title: Volumetric quantification of myocardial perfusion using analysis of multi-detector computed tomography 3D datasets: comparison with nuclear perfusion imaging.
abstract: BACKGROUND
  Although the ability of multi-detector computed tomography (MDCT) to detect perfusion abnormalities associated with acute and chronic myocardial infarction (MI) has been demonstrated, this methodology is based on visual interpretation of selected 2D slices.
  
  
  OBJECTIVE
  We sought to develop a new technique for quantitative volumetric analysis of myocardial perfusion from 3D datasets and test it against resting nuclear myocardial perfusion imaging (NMPI) reference.
  
  
  METHODS
  We studied 44 patients undergoing CTCA: a control group of 15 patients and a study group of 29 patients. MDCT datasets acquired for CTCA were analyzed using custom software designed to: (1) generate bull's eye display of myocardial perfusion and (2) calculate a quantitative index of extent and severity of perfusion abnormality, Q(H), for 16 volumetric myocardial segments. Visual interpretation of MDCT-derived bull's eyes was compared with rest NMPI scores using kappa statistics of agreement on a coronary territory and patient basis. Quantitative MDCT perfusion data were correlated with rest NMPI summed scores and used for objective detection of perfusion defects.
  
  
  RESULTS
  Visual analysis of MDCT-derived bull's eyes accurately detected perfusion defects in agreement with NMPI (kappa = 0.70 by territory; 0.79 by patient). Quantitative data were in good agreement with NMPI, as reflected by: (1) correlation of 0.87 (territory) and 0.84 (patient) between summed Q(H) and NMPI scores, (2) area under ROC curve 0.87 with sensitivity of 0.79-0.92, specificity 0.83-0.91, and accuracy 0.83-0.89 for objective detection of abnormalities.
  
  
  CONCLUSIONS
  Our new technique for volumetric analysis of 3D MDCT images allows accurate objective detection of perfusion defects. This perfusion information can be obtained without additional radiation or contrast load, and may aid in elucidating the significance of coronary lesions.
authors.affiliation: University of Chicago Medical Center, Chicago, IL 60637, USA.
authors.forename: Nadjia
authors.initials: N
authors.lastname: Kachenoura
authors.forename: Federico
authors.initials: F
authors.lastname: Veronesi
authors.forename: Joseph A
authors.initials: JA
authors.lastname: Lodato
authors.forename: Cristiana
authors.initials: C
authors.lastname: Corsi
authors.forename: Rupa
authors.initials: R
authors.lastname: Mehta
authors.forename: Barbara
authors.initials: B
authors.lastname: Newby
authors.forename: Roberto M
authors.initials: RM
authors.lastname: Lang
authors.forename: Victor
authors.initials: V
authors.lastname: Mor-Avi
mesh_terms: D000368:Aged; D000465:Algorithms; D017023:Coronary Angiography / Q000379:methods*; D003324:Coronary Artery Disease / Q000175:diagnosis*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D008875:Middle Aged; D055420:Perfusion Imaging / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D015899:Tomography, Emission-Computed, Single-Photon / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*