, specificity, positive predictive value and negative predictive value) was assessed using the Likelihood Ratio Χ(2) test both at the per-patient and per-vessel levels.
  
  
  RESULTS
  The sensitivity of the CAD system alone for stenosis detection was 71 % per-vessel and 100 % per-patient. There were 54 false positive (FP) findings within 199 analyzed vessels, most of them associated with non-obstructive (<50 %) lesions. With CAD, one (out of three, 33 %) inexperienced reader's per-patient sensitivity and negative predictive value significantly improved from 79 % to 100 % (P = 0.046) and from 90 % to 100 % (P = 0.034), respectively. Other readers' performance indices showed no statistically significant change.
  
  
  CONCLUSIONS
  Our results suggest that CAD can improve some inexperienced readers' sensitivity for diagnosing coronary artery stenosis at cCTA.
authors.affiliation: Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, MSC 226, Charleston, SC, 29401, USA.
authors.forename: Christian
authors.initials: C
authors.lastname: Thilo
authors.forename: Mulugeta
authors.initials: M
authors.lastname: Gebregziabher
authors.forename: Felix G
authors.initials: FG
authors.lastname: Meinel
authors.forename: Roman
authors.initials: R
authors.lastname: Goldenberg
authors.forename: John W
authors.initials: JW
authors.lastname: Nance
authors.forename: Elisabeth M
authors.initials: EM
authors.lastname: Arnoldi
authors.forename: Lashonda D
authors.initials: LD
authors.lastname: Soma
authors.forename: Ullrich
authors.initials: U
authors.lastname: Ebersberger
authors.forename: Philip
authors.initials: P
authors.lastname: Blanke
authors.forename: Richard L
authors.initials: RL
authors.lastname: Coursey
authors.forename: Michael A
authors.initials: MA
authors.lastname: Rosenblum
authors.forename: Peter L
authors.initials: PL
authors.lastname: Zwerner
authors.forename: U Joseph
authors.initials: UJ
authors.lastname: Schoepf
mesh_terms: D000368:Aged; D000465:Algorithms; D002983:Clinical Competence / Q000592:standards; D003287:Contrast Media; D017023:Coronary Angiography / Q000379:methods*; D023921:Coronary Stenosis / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008297:Male; D008875:Middle Aged; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D003287:Contrast Media