title: 3D Geometric Analysis of the Pediatric Aorta in 3D MRA Follow-Up Images with Application to Aortic Coarctation.
abstract: BACKGROUND
  Coarctation of the aorta is one of the most common congenital heart diseases. Despite different treatment opportunities, long-term outcome after surgical or interventional therapy is diverse. Serial morphologic follow-up of vessel growth is necessary, because vessel growth cannot be predicted by primer morphology or a therapeutic option.
  
  
  OBJECTIVE
  For the analysis of the long-term outcome after therapy of congenital diseases such as aortic coarctation, accurate 3D geometric analysis of the aorta from follow-up 3D medical image data such as magnetic resonance angiography (MRA) is important. However, for an objective, fast, and accurate 3D geometric analysis, an automatic approach for 3D segmentation and quantification of the aorta from pediatric images is required.
  
  
  METHODS
  We introduce a new model-based approach for the segmentation of the thoracic aorta and its main branches from follow-up pediatric 3D MRA image data. For robust segmentation of vessels even in difficult cases (e.g., neighboring structures), we propose a new extended parametric cylinder model that requires only relatively few model parameters. Moreover, we include a novel adaptive background-masking scheme used for least-squares model fitting, we use a spatial normalization scheme to align the segmentation results from follow-up examinations, and we determine relevant 3D geometric parameters of the aortic arch.
  
  
  RESULTS
  We have evaluated our proposed approach using different 3D synthetic images. Moreover, we have successfully applied the approach to follow-up pediatric 3D MRA image data, we have normalized the 3D segmentation results of follow-up images of individual patients, and we have combined the results of all patients. We also present a quantitative evaluation of our approach for four follow-up 3D MRA images of a patient, which confirms that our approach yields accurate 3D segmentation results. An experimental comparison with two previous approaches demonstrates that our approach yields superior results.
  
  
  CONCLUSIONS
  From the results, we found that our approach is well suited for the quantification of the 3D geometry of the aortic arch from follow-up pediatric 3D MRA image data. In future work, this will enable to investigate the long-term outcome of different surgical and interventional therapies for aortic coarctation.
authors.affiliation: Stefan Wörz, BioQuant Center, BQ 20, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany, E-mail: s.woerz@dkfz.de.
authors.forename: Stefan
authors.initials: S
authors.lastname: Wörz
authors.forename: Jens-Peter
authors.initials: JP
authors.lastname: Schenk
authors.forename: Abdulsattar
authors.initials: A
authors.lastname: Alrajab
authors.forename: Hendrik
authors.initials: H
authors.lastname: von Tengg-Kobligk
authors.forename: Karl
authors.initials: K
authors.lastname: Rohr
authors.forename: Raoul
authors.initials: R
authors.lastname: Arnold
mesh_terms: D000293:Adolescent; D000328:Adult; D001011:Aorta / Q000000981:diagnostic imaging* / Q000473:pathology*; D001017:Aortic Coarctation / Q000000981:diagnostic imaging*; D002648:Child; D005500:Follow-Up Studies; D006801:Humans; D021621:Imaging, Three-Dimensional; D018810:Magnetic Resonance Angiography; D055815:Young Adult
keywords: 3D model-based segmentation; 3D vessel segmentation; aortic coarctation; cylindrical intensity model; follow-up MRA; pediatric image data; thoracic aorta