Abstract
The Cardiac Atlas Project seeks to establish a standardized database of cardiovascular imaging examinations, together with derived analyses, for the purposes of statistical characterization of global and regional heart function abnormalities. We present preliminary results from a subset of cases contributed from the Defibrillators to Reduce Risk by Magnetic Resonance Imaging Evaluation (DETERMINE) study of patients with myocardial infarction. Finite element models were fitted to the epicardial and endocardial surfaces throughout the cardiac cycle in 200 patients using a standardized procedure. The control points of the shape model were used in a principal component analysis of shape and motion. The modes were associated with well-known clinical indices of adverse remodeling in heart disease, including heart size, sphericity and mitral valve geometry. These results therefore show promise for the clinical application of a statistical analysis of shape and motion in patients with myocardial infarction.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Augenstein, K., Young, A.: Finite element modeling for three-dimensional motion reconstruction and analysis. In: Measurement of Cardiac Deformations from MRI: Physical and Mathematical Models, pp. 37–58 (2001)
Cardoso, J.: High-order contrasts for independent component analysis. Neural computation 11(1), 157–192 (1999)
Frangi, A., Niessen, W., Viergever, M.: Three-dimensional modeling for functional analysis of cardiac images: A review. IEEE Transactions on medical imaging 20(1), 2–5 (2001)
Frangi, A., Rueckert, D., Schnabel, J., Niessen, W.: Automatic construction of multiple-object three-dimensional statistical shape models: Application to cardiac modeling. IEEE Transactions on Medical Imaging 21(9), 1151–1166 (2002)
Kadish, A., Bello, D., Finn, J., Bonow, R., Schaechter, A., Subacius, H., Albert, C., Daubert, J., Fonseca, C., Goldberger, J.: Rationale and design for the defibrillators to reduce risk by magnetic resonance imaging evaluation (DETERMINE) trial. Journal of Cardiovascular Electrophysiology 20(9), 982–987 (2009)
Lam, H., Cowan, B., Nash, M., Young, A.: Interactive biventricular modeling tools for clinical cardiac image analysis. Journal of Cardiovascular Magnetic Resonance 12(suppl. 1), 248 (2010)
Lötjönen, J., Koikkalainen, J., Smutek, D., Kivistö, S., Lauerma, K.: Four-chamber 3-D statistical shape model from cardiac short-axis and long-axis MR images. In: Ellis, R.E., Peters, T.M. (eds.) MICCAI 2003. LNCS, vol. 2878, pp. 459–466. Springer, Heidelberg (2003)
Mansi, T., Durrleman, S., Bernhardt, B., Sermesant, M., Delingette, H., Voigt, I., Lurz, P., Taylor, A., Blanc, J., Boudjemline, Y., et al.: A Statistical Model of Right Ventricle in Tetralogy of Fallot for Prediction of Remodelling and Therapy Planning. In: Yang, G.-Z., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds.) MICCAI 2009. LNCS, vol. 5761, pp. 214–221. Springer, Heidelberg (2009)
Nielsen, P.: The anatomy of the heart: a finite element model. PhD Thesis-University of Auckland (1987)
Ordas, S., Oubel, E., Leta, R., Carreras, F., Frangi, A.: A statistical shape model of the heart and its application to model-based segmentation. In: Proc. SPIE Medical Imaging, San Diego, CA, USA, vol. 6511 (2007)
Papademetris, X., Sinusas, A., Dione, D., Constable, R., Duncan, J.: Estimation of 3-D left ventricular deformation from medical images using biomechanical models. IEEE Transactions on Medical Imaging 21(7), 786–800 (2002)
Remme, E., Young, A., Augenstein, K., Cowan, B., Hunter, P.: Extraction and quantification of left ventricular deformation modes. IEEE Transactions on Biomedical Engineering 51(11), 1923–1931 (2004)
Young, A., Cowan, B., Thrupp, S., Hedley, W., Dell’Italia, L.: Left Ventricular Mass and Volume: Fast Calculation with Guide-Point Modeling on MR Images. Radiology 216(2), 597 (2000)
Young, A., Frangi, A.: Computational cardiac atlases: from patient to population and back. Experimental Physiology 94(5), 578 (2009)
Zito, T., Wilbert, N., Wiskott, L., Berkes, P.: Modular toolkit for Data Processing (MDP): a Python data processing framework. Frontiers in neuroinformatics, 2 (2008)
Üzümcü, M., Frangi, A., Sonka, M., Reiber, J., Lelieveldt, B.: ICA vs. PCA active appearance models: Application to cardiac MR segmentation. In: Ellis, R.E., Peters, T.M. (eds.) MICCAI 2003. LNCS, vol. 2878, pp. 451–458. Springer, Heidelberg (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Medrano-Gracia, P. et al. (2010). The Cardiac Atlas Project: Preliminary Description of Heart Shape in Patients with Myocardial Infarction. In: Camara, O., Pop, M., Rhode, K., Sermesant, M., Smith, N., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. STACOM 2010. Lecture Notes in Computer Science, vol 6364. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15835-3_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-15835-3_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15834-6
Online ISBN: 978-3-642-15835-3
eBook Packages: Computer ScienceComputer Science (R0)