Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Advertisement

Optical Flow Analysis of Left Ventricle Wall Motion with Real-Time Cardiac Magnetic Resonance Imaging in Healthy Subjects and Heart Failure Patients

  • Original Article
  • Published:
Annals of Biomedical Engineering Aims and scope Submit manuscript

This article has been updated

Abstract

In cardiology, magnetic resonance imaging (MRI) provides a clinical standard for measuring ventricular volumes. Owing to their reliability, volumetric measurements with cardiac MRI have become an essential tool for quantitative assessment of ventricular function. However, as volumetric indices are indirectly related to myocardial motion that drives ventricular filling and ejection, cardiac MRI cannot provide comprehensive evaluation of ventricular performance. To overcome this limitation, the presented work sought to measure ventricular wall motion directly with optical flow analysis of real-time cardiac MRI. By modeling left ventricle (LV) walls in real-time images based on myocardial architecture, we developed an optical flow approach to analyzing LV radial and circumferential wall motion for improved quantitative assessment of ventricular function. For proof-of-concept, a cardiac MRI study was conducted with healthy volunteers and heart failure (HF) patients. It was found that, as real-time images provided sufficient temporal information for correlation analysis between different LV wall motion velocity components, optical flow assessment detected the difference of ventricular performance between the HF patients and the healthy volunteers more effectively than volumetric measurements. We expect that this model-based optical flow assessment with real-time cardiac MRI would offer intricate analysis of ventricular function beyond conventional volumetric measurements.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8

Similar content being viewed by others

Change history

  • 27 January 2022

    The original article was revised to correct the editorial responsibility line

References

  1. Alfakih, K., S. Reid, T. Jones, and M. Sivananthan. Assessment of ventricular function and mass by cardiac magnetic resonance imaging. Eur. Radiol. 14:1813–1822, 2004.

    Article  Google Scholar 

  2. Anderson, R. H., S. Y. Ho, K. Redmann, D. Sanchez-Quintana, and P. P. Lunkenheimer. The anatomical arrangement of the myocardial cells making up the ventricular mass. Eur. J. Cardiothorac. Surg. 28:517–525, 2005.

    Article  Google Scholar 

  3. Bellenger, N. G., M. I. Burgess, S. G. Ray, A. Lahiri, A. J. Coats, J. G. Cleland, and D. J. Pennell. Comparison of left ventricular ejection fraction and volumes in heart failure by echocardiography, radionuclide ventriculography and cardiovascular magnetic resonance. Are they interchangeable? Eur. Heart J. 21:1387–1396, 2000.

    Article  CAS  Google Scholar 

  4. Bluemke, D. A., J. L. Boxerman, E. Atalar, and E. R. McVeigh. Segmented K-space cine breath-hold cardiovascular MR imaging: Part 1. Principles and technique. AJR Am. J. Roentgenol. 169:395–400, 1997.

    Article  CAS  Google Scholar 

  5. Chava, R., F. Assis, D. Herzka, and A. Kolandaivelu. Segmented radial cardiac MRI during arrhythmia using retrospective electrocardiogram and respiratory gating. Magn. Reson. Med. 81:1726–1738, 2019.

    Article  Google Scholar 

  6. Claessen, G., P. Claus, M. Delcroix, J. Bogaert, A. L. Gerche, and H. Heidbuchel. Interaction between respiration and right versus left ventricular volumes at rest and during exercise: a real-time cardiac magnetic resonance study. Am. J. Physiol.-Heart Circ. Physiol. 306:H816–H824, 2014.

    Article  CAS  Google Scholar 

  7. Codreanu, I., T. Pegg, J. Selvanayagam, M. Robson, and O. Rider. Comprehensive assessment of left ventricular wall motion abnormalities in coronary artery disease using cardiac magnetic resonance. J. Cardiol. Neuro-cardiovasc. Dis. 2:2, 2015.

    Google Scholar 

  8. Feng, L., R. Grimm, K. T. Block, H. Chandarana, S. Kim, J. Xu, L. Axel, D. K. Sodickson, and R. Otazo. Golden-angle radial sparse parallel MRI: combination of compressed sensing, parallel imaging, and golden-angle radial sampling for fast and flexible dynamic volumetric MRI. Magn. Reson. Med. 72:707–717, 2014.

