title: Effects of region of interest tracking on the diagnosis of left ventricular dyssynchrony from Doppler tissue images.
abstract: BACKGROUND
  Left ventricular dyssynchrony is often diagnosed by comparing velocity curves from Doppler tissue images of two or more myocardial regions. Velocity curves are generated by placing sample volumes or regions of interest (ROIs) within the myocardium. ROIs need to be manually relocated to maintain a midmyocardial location as the heart moves, but are frequently left in a stationary position. The error caused by use of a stationary ROI may affect the diagnosis of dyssynchrony, but this has not been quantified.
  
  
  OBJECTIVE
  We hypothesized that using a stationary ROI to quantify dyssynchrony from Doppler tissue images would affect the diagnosis of dyssynchrony in patients with heart failure.
  
  
  METHODS
  We quantified dyssynchrony in 18 patients with heart failure using 4 published dyssynchrony parameters: septal-to-lateral delay, maximum difference in the basal 2- or 4-chamber times to peak, SD of the 12 basal and midwall times to peak, and cross-correlation delay (XCD). Each dyssynchrony parameter was measured using both tracked and stationary ROIs.
  
  
  RESULTS
  Use of a stationary ROI did not change the diagnosis of dyssynchrony when using XCD. However, ROI tracking changed the diagnosis of dyssynchrony in 17%, 11%, and 17% of patients when using septal-to-lateral delay, maximum difference in the basal 2- or 4-chamber times to peak, and SD of the 12 basal and midwall times to peak, respectively. XCD showed the lowest percent difference between tracked and stationary ROIs (4 +/- 9% vs 22 +/- 53%, 50 +/- 167%, and 12 +/- 30%, respectively, for septal-to-lateral delay, maximum difference in the basal 2- or 4-chamber times to peak, and SD of the 12 basal and midwall times to peak).
  
  
  CONCLUSIONS
  Manual ROI tracking is required when using conventional time-to-peak parameters to diagnose dyssynchrony. XCD diagnosis of dyssynchrony can be performed accurately with a stationary ROI.
authors.affiliation: Emory University School of Medicine, Department of Biomedical Engineering, Atlanta, Georgia 30322, USA. bfornwa@emory.edu
authors.forename: Brandon K
authors.initials: BK
authors.lastname: Fornwalt
authors.forename: Joshua A
authors.initials: JA
authors.lastname: Thomas
authors.forename: Mohit
authors.initials: M
authors.lastname: Bhasin
authors.forename: John D
authors.initials: JD
authors.lastname: Merlino
authors.forename: Angel R
authors.initials: AR
authors.lastname: León
authors.forename: Derek A
authors.initials: DA
authors.lastname: Fyfe
authors.forename: John N
authors.initials: JN
authors.lastname: Oshinski
mesh_terms: D016477:Artifacts; D015150:Echocardiography, Doppler / Q000379:methods*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013223:Statistics as Topic; D018487:Ventricular Dysfunction, Left / Q000150:complications / Q000000981:diagnostic imaging*; D014693:Ventricular Fibrillation / Q000150:complications / Q000000981:diagnostic imaging*