Literature DB >> 16093505

Measuring and mapping cardiac fiber and laminar architecture using diffusion tensor MR imaging.

Patrick Helm1, Mirza Faisal Beg, Michael I Miller, Raimond L Winslow.   

Abstract

The ventricular myocardium is known to exhibit a complex spatial organization, with fiber orientation varying as a function of transmural location. It is now well established that diffusion tensor magnetic resonance imaging (DTMRI) may be used to measure this fiber orientation at high spatial resolution. Cardiac fibers are also known to be organized in sheets with surface orientation varying throughout the ventricles. This article reviews results on use of DTMRI for measuring ventricular fiber orientation, as well as presents new results providing strong evidence that the tertiary eigenvector of the diffusion tensor is aligned locally with the cardiac sheet surface normal. Considered together, these data indicate that DTMRI may be used to reconstruct both ventricular fiber and sheet organization. This article also presents the large deformation diffeomorphic metric mapping (LDDMM) algorithm and shows that this algorithm may be used to bring ensembles of imaged and reconstructed hearts into correspondence (e.g., registration) so that variability of ventricular geometry, fiber, and sheet orientation may be quantified. Ventricular geometry and fiber structure is known to be remodeled in a range of disease processes; however, descriptions of this remodeling have remained subjective and qualitative. We anticipate that use of DTMRI for reconstruction of ventricular anatomy coupled with application of the LDDMM method for image volume registration will enable the detection and quantification of changes in cardiac anatomy that are characteristic of specific disease processes in the heart. Finally, we show that epicardial electrical mapping and DTMRI imaging may be performed in the same hearts. The anatomic data may then be used to simulate electrical conduction in a computational model of the very same heart that was mapped electrically. This facilitates direct comparison and testing of model versus experimental results and opens the door to quantitative measurement, modeling, and analysis of the ways in which remodeling of ventricular microanatomy influences electrical conduction in the heart.

Mesh:

Year:  2005        PMID: 16093505     DOI: 10.1196/annals.1341.026

Source DB:  PubMed          Journal:  Ann N Y Acad Sci        ISSN: 0077-8923            Impact factor:   5.691


  82 in total

1.  The presence of two local myocardial sheet populations confirmed by diffusion tensor MRI and histological validation.

Authors:  Geoffrey L Kung; Tom C Nguyen; Aki Itoh; Stefan Skare; Neil B Ingels; D Craig Miller; Daniel B Ennis
Journal:  J Magn Reson Imaging       Date:  2011-09-19       Impact factor: 4.813

2.  Visualization and quantification of whole rat heart laminar structure using high-spatial resolution contrast-enhanced MRI.

Authors:  Stephen H Gilbert; David Benoist; Alan P Benson; Ed White; Steven F Tanner; Arun V Holden; Halina Dobrzynski; Olivier Bernus; Aleksandra Radjenovic
Journal:  Am J Physiol Heart Circ Physiol       Date:  2011-10-21       Impact factor: 4.733

3.  Anisotropy of wave propagation in the heart can be modeled by a Riemannian electrophysiological metric.

Authors:  Robert J Young; Alexander V Panfilov
Journal:  Proc Natl Acad Sci U S A       Date:  2010-08-09       Impact factor: 11.205

4.  A novel rule-based algorithm for assigning myocardial fiber orientation to computational heart models.

Authors:  J D Bayer; R C Blake; G Plank; N A Trayanova
Journal:  Ann Biomed Eng       Date:  2012-05-31       Impact factor: 3.934

5.  Focal but reversible diastolic sheet dysfunction reflects regional calcium mishandling in dystrophic mdx mouse hearts.

Authors:  Ya-Jian Cheng; Di Lang; Shelton D Caruthers; Igor R Efimov; Junjie Chen; Samuel A Wickline
Journal:  Am J Physiol Heart Circ Physiol       Date:  2012-07-09       Impact factor: 4.733

6.  Image-based estimation of ventricular fiber orientations for personalized modeling of cardiac electrophysiology.

Authors:  Fijoy Vadakkumpadan; Hermenegild Arevalo; Can Ceritoglu; Michael Miller; Natalia Trayanova
Journal:  IEEE Trans Med Imaging       Date:  2012-01-18       Impact factor: 10.048

7.  Three-dimensional imaging of ventricular activation and electrograms from intracavitary recordings.

Authors:  Chenguang Liu; Paul A Iaizzo; Bin He
Journal:  IEEE Trans Biomed Eng       Date:  2010-12-23       Impact factor: 4.538

8.  Three-dimensional models of individual cardiac histoanatomy: tools and challenges.

Authors:  Rebecca A B Burton; Gernot Plank; Jürgen E Schneider; Vicente Grau; Helmut Ahammer; Stephen L Keeling; Jack Lee; Nicolas P Smith; David Gavaghan; Natalia Trayanova; Peter Kohl
Journal:  Ann N Y Acad Sci       Date:  2006-10       Impact factor: 5.691

9.  Patient-specific modeling of the heart: estimation of ventricular fiber orientations.

Authors:  Fijoy Vadakkumpadan; Hermenegild Arevalo; Natalia A Trayanova
Journal:  J Vis Exp       Date:  2013-01-08       Impact factor: 1.355

10.  Noninvasive three-dimensional cardiac activation imaging from body surface potential maps: a computational and experimental study on a rabbit model.

Authors:  Chengzong Han; Zhongming Liu; Xin Zhang; Steven Pogwizd; Bin He
Journal:  IEEE Trans Med Imaging       Date:  2008-11       Impact factor: 10.048

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