    Article  Google Scholar 

  9. Hestenes, M. R., and E. Stiefel. Methods of Conjugate Gradients for Solving Linear Systems. Washington: NBS, 1952.

    Book  Google Scholar 

  10. Kallaher, M. J. Affine Planes with Transitive Collineation Groups. North-Holland: University of California, 1982.

    Google Scholar 

  11. King, M., J. E. Kingery, and B. Casey. Diagnosis and evaluation of heart failure. Am. Fam. Phys. 85:1161–1168, 2012.

    Google Scholar 

  12. Klabunde, R. Cardiovascular Physiology Concepts. Philadelphia: Lippincott Williams & Wilkins, 2011.

    Google Scholar 

  13. Konstam, M. A., and F. M. Abboud. Ejection fraction: misunderstood and overrated (changing the paradigm in categorizing heart failure). Circulation. 135:717–719, 2017.

    Article  Google Scholar 

  14. Kramer, C. M., J. Barkhausen, C. Bucciarelli-Ducci, S. D. Flamm, R. J. Kim, and E. Nagel. Standardized cardiovascular magnetic resonance imaging (CMR) protocols: 2020 update. J. Cardiovasc. Magn. Reson. 22:1–18, 2020.

    Article  Google Scholar 

  15. Leong, D. P., C. G. De Pasquale, and J. B. Selvanayagam. Heart failure with normal ejection fraction: the complementary roles of echocardiography and CMR imaging. JACC Cardiovasc. Imaging. 3:409–420, 2010.

    Article  Google Scholar 

  16. Li, Y., M. Edalati, X. Du, H. Wang, and J. J. Cao. Self-calibrated correlation imaging with k-space variant correlation functions. Magn. Reson. Med. 79:1483–1494, 2018.

    Article  Google Scholar 

  17. Li, Y. Y., P. Zhang, S. Rashid, Y. J. Cheng, W. Li, W. Schapiro, K. Gliganic, A.-M. Yamashita, M. Grgas, E. Haag, and J. J. Cao. Real-time exercise stress cardiac MRI with Fourier-series reconstruction from golden-angle radial data. Magn. Reson. Imaging. 75:89–99, 2021.

    Article  Google Scholar 

  18. Lindley, D. Regression and correlation analysis. In: Time Series and Statistics, edited by J. D. Cryer, and K. S. Chan. New York: Springer, 1990, pp. 237–243.

    Chapter  Google Scholar 

  19. Miller, R. G., Jr. Beyond ANOVA: Basics of Applied Statistics. Boca Raton: CRC Press, 1997.

    Book  Google Scholar 

  20. Oppenheim, A. V., J. R. Buck, and R. W. Schafer. Discrete-Time Signal Processing, Vol. 2, Upper Saddle River: Prentice Hall, 2001.

    Google Scholar 

  21. Paragios, N., Y. Chen, and O. Faugeras (eds.). Mathematical Models for Computer Vision: The Handbook, 1st ed., New York: Springer, 2005.

    Google Scholar 

  22. Pedrizzetti, G., P. Claus, P. J. Kilner, and E. Nagel. Principles of cardiovascular magnetic resonance feature tracking and echocardiographic speckle tracking for informed clinical use. J. Cardiovasc. Magn. Reson. 18:51, 2016.

    Article  Google Scholar 

  23. Pluempitiwiriyawej, C., J. M. Moura, Y.-J.L. Wu, and C. Ho. STACS: new active contour scheme for cardiac MR image segmentation. IEEE Trans. Med. Imaging. 24:593–603, 2005.

    Article  Google Scholar 

  24. Sakuma, H., N. Fujita, T. Foo, G. R. Caputo, S. J. Nelson, J. Hartiala, A. Shimakawa, and C. B. Higgins. Evaluation of left ventricular volume and mass with breath-hold cine MR imaging. Radiology. 188:377–380, 1993.

    Article  CAS  Google Scholar 

  25. Schulz-Menger, J., D. A. Bluemke, J. Bremerich, S. D. Flamm, M. A. Fogel, M. G. Friedrich, R. J. Kim, F. von Knobelsdorff-Brenkenhoff, C. M. Kramer, D. J. Pennell, S. Plein, and E. Nagel. Standardized image interpretation and post-processing in cardiovascular magnetic resonance-2020 update: Society for Cardiovascular Magnetic Resonance (SCMR): Board of Trustees Task Force on Standardized Post-Processing. J. Cardiovasc. Magn. Reson. 22:19, 2020.

    Article  Google Scholar 

  26. Sengupta, P. P., A. J. Tajik, K. Chandrasekaran, and B. K. Khandheria. Twist mechanics of the left ventricle: principles and application. JACC Cardiovasc. Imaging. 1:366–376, 2008.

