Advertisement

Analysis of the Left Ventricle After Myocardial Infarction Combining 4D Cine-MR and 3D DE-MR Image Sequences

  • D. Säring
  • J. Ehrhardt
  • A. Stork
  • M. P. Bansmann
  • G. K. Lund
  • H. Handels
Conference paper
Part of the Informatik aktuell book series (INFORMAT)

Abstract

Spatial-temporal MR image sequences of the heart contain information about shape and motion changes and pathological structures after myocardial infarction. In this paper a software system called HeAT for the quantitative analysis of 4D MR image sequences of infarct patients is presented. HeAT supports interactive segmentation of anatomical and pathological structures. Registration of Cine- and DE-MR image data is applied to enable their combined evaluation during the analysis process. Partitioning of the myocardium in segments enables the analysis with high local resolution. Corresponding segments are generated and used for inter/intra patient comparison. Quantitative parameters were extracted and visualized. Parameters like endocard movement in the infarcted area of 6 infarct patients were computed in HeAT. Parameters in the infarct area show the expected dysfunctional characteristics. Based on theses parameters passive endocardial movement and myocardial areas with decreased contraction were identified.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Zimmerman SD, Criscione J, Covell JW. Remodeling in myocardium adjacent to an infarction in the pig left ventricle. Am J Physiol Heart Circ Physiol Dec 2004;(287):H2697–H2704.CrossRefGoogle Scholar
  2. 2.
    Wu KC, Zerhouni EA, Judd RM, et al. Prognostic significance of microvascular obstruction by magnetic resonance imaging in patients with acute myocardial infarction. Circulation 1998;(97):765–772.Google Scholar
  3. 3.
    Gerber BL, Garot J, et al. Accuracy of Contrast-Enhanced Magnetic Resonance Imaging in Predicting Improvement of Regional Myocardial Function in Patients After Acute Myocardial Infarction. Circulation Aug 2002;(106):1083–1089.CrossRefGoogle Scholar
  4. 4.
    Wells W, Viola P, et al. Multi-modal volume registration by maximization of mutual information. Medical Image Analysis 1996;1(1):35–51.CrossRefGoogle Scholar
  5. 5.
    Thirion JeanPhilippe. Non-Rigid Matching Using Demons. In: Proc. Int. Conf. Computer Vision and Pattern Recognition (CVPR’ 96). Washington, DC, USA: IEEE Computer Society; 1996. p. 245.Google Scholar
  6. 6.
    Säring D, Ehrhardt J, Stork A, Bannsmann MP, Lund GK, Handels H. HeAT-Heart Analysis Tool. In: 50. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. Freiburg; 2005. p. 28–30.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • D. Säring
    • 1
  • J. Ehrhardt
    • 1
  • A. Stork
    • 2
  • M. P. Bansmann
    • 2
  • G. K. Lund
    • 3
  • H. Handels
    • 1
  1. 1.Department of Medical InformaticsUniversity Medical Center Hamburg-EppendorfHamburgGermany
  2. 2.Department of Diagnostic and Interventional RadiologyUniversity Medical Center Hamburg-EppendorfHamburgGermany
  3. 3.Department of Cardiology/AngiologyUniversity Medical Center Hamburg-EppendorfHamburgGermany

Personalised recommendations