title: Automatic detection of left and right ventricles from CTA enables efficient alignment of anatomy with myocardial perfusion data.
abstract: BACKGROUND
  Accurate alignment between cardiac CT angiographic studies (CTA) and nuclear perfusion images is crucial for improved diagnosis of coronary artery disease. This study evaluated in an animal model the accuracy of a CTA fully automated biventricular segmentation algorithm, a necessary step for automatic and thus efficient PET/CT alignment.
  
  
  RESULTS
  Twelve pigs with acute infarcts were imaged using Rb-82 PET and 64-slice CTA. Post-mortem myocardium mass measurements were obtained. Endocardial and epicardial myocardial boundaries were manually and automatically detected on the CTA and both segmentations used to perform PET/CT alignment. To assess the segmentation performance, image-based myocardial masses were compared to experimental data; the hand-traced profiles were used as a reference standard to assess the global and slice-by-slice robustness of the automated algorithm in extracting myocardium, LV, and RV. Mean distances between the automated and the manual 3D segmented surfaces were computed. Finally, differences in rotations and translations between the manual and automatic surfaces were estimated post-PET/CT alignment. The largest, smallest, and median distances between interactive and automatic surfaces averaged 1.2 ± 2.1, 0.2 ± 1.6, and 0.7 ± 1.9 mm. The average angular and translational differences in CT/PET alignments were 0.4°, -0.6°, and -2.3° about x, y, and z axes, and 1.8, -2.1, and 2.0 mm in x, y, and z directions.
  
  
  CONCLUSIONS
  Our automatic myocardial boundary detection algorithm creates surfaces from CTA that are similar in accuracy and provide similar alignments with PET as those obtained from interactive tracing. Specific difficulties in a reliable segmentation of the apex and base regions will require further improvements in the automated technique.
authors.affiliation: Department of Radiology and Imaging Sciences, Emory University, 101 Woodruff Circle, Room 1203C, Atlanta, GA, 30322, USA, mpiccin@emory.edu.
authors.forename: Marina
authors.initials: M
authors.lastname: Piccinelli
authors.forename: Tracy L
authors.initials: TL
authors.lastname: Faber
authors.forename: Chesnal D
authors.initials: CD
authors.lastname: Arepalli
authors.forename: Vikram
authors.initials: V
authors.lastname: Appia
authors.forename: Jakob
authors.initials: J
authors.lastname: Vinten-Johansen
authors.forename: Susan L
authors.initials: SL
authors.lastname: Schmarkey
authors.forename: Russell D
authors.initials: RD
authors.lastname: Folks
authors.forename: Ernest V
authors.initials: EV
authors.lastname: Garcia
authors.forename: Anthony
authors.initials: A
authors.lastname: Yezzi
mesh_terms: D000465:Algorithms; D000818:Animals; D017023:Coronary Angiography / Q000379:methods*; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging; D001330:Electronic Data Processing; D005260:Female; D006321:Heart / Q000000981:diagnostic imaging*; D006352:Heart Ventricles / Q000000981:diagnostic imaging; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D009206:Myocardium / Q000473:pathology*; D010477:Perfusion; D049268:Positron-Emission Tomography / Q000379:methods; D012414:Rubidium Radioisotopes / Q000737:chemistry; D013552:Swine; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D012414:Rubidium Radioisotopes