Abstract
Ultrasound Myocardial Elastography (UME) and Tagged Magnetic Resonance Imaging (tMRI) are two imaging modalities that were developed in the recent years to quantitatively estimate the myocardial deformations. Tagged MRI is currently considered as the gold standard for myocardial strain mapping in vivo. However, despite the low SNR nature of ultrasound signals, echocardiography enjoys the wides- pread availability in the clinic, as well as its low cost and high temporal resolution. Comparing the strain estimation performances of the two techniques has been of great interests to the community. In order to assess the cardiac deformation across different imaging modalities, in this paper, we developed a semi-automatic intensity and gradient based registration framework that rigidly registers the 3D tagged MRIs with the 2D ultrasound images. Based on the two registered modalities, we conducted spatially and temporally more detailed quantitative strain comparison of the RF-based UME technique and tagged MRI. From the experimental results, we conclude that qualitatively the two modalities share similar overall trends. But error and variations in UME accumulate over time. Quantitatively tMRI is more robust and accurate than UME.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Konofagou, E.E., Dhhooge, J., Ophir, J.: Myocardial elastography-a feasibility study in vivo. Ultrasound in Med. & Bio. 28(4), 475–482 (2002)
Lee, W.N., Konofagou, E.E.: Analysis of 3D motion effects in 2D myocardial elastography. In: IEEE-UFFC Symp. Proc. pp. 1217–1220 (2006)
Notomi, Y., et al.: Measurement of ventricular torsion by two-dimensional ultrasound speckle tracking imaging. J. Am. Coll. Cardiol. 45, 2034–2041 (2005)
Helle-Valle, T., et al.: New noninvasive method for assessment of left ventricular rotation - speckle tracking echocardiography. Circulation 112, 3149–3156 (2005)
Cho, G., et al.: Comparison of two-dimensional speckle and tissue velocity based strain and validation with harmonic phase magnetic resonance imaging. The American Journal of Cardiology 97, 1661–1666 (2006)
Lee, W., et al.: Validation of ultrasound myocardial elastography using MR tagging in normal human hearts in vivo. In: ISBI (2007)
Makela, T., et al.: A review of cardiac image registration methods. IEEE Trans. Med. Imaging 21(9), 1011–1021 (2002)
Roche, A., Pennec, X., Malandain, G., Ayache, N.: Rigid registration of 3D ultrasound with MR images: a new approach combining intensity and gradient information. IEEE Trans. Med. Imaging 20(10), 1038–1049 (2001)
Huang, X., et al.: Dynamic 3D ultrasound and MR image registration of the beating heart. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3750, pp. 171–178. Springer, Heidelberg (2005)
Manglik, T., et al.: Use of bandpass Gabor filters for enhancing blood-myocardium contrast and filling-in tags in tagged MR images. In: Proc of ISMRM p. 1793 (2004)
Lai, W.M.: Introduction to Continuum Mechanics, 3rd edn. Butterworth-Heinemann (1993)
Kallel, F., Ophir, J.: A least-squares strain estimator for elastography. Ultrasound Imaging 19, 195–208 (1997)
Qian, Z., Metaxas, D., Axel, L.: Extraction and tracking of MRI tagging sheets using a 3D Gabor filter bank. In: Proc. of Int’l. Conf. of the Engineering in Medicine and Biology Society (2006)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Qian, Z., Lee, WN., Konofagou, E.E., Metaxas, D.N., Axel, L. (2007). Ultrasound Myocardial Elastography and Registered 3D Tagged MRI: Quantitative Strain Comparison. In: Ayache, N., Ourselin, S., Maeder, A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007. MICCAI 2007. Lecture Notes in Computer Science, vol 4791. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75757-3_97
Download citation
DOI: https://doi.org/10.1007/978-3-540-75757-3_97
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75756-6
Online ISBN: 978-3-540-75757-3
eBook Packages: Computer ScienceComputer Science (R0)