Full Paper

Computational cardiac anatomy using MRI†

  1. Mirza Faisal Beg1,‡,
  2. Patrick A. Helm2,‡,
  3. Elliot McVeigh3,
  4. Michael I. Miller1,
  5. Raimond L. Winslow2,*

Article first published online: 26 OCT 2004

DOI: 10.1002/mrm.20255

Issue

Magnetic Resonance in Medicine

Magnetic Resonance in Medicine

Volume 52, Issue 5, pages 1167–1174, November 2004

Additional Information

How to Cite

Beg, M. F., Helm, P. A., McVeigh, E., Miller, M. I. and Winslow, R. L. (2004), Computational cardiac anatomy using MRI. Magnetic Resonance in Medicine, 52: 1167–1174. doi: 10.1002/mrm.20255

Author Information

  1. 1

    Center for Imaging Science, The Whitaker Biomedical Engineering Institute, Johns Hopkins University School of Medicine and Whiting School of Engineering, Baltimore, Maryland

  2. 2

    Center for Cardiovascular Bioinformatics & Modeling, The Whitaker Biomedical Engineering Institute, Johns Hopkins University School of Medicine and Whiting School of Engineering, Baltimore, Maryland

  3. 3

    Laboratory of Cardiac Energetics, National Heart Lung Blood Institute, National Institutes of Health, Bethesda, Maryland

  1. ‡

    M.F. Beg and P.A. Helm contributed equally to this work

*Rm. 201B Clark Hall, Johns Hopkins University, 3400 N. Charles St., Baltimore MD 21218

  1. †

    This article is a US Government work and, as such, is in the public domain in the United States of America.

Publication History

  1. Issue published online: 26 OCT 2004
  2. Article first published online: 26 OCT 2004
  3. Manuscript Revised: 18 JUN 2004
  4. Manuscript Accepted: 18 JUN 2004
  5. Manuscript Received: 20 NOV 2003

Funded by

  • National Institutes of Health (NIH). Grant Numbers: HL70894, HL52307
  • Falk Medical Trust, IBM Corporation

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Keywords:

  • computational anatomy;
  • diffusion tensor MRI;
  • cardiac architecture;
  • fiber orientation;
  • remodeling

Abstract

Ventricular geometry and fiber orientation may undergo global or local remodeling in cardiac disease. However, there are as yet no mathematical and computational methods for quantifying variation of geometry and fiber orientation or the nature of their remodeling in disease. Toward this goal, a landmark and image intensity-based large deformation diffeomorphic metric mapping (LDDMM) method to transform heart geometry into common coordinates for quantification of shape and form was developed. Two automated landmark placement methods for modeling tissue deformations expected in different cardiac pathologies are presented. The transformations, computed using the combined use of landmarks and image intensities, yields high-registration accuracy of heart anatomies even in the presence of significant variation of cardiac shape and form. Once heart anatomies have been registered, properties of tissue geometry and cardiac fiber orientation in corresponding regions of different hearts may be quantified. Magn Reson Med 52:1167–1174, 2004. Published 2004 Wiley-Liss, Inc.

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