title: [Automatic phase point determination of minimal motion reconstruction intervals with motion maps in ECG-gated CT diagnostics of coronary sclerosis].
abstract: OBJECTIVE
  Cardio-CT motion maps for automated cardiac phase point determination were evaluated for image quality and reliability of coronary calcium scores.
  
  
  METHODS
  24 patients underwent ECG-gated non-enhanced cardiac CT for calcium scoring. From raw data the motion map software reconstructed low-resolution images in 2 % steps of the RR interval and automatically generated cardiac motion maps for determination of minimal motion phase points. Diagnostic images were reconstructed in 10% steps of the RR interval (RR data) and according to the motion maps (MM data). For every data set, the Agatston score was calculated. Image quality was evaluated by two independent observers. Image quality was correlated with the Agatston score.
  
  
  RESULTS
  The Agatston score calculated over the RR interval showed a mean variation of 127 with 41% of patients assigned to more than one risk group. If the motion map RR intervals were calculated, only 16% patients were assigned to different risk categories with a mean variation of 55. Regarding the image quality, the inter-rater variance was moderate. The best image quality was achieved with the 30 - 40% and 70 - 80% RR interval. Over the complete RR interval motion map reconstructions produced a good image quality.
  
  
  CONCLUSIONS
  Calculation of the Agatston score requires selection of the proper reconstruction interval to guarantee the assignment of patients into the appropriate risk category. By using motion maps for phase point determination, the amount of necessary reconstruction can be minimized and the assignment to different risk groups is also reduced.
authors.affiliation: Klinik und Poliklinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Hamburg-Eppendorf. t.klink@uke.uni-hamburg.de
authors.forename: T
authors.initials: T
authors.lastname: Klink
authors.forename: M H
authors.initials: MH
authors.lastname: Hoffmann
authors.forename: U
authors.initials: U
authors.lastname: van Stevendaal
authors.forename: M
authors.initials: M
authors.lastname: Regier
authors.forename: G
authors.initials: G
authors.lastname: Adam
authors.forename: M
authors.initials: M
authors.lastname: Grass
authors.forename: P G
authors.initials: PG
authors.lastname: Begemann
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002114:Calcinosis / Q000000981:diagnostic imaging; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging*; D004562:Electrocardiography / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D008432:Mathematical Computing; D008875:Middle Aged; D009200:Myocardial Contraction / Q000502:physiology*; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D012984:Software; D036542:Tomography, Spiral Computed / Q000379:methods*