title: Diagnostic accuracy of second-generation dual-source computed tomography coronary angiography with iterative reconstructions: a real-world experience.
abstract: OBJECTIVE
  The authors evaluated the diagnostic accuracy of second-generation dual-source (DSCT) computed tomography coronary angiography (CTCA) with iterative reconstructions for detecting obstructive coronary artery disease (CAD).
  
  
  METHODS
  Between June 2010 and February 2011, we enrolled 160 patients (85 men; mean age 61.2±11.6 years) with suspected CAD. All patients underwent CTCA and conventional coronary angiography (CCA). For the CTCA scan (Definition Flash, Siemens), we use prospective tube current modulation and 70-100 ml of iodinated contrast material (Iomeprol 400 mgI/ ml, Bracco). Data sets were reconstructed with iterative reconstruction algorithm (IRIS, Siemens). CTCA and CCA reports were used to evaluate accuracy using the threshold for significant stenosis at ≥50% and ≥70%, respectively.
  
  
  RESULTS
  No patient was excluded from the analysis. Heart rate was 64.3±11.9 bpm and radiation dose was 7.2±2.1 mSv. Disease prevalence was 30% (48/160). Sensitivity, specificity and positive and negative predictive values of CTCA in detecting significant stenosis were 90.1%, 93.3%, 53.2% and 99.1% (per segment), 97.5%, 91.2%, 61.4% and 99.6% (per vessel) and 100%, 83%, 71.6% and 100% (per patient), respectively. Positive and negative likelihood ratios at the per-patient level were 5.89 and 0.0, respectively.
  
  
  CONCLUSIONS
  CTCA with second-generation DSCT in the real clinical world shows a diagnostic performance comparable with previously reported validation studies. The excellent negative predictive value and likelihood ratio make CTCA a first-line noninvasive method for diagnosing obstructive CAD.
authors.affiliation: Unità Cardio-Vascolare Radiologica, Ospedale Giovanni XXIII, Monastier di Treviso (TV), Italy.
authors.forename: E
authors.initials: E
authors.lastname: Maffei
authors.forename: C
authors.initials: C
authors.lastname: Martini
authors.forename: A
authors.initials: A
authors.lastname: Rossi
authors.forename: N
authors.initials: N
authors.lastname: Mollet
authors.forename: C
authors.initials: C
authors.lastname: Lario
authors.forename: M
authors.initials: M
authors.lastname: Castiglione Morelli
authors.forename: A
authors.initials: A
authors.lastname: Clemente
authors.forename: G
authors.initials: G
authors.lastname: Gentile
authors.forename: T
authors.initials: T
authors.lastname: Arcadi
authors.forename: S
authors.initials: S
authors.lastname: Seitun
authors.forename: O
authors.initials: O
authors.lastname: Catalano
authors.forename: A
authors.initials: A
authors.lastname: Aldrovandi
authors.forename: F
authors.initials: F
authors.lastname: Cademartiri
mesh_terms: D000465:Algorithms; D003287:Contrast Media; D017023:Coronary Angiography / Q000379:methods*; D023921:Coronary Stenosis / Q000000981:diagnostic imaging* / Q000503:physiopathology; D005260:Female; D006801:Humans; D007479:Iopamidol / Q000031:analogs & derivatives; D016013:Likelihood Functions; D008297:Male; D008875:Middle Aged; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D003287:Contrast Media; C057937:iomeprol; D007479:Iopamidol
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