Abstract
A clinical image data driven mechanics analysis was used to quantify changes in tissue-specific passive and contractile material properties for groups of normal and HF patients. We have developed an automated mechanics modelling framework to firstly construct left ventricular (LV) mechanics models based on shape information derived from non-invasive dynamic magnetic resonance images, then to characterise passive tissue stiffness and maximum contractile stress by matching the simulated LV mechanics with data from the dynamic cardiac images. Preliminary statistical analysis revealed that patients with hypertrophy or non-ischemic heart failure exhibited increased passive myocardial stiffness compared to the normals. Elevated maximum contractile stress was also observed for hypertrophic patients. Tissue-specific parameter estimation analysis of this kind can potentially be applied in the clinical setting to provide a more specific disease measure to assist with stratification of HF patients.
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
Zile, M.R., Brutsaert, D.L.: New Concepts in Diatsolic Dysfunction and Diastolic Heart Failure: Part I: Diagnosis, Prognosis, and Measurements of Diastolic Function. Circ. 105, 1387–1393 (2002)
Kitzman, D.W., et al.: Pathophysiological Characterization of Isolated Diastolic Heart Failure in Comparison to Systolic Heart Failure. J. Am. Med. Assoc. 288, 2144–2150 (2002)
Zile, M.R., Baicu, C.F., Gaasch, W.H.: Diastolic Heart Failure - Abnormalities in Active Relaxation and Passive Stiffness of the Left Ventricle. New Engl. J. Med. 350(19), 1953–1959 (2004)
Moulton, M.J., et al.: Myocardial material property determination in the in vivo heart using magnetic resonance imaging. Int. J. Card. Imaging 12, 153–167 (1996)
Paulus, W.J., et al.: How to diagnose diastolic heart failure. Eur. Heart J. 28(20), 2539–2550 (2007)
Leonard, B.L., Smaill, B.H., LeGrice, I.J.: Structural Remodeling and Mechanical Function in Heart Failure. Microsc. Microanal. 18(01), 50–67 (2012)
Westermann, D., et al.: Role of Left Ventricular Stiffness in Heart Failure With Normal Ejection Fraction. Circ. 117(16), 2051–2060 (2008)
Teeters, J.C., Alexis, J.D.: Systolic Heart Failure. In: Manual of Heart Failure Management, pp. 1–9. Springer, London (2009)
McMurray, J.J.V.: Systolic Heart Failure. New Engl. J. Med. 362(3), 228–238 (2010)
Wang, V.Y., et al.: Automated Personalised Human Left Ventricular FE Models To Investigate Heart Failure Mechanics. (in press)
Radau, P., Lu, Y., Connelly, K., Paul, G., Dick, A.J., Wright, G.A.: Evaluation Framework for Algorithms Segmenting Short Axis Cardiac MRI. The MIDAS Journal - Cardiac MR Left Ventricle Segmentation Challenge, http://hdl.handle.net/10380/3070
LV Segmentation Challenge: Data, http://smial.sri.utoronto.ca/LV_Challenge/Data.html
Fonseca, C.G., et al.: The Cardiac Atlas Project – An Imaging Database for Computational Modeling and Statistical Atlases of the Heart. Bioinformatics 27, 2288–2295 (2011)
Young, A.A., et al.: Left Ventricular Mass and Volume: Fast Calculation with Guide-Point Modeling on MR Images1. Radiology 216(2), 597–602 (2000)
Li, B., et al.: In-line automated tracking for four dimensional ventricular function with magnetic resonance imaging. J. Am. Coll. Cardiol. Img. 3, 860–866 (2010)
Nielsen, P.M.F., Le Grice, I.J., Smaill, B.H., Hunter, P.J.: Mathematical model of geometry and fibrous structure of the heart. Am. J. Physiol. 1378, H1365-H1378 (1991)
Honda, H., et al.: Non-invasive estimation of human left ventricular end-diastolic pressure. Med. Eng. Phys. 6, 485–488 (1998)
McKay, R.G., et al.: Assessment of the end-systolic pressure-volume relationship in human beings with the use of a time-varying elastance model. Circ. 74, 97–104 (1986)
Scali, M., Basso, M., Gandolfo, A., Bombardini, T., Bellotti, P., Sicari, R.: Real Time 3D echocardiography (RT3D) for assessment of ventricular and vascular function in hypertensive and heart failure patients. Cardiovasc. Ultrasound 10(1), 27 (2012)
Guccione, J.M., et al.: Passive material properties of intact ventricular myocardium determined from a cylindrical model. J. Biomech. Eng. 113, 43–55 (1991)
Wang, V.Y., Ennis, D.B., Cowan, B.R., Young, A.A., Nash, M.P.: Myocardial Contractility and Regional Work throughout the Cardiac Cycle Using FEM and MRI. In: Camara, O., Konukoglu, E., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds.) STACOM 2011. LNCS, vol. 7085, pp. 149–159. Springer, Heidelberg (2012)
Hunter, P.J., McCulloch, A.D., ter Keurs, H.E.D.J.: Modelling the mechanical properties of cardiac muscle. Prog. Biophys. and Molec. Biol. 69, 289–331 (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, V.Y., Young, A.A., Cowan, B.R., Nash, M.P. (2013). Changes in In Vivo Myocardial Tissue Properties Due to Heart Failure. In: Ourselin, S., Rueckert, D., Smith, N. (eds) Functional Imaging and Modeling of the Heart. FIMH 2013. Lecture Notes in Computer Science, vol 7945. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38899-6_26
Download citation
DOI: https://doi.org/10.1007/978-3-642-38899-6_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38898-9
Online ISBN: 978-3-642-38899-6
eBook Packages: Computer ScienceComputer Science (R0)