title: Prevalence and predictors of mechanical dyssynchrony as defined by phase analysis in patients with left ventricular dysfunction undergoing gated SPECT myocardial perfusion imaging.
abstract: BACKGROUND
  A novel method to quantify dyssynchrony using phase analysis of single-photon emission computed tomography (SPECT) myocardial perfusion imaging has been developed. We sought to determine the prevalence of SPECT-derived mechanical dyssynchrony, and we report clinical variables which predict mechanical dyssynchrony in patients with left ventricular dysfunction.
  
  
  METHODS
  We used a count-based Fourier analysis method to convert the regional myocardial counts from discrete frames per cardiac cycle into a continuous thickening function which allows resolution of the phase of the onset of myocardial contraction. The standard deviation of left ventricular phases (Phase SD) describes the regional phase dispersion as a measure of dyssynchrony. Significant dyssynchrony was defined as Phase SD ≥ 43°. 260 patients with left ventricular ejection fraction ≤ 35% were examined.
  
  
  RESULTS
  The prevalence of mechanical dyssynchrony in the entire cohort of patients studied was 52%. Univariate predictors of Phase SD were age (P = .03), black race (P = .0005), QRS duration, EF, EDV, summed stress score (SSS), and summed rest score (SRS) (all P = <.0001). Black race, male gender, QRS EF, and SRS were independent predictors of SPECT-based mechanical dyssynchrony.
  
  
  CONCLUSIONS
  Significant SPECT-based mechanical dyssynchrony is relatively common among patients with left ventricular dysfunction. In a population of patients with predominantly ischemic heart disease referred for SPECT, a reduced EF, increasing QRS duration, severity and extent of myocardial scar on SPECT imaging are independent predictors of mechanical dyssynchrony and may serve to identify patients for dyssynchrony screening.
authors.affiliation: Division of Cardiology, Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA.
authors.forename: Zainab
authors.initials: Z
authors.lastname: Samad
authors.forename: Allen E
authors.initials: AE
authors.lastname: Atchley
authors.forename: Mark A
authors.initials: MA
authors.lastname: Trimble
authors.forename: Jie-Lena
authors.initials: JL
authors.lastname: Sun
authors.forename: Linda K
authors.initials: LK
authors.lastname: Shaw
authors.forename: Robert
authors.initials: R
authors.lastname: Pagnanelli
authors.forename: Ji
authors.initials: J
authors.lastname: Chen
authors.forename: Ernest V
authors.initials: EV
authors.lastname: Garcia
authors.forename: Ami E
authors.initials: AE
authors.lastname: Iskandrian
authors.forename: Eric J
authors.initials: EJ
authors.lastname: Velazquez
authors.forename: Salvador
authors.initials: S
authors.lastname: Borges-Neto
mesh_terms: D000368:Aged; D000465:Algorithms; D055426:Cardiac-Gated Single-Photon Emission Computer-Assisted Tomography / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D015994:Incidence; D008297:Male; D055414:Myocardial Perfusion Imaging / Q000706:statistics & numerical data*; D009657:North Carolina / Q000453:epidemiology; D015995:Prevalence; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors; D012680:Sensitivity and Specificity; D018487:Ventricular Dysfunction, Left / Q000000981:diagnostic imaging* / Q000453:epidemiology*