title: A novel analysis algorithm for potential quantitative assessment of myocardial computed tomography perfusion.
abstract: OBJECTIVE
  Cardiac computed tomography (CT) has emerged as a robust modality for imaging coronary stenosis and has recently been used to evaluate myocardial abnormalities such as ischemic perfusion defects and infarction. We developed a new image analysis algorithm for the semiautomatic and quantitative assessment of myocardial perfusion by CT.
  
  
  METHODS
  The algorithm semiautomatically segments two-dimensional short-axis reformatted DICOM images of the left ventricle into regions of interest (ROIs) in accordance with American Heart Association (AHA) standards and is capable of creating nine further ROI subsegments. This includes separate endocardial, mid-ventricle, and epicardial layers. Image intensity values (Hounsfield unit) and relative myocardial thickness are quantitatively reported for each ROI and segment.
  
  
  RESULTS
  The algorithm allows comparison of the HU values at the same ROI locations between rest and stress. The reproducibility is very good; ICC 0.89 for rest images, 0.83 for stress images. The mean time for generating ROIs for the entire heart was 11 minutes versus 22 minutes for manual tracing.
  
  
  CONCLUSIONS
  The algorithm reports parameters relevant for evaluation of stress perfusion CT studies and will allow more accurate and reproducible analysis in cardiac CT research.
authors.affiliation: Cardiac MR PET CT Program, Department of Radiology, Massachusetts General Hospital, 165 Cambridge St, Suite 400, Boston, MA 02114. Electronic address: gyhliew@gmail.com.
authors.forename: Gary
authors.initials: G
authors.lastname: Liew
authors.forename: Nabeel
authors.initials: N
authors.lastname: Ali
authors.forename: Synho
authors.initials: S
authors.lastname: Do
authors.forename: Milena
authors.initials: M
authors.lastname: Petranovic
authors.forename: Ricardo
authors.initials: R
authors.lastname: Cury
authors.forename: Thomas
authors.initials: T
authors.lastname: Brady
authors.forename: Udo
authors.initials: U
authors.lastname: Hoffmann
authors.forename: Brian
authors.initials: B
authors.lastname: Ghoshhajra
mesh_terms: D000465:Algorithms; D017023:Coronary Angiography / Q000379:methods*; D023921:Coronary Stenosis / Q000000981:diagnostic imaging*; D006801:Humans; D055414:Myocardial Perfusion Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: Computed tomography; algorithm; cardiac imaging; image analysis; myocardial perfusion