title: Quantitative myocardial perfusion PET combined with coronary anatomy derived from CT angiography: validation of a new fusion and visualisation software.
abstract: OBJECTIVE
  Dynamic perfusion PET offers a clinical relevant advantage over myocardial perfusion scintigraphy due to its ability to measure myocardial blood flow quantitatively. This leads to an improved detection of multivessel disease and the possibility to assess not only the culprit lesion but lower grade stenoses as well. For appropriate revascularization, perfusion defects must be matched to coronary lesions. It has been shown that image fusion of morphological and functional images is superior to side-by-side analysis. Still, software for quantitative perfusion PET combined with CT angiography is rare. In this paper we present a new software tool for image fusion and visualization of quantitative perfusion PET and coronary morphology derived from CT angiography.
  
  
  METHODS
  In our software, a PET uptake image is used for manual co-registration. Co-registration results are then applied to the functional data derived from compartment modelling. To evaluate the reproducibility of the manual co-registration, we calculated the deviation between a series of manual co-registrations performed on nine pairs of unregistered PET and CT datasets by five trained participants. Two dimensional transfer functions were used to highlight the coronary arteries from the CT study in the combined data sets.
  
  
  RESULTS
  The average Euclidian distances for three references points were between 3.7 and 4.1 mm. The maximum distance was 10.6 mm. By the use of the two dimensional transfer functions, coronary anatomy could be easily visualised either by user-interaction or automatically by use of neuronal networks.
  
  
  CONCLUSIONS
  With this approach it is possible to combine quantitative perfusion PET with coronary anatomy derived from CT angiography. Our first experiences indicate that manual image fusion with our tool is reproducible and that visualisation of the combined datasets is achieved within short time.
authors.affiliation: Institute of Radiology, Nuclear Medicine and Molecular Imaging, Heart and Diabetes Centre North Rhine-Westphalia, Ruhr-University Bochum, Bad Oeynhausen, Germany. hfricke@hdz-nrw.de
authors.forename: Harald
authors.initials: H
authors.lastname: Fricke
authors.forename: Andreas
authors.initials: A
authors.lastname: Elsner
authors.forename: Reiner
authors.initials: R
authors.lastname: Weise
authors.forename: Matthias
authors.initials: M
authors.lastname: Bolte
authors.forename: Jörg
authors.initials: J
authors.lastname: van den Hoff
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Burchert
authors.forename: Gitta
authors.initials: G
authors.lastname: Domik
authors.forename: Eva
authors.initials: E
authors.lastname: Fricke
mesh_terms: D000368:Aged; D017023:Coronary Angiography / Q000379:methods; D001026:Coronary Artery Bypass; D003327:Coronary Disease / Q000000981:diagnostic imaging*; D003331:Coronary Vessels / Q000000981:diagnostic imaging*; D005260:Female; D006321:Heart / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D049268:Positron-Emission Tomography; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*; D016277:Ventricular Function, Left