title: Fully automated analysis of attenuation-corrected SPECT for the long-term prediction of acute myocardial infarction.
abstract: Most prior studies assessing the prognostic value of SPECT myocardial perfusion imaging (MPI) have used semi-quantitative visual analysis. We assessed the feasibility of large-scale fully automated quantitative analysis of SPECT MPI to predict acute myocardial infarction (AMI). Additionally, we examined the impact of attenuation correction (AC) in automated strategies.
  
  
  
  5960 patients underwent rest/stress SPECT MPI with AC. Left ventricular (LV) segmentation, contour QC check, and quantitation of stress and ischemic total perfusion deficit (sTPD, iTPD) were performed. Only contours flagged for potential errors by QC were visually checked (10%). During long-term follow-up (6.1 ± 2.7 years), 522 patients (9%) had AMI. In Cox models, adjusted for ejection fraction (LVEF) and other relevant covariates, there was a stepwise increase in risk hazard ratios by quartile for sTPD (Q1: 1.00, Q2: 1.26, Q3: 1.66, Q4: 1.79; P < 0.0001) and iTPD (Q1: 1.00, Q2: 1.26, Q3: 1.66, Q4: 1.79; P < 0.0001). Area under curve for AMI prediction by automated measures was similar for AC and non-AC data (sTPD: 0.63 vs 0.64, P = 0.85; iTPD: 0.61 vs 0.61, P = 0.70). Higher AUCs for both AC and non-AC data were seen for AMI occurring in the first 1 year of follow-up (sTPD: 0.71, 0.72; iTPD: 0.70, 0.68).
  
  
  
  Fully automated sTPD was an independent predictor of future AMI events even after adjusting for LVEF and other relevant covariates. AC did not significantly impact predictive accuracy.
authors.affiliation: Cedars-Sinai Medical Center, Los Angeles, CA, USA.
authors.forename: Manish
authors.initials: M
authors.lastname: Motwani
authors.affiliation: University of Manitoba, Winnipeg, MB, Canada.
authors.forename: William D
authors.initials: WD
authors.lastname: Leslie
authors.affiliation: University of Manitoba, Winnipeg, MB, Canada.|Health Sciences Centre, Winnipeg, MB, Canada.
authors.forename: Andrew L
authors.initials: AL
authors.lastname: Goertzen
authors.affiliation: Cedars-Sinai Medical Center, Los Angeles, CA, USA.
authors.forename: Yuka
authors.initials: Y
authors.lastname: Otaki
authors.affiliation: Cedars-Sinai Medical Center, Los Angeles, CA, USA.
authors.forename: Guido
authors.initials: G
authors.lastname: Germano
authors.affiliation: Cedars-Sinai Medical Center, Los Angeles, CA, USA.
authors.forename: Daniel S
authors.initials: DS
authors.lastname: Berman
authors.affiliation: Cedars-Sinai Medical Center, Los Angeles, CA, USA. slomkap@cshs.org.
authors.forename: Piotr J
authors.initials: PJ
authors.lastname: Slomka
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009203:Myocardial Infarction / Q000000981:diagnostic imaging*; D055414:Myocardial Perfusion Imaging / Q000379:methods*; D016016:Proportional Hazards Models; D011786:Quality Control; D015899:Tomography, Emission-Computed, Single-Photon / Q000379:methods*
keywords: Myocardial perfusion imaging; myocardial infarction; prognosis; quantification; total perfusion deficit