title: Diagnostic value of parametric imaging of left ventricular wall motion from contrast-enhanced echocardiograms in patients with poor acoustic windows.
abstract: BACKGROUND
  Analysis of left ventricular (LV) regional wall motion (RWM) is subjective and may be challenging in patients with suboptimal images, even with contrast enhancement. It was hypothesized that the amplitude and timing of RWM obtained from contrast-enhanced echocardiograms can be accurately represented in still-frame parametric images. This study was designed to (1) test this hypothesis, (2) establish the diagnostic value of these images as an aid for inexperienced readers, and (3) test the feasibility of automated quantitative analysis of RWM.
  
  
  METHODS
  Contrast-enhanced apical 4-chamber, 2-chamber, and 3-chamber LV views were acquired in 45 patients with poor acoustic windows. The interpretation of dynamic images by an experienced reader who classified RWM as normal or abnormal was used as a reference for comparisons against (1) visual interpretation of parametric images, (2) interpretation of dynamic images by two inexperienced readers (American Society of Echocardiography level I) without and subsequently with parametric images, and (3) automated quantification of RWM.
  
  
  RESULTS
  Expert readers detected abnormal RWM in 30 patients (437 of 945 segments). Visual interpretation of parametric images showed good agreement with the reference (sensitivity, 85%; specificity, 82%; accuracy, 84%). The interpretations by inexperienced readers improved with the addition of parametric images, with increases in specificity (from 58% to 79%) and accuracy (from 74% to 84%), despite a slight decrease in sensitivity (from 92% to 91%). Automated classification was feasible and accurate (sensitivity, 82%; specificity, 78%; accuracy, 80%).
  
  
  CONCLUSIONS
  Parametric images derived from contrast-enhanced echocardiograms of patients with poor acoustic windows accurately depicted RWM, improved the diagnostic accuracy of inexperienced readers, and allowed the objective detection of RWM abnormalities.
authors.affiliation: University of Chicago Medical Center, Chicago, Illinois 60637, USA. nadjia.kachenoura@gmail.com
authors.forename: Nadjia
authors.initials: N
authors.lastname: Kachenoura
authors.forename: Victor
authors.initials: V
authors.lastname: Mor-Avi
authors.forename: Frederique
authors.initials: F
authors.lastname: Frouin
authors.forename: Annie
authors.initials: A
authors.lastname: Delouche
authors.forename: Tamar S
authors.initials: TS
authors.lastname: Polonsky
authors.forename: Sandra
authors.initials: S
authors.lastname: D'Amore
authors.forename: Benoit
authors.initials: B
authors.lastname: Diebold
authors.forename: Roberto M
authors.initials: RM
authors.lastname: Lang
mesh_terms: D000465:Algorithms; D016477:Artifacts; D003287:Contrast Media; D004452:Echocardiography / Q000379:methods*; D005260:Female; D005466:Fluorocarbons; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D018487:Ventricular Dysfunction, Left / Q000000981:diagnostic imaging*
chemical_list: D003287:Contrast Media; D005466:Fluorocarbons; C042852:perflutren