Estimation of deformation gradient and strain from cine-PC velocity data [cardiac magnetic resonance imaging]

• Published in: IEEE transactions on medical imaging Vol. 16; no. 6; pp. 840 - 851
• Main Authors: Yudong Zhu, Drangova, M., Pelc, N.J.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.12.1997; Institute of Electrical and Electronics Engineers
• Subjects: Algorithms; Aortic Stenosis, Subvalvular - physiopathology; Biological and medical sciences; Cardiovascular system; Computer Simulation; Data acquisition; Heart; Humans; Image Processing, Computer-Assisted; In vivo; Investigative techniques, diagnostic techniques (general aspects); Magnetic field induced strain; Magnetic field measurement; Magnetic materials; Magnetic resonance imaging; Magnetic Resonance Imaging, Cine; Medical imaging; Medical sciences; Myocardial Contraction; Myocardium; Noninvasive medical procedures; Performance analysis; Phantoms, Imaging; Phase measurement; Physiological models; Radiodiagnosis. Nmr imagery. Nmr spectrometry; Reproducibility of Results; Signal to noise ratio; Strain; Velocity measurement; Human; Computer simulation; Data processing; Velocity distribution; Nuclear magnetic resonance imaging; In vivo; Accuracy; Phase contrast; Myocardium; Medical imagery; Strain distribution; Circulatory system; Quantitative analysis; Test object
• ISSN: 0278-0062; 1558-254X
• DOI: 10.1109/42.650880

Phase contrast magnetic resonance imaging (MRI) can provide in vivo myocardial velocity field measurements. These data allow densely spaced material points to be tracked throughout the whole heart cycle using, for example, the Fourier tracking algorithm. To process the tracking results for myocardial deformation and strain quantification, the authors developed a method that is based on fitting the tracking results to an appropriate local deformation model. They further analyzed the accuracy and precision of the method and provided performance predictions for several local models. In order to validate the method and the theoretical performance analysis, the authors conducted controlled computer simulations and a phantom study. The results agreed well with expectations. Human heart data were also acquired and analyzed, and provided encouraging results. At the signal-to-noise ratio (SNR) level and spatial resolution expected in clinical settings, the study predicts strain quantification accuracy and precision that may allow the technique to become a practical and powerful noninvasive approach for the study of cardiac function, although clinically acceptable data acquisition strategies for three-dimensional (3-D) data are still a challenge.