title: Prognostic value of automated vs visual analysis for adenosine stress myocardial perfusion SPECT in patients without prior coronary artery disease: a case-control study.
abstract: OBJECTIVE
  We aimed to evaluate the prognostic value of automated quantitative hypoperfusion parameters derived from adenosine stress myocardial perfusion SPECT (MPS) for predicting sudden or cardiac death (CD) in case-controlled patients with suspected coronary artery disease (CAD).
  
  
  METHODS
  We considered patients with available adenosine stress Tc-99m sestamibi MPS scans and follow-up information. 81 CD patients from a registry of 428 patients documented by the National Death Index were directly matched in a retrospective case-control design to patients without CD by key clinical parameters (age by deciles, gender, no early revascularization, pre-test likelihood categories, diabetes, and chest pain symptoms). Multivariable analysis of stress MPS total perfusion deficit (STPD) and major clinical confounders were used as predictors of CD. Visual 17-segment summed stress segmental scores (VSSS) obtained by an expert reader, were compared to STPD.
  
  
  RESULTS
  CD patients had higher stress hypoperfusion measures compared to controls [STPD: 7.0% vs 3.6% (P < .05), VSSS: 5.3 vs 2.1 (P < .05)]. By univariate analysis, STPD and VSSS have similar predictive power (the areas under receiver operator characteristics curves: STPD = 0.64, VSSS = 0.63; Kaplan-Meier models: χ(2) = 7.59, P = .0059 for STPD and χ(2) = 11.10, P = .0009 for VSSS). The multiple Cox proportional hazards regression models with continuous perfusion measures showed that STPD had similar power to normalized VSSS as a predictor for CD (χ(2) = 4.92; P = .027) vs (χ(2) = 8.90; P = .003).
  
  
  CONCLUSIONS
  Quantitative analysis is comparable to expert visual scoring in predicting CD in a case-controlled study.
authors.affiliation: Departments of Imaging and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Taper #A047, Los Angeles, CA 90048, USA. yuan.xu@cshs.org
authors.forename: Yuan
authors.initials: Y
authors.lastname: Xu
authors.forename: Ryo
authors.initials: R
authors.lastname: Nakazato
authors.forename: Sean
authors.initials: S
authors.lastname: Hayes
authors.forename: Rory
authors.initials: R
authors.lastname: Hachamovitch
authors.forename: Victor Y
authors.initials: VY
authors.lastname: Cheng
authors.forename: Heidi
authors.initials: H
authors.lastname: Gransar
authors.forename: Romalisa
authors.initials: R
authors.lastname: Miranda-Peats
authors.forename: Mark
authors.initials: M
authors.lastname: Hyun
authors.forename: Leslee J
authors.initials: LJ
authors.lastname: Shaw
authors.forename: John
authors.initials: J
authors.lastname: Friedman
authors.forename: Guido
authors.initials: G
authors.lastname: Germano
authors.forename: Daniel S
authors.initials: DS
authors.lastname: Berman
authors.forename: Piotr J
authors.initials: PJ
authors.lastname: Slomka
mesh_terms: D000241:Adenosine; D000368:Aged; D002140:California / Q000453:epidemiology; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging* / Q000401:mortality*; D005080:Exercise Test / Q000401:mortality*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008297:Male; D055414:Myocardial Perfusion Imaging / Q000401:mortality*; D011379:Prognosis; D012042:Registries; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors; D012680:Sensitivity and Specificity; D016019:Survival Analysis; D015996:Survival Rate; D015899:Tomography, Emission-Computed, Single-Photon / Q000401:mortality* / Q000706:statistics & numerical data*; D014665:Vasodilator Agents
chemical_list: D014665:Vasodilator Agents; D000241:Adenosine