    Article  Google Scholar 

  27. Unterberg-Buchwald, C., M. Fasshauer, J. M. Sohns, W. Staab, A. Schuster, D. Voit, J. T. Kowallick, M. Steinmetz, J. Frahm, and J. Lotz. Real time cardiac MRI and its clinical usefulness in arrhythmias and wall motion abnormalities. J. Cardiovasc. Magn. Reson. 16:P34, 2014.

    Article  Google Scholar 

  28. Zhang, S., M. Uecker, D. Voit, K.-D. Merboldt, and J. Frahm. Real-time cardiovascular magnetic resonance at high temporal resolution: radial FLASH with nonlinear inverse reconstruction. J. Cardiovasc. Magn. Reson. 12:39, 2010.

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to thank Drs Jianing Pang, Mickael Bush and Xiaoming Bi for providing technical support on MRI pulse sequence programming.

Funding

Funding was provided by Foundation for the National Institutes of Health (Grant No. R01EB022405).

Conflict of interest

There is no conflict of interest.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yu Y. Li.

Additional information

Associate Editor Umberto Morbiducci oversaw the review of this article.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

The coefficient terms Am(x,y,z,t-t') and Bmn(x,y,z,t) in Eq. 4 are given as below:

$$A_{0} \left( {x,y,z,t - t^{\prime}} \right) = \left[ {\frac{{\partial I\left( {x,y,z,t} \right)}}{\partial x}\cos \left( \theta \right) + \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial y}\sin \left( \theta \right)} \right]s_{v} \left( {z,t - t^{\prime}} \right)$$
$$A_{1} \left( {x,y,z,t - t^{\prime}} \right) = \left[ {\frac{{\partial I\left( {x,y,z,t} \right)}}{\partial x}\cos \left( \theta \right)\sin \left( \theta \right) + \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial y}\sin^{2} \left( \theta \right)} \right]s_{v} \left( {z,t - t^{\prime}} \right)$$
$$A_{2} \left( {x,y,z,t - t^{\prime}} \right) = \left[ {\frac{{\partial I\left( {x,y,z,t} \right)}}{\partial x}\sin^{2} \left( \theta \right) + \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial y}\cos \left( \theta \right)\sin \left( \theta \right)} \right]s_{v} \left( {z,t - t^{\prime}} \right)$$
$$A_{3} \left( {x,y,z,t - t^{\prime}} \right) = \left[ { - \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial x}r \sin \left( \theta \right) + \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial y}r \cos \left( \theta \right)} \right]s_{v} \left( {z,t - t^{\prime}} \right)$$
$$A_{4} \left( {x,y,z,t - t^{\prime}} \right) = \left[ { - \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial x}r^{2} \sin \left( \theta \right) + \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial y}r^{2} \cos \left( \theta \right)} \right]s_{v} \left( {z,t - t^{\prime}} \right)$$
$$A_{5} \left( {x,y,z,t - t^{\prime}} \right) = \left[ { - \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial x}rz \sin \left( \theta \right) + \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial y}rz \cos \left( \theta \right)} \right]s_{v} \left( {z,t - t^{\prime}} \right)$$
$$B_{0n} \left( {x,y,z,t} \right) = \left[ {\frac{{\partial I\left( {x,y,z,t} \right)}}{\partial x}\cos \left( \theta \right) + \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial y}\sin \left( \theta \right)} \right]\mathop \sum \limits_{{t^{\prime} = 0}}^{{t_{a} }} s_{w} \left( {z,t - t^{\prime}} \right)T_{n} \left( {\frac{{t^{\prime}}}{{t_{a} }}} \right)$$
$$B_{1n} \left( {x,y,z,t} \right) = \left[ {\frac{{\partial I\left( {x,y,z,t} \right)}}{\partial x}x\cos \left( \theta \right) + \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial y}x \sin \left( \theta \right)} \right]\mathop \sum \limits_{{t^{\prime} = 0}}^{{t_{a} }} s_{w} \left( {z,t - t^{\prime}} \right)T_{n} \left( {\frac{{t^{\prime}}}{{t_{a} }}} \right)$$
$$B_{2n} \left( {x,y,z,t} \right) = \left[ {\frac{{\partial I\left( {x,y,z,t} \right)}}{\partial x}y\cos \left( \theta \right) + \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial y}y \sin \left( \theta \right)} \right]\mathop \sum \limits_{{t^{\prime} = 0}}^{{t_{a} }} s_{w} \left( {z,t - t^{\prime}} \right)T_{n} \left( {\frac{{t^{\prime}}}{{t_{a} }}} \right)$$
$$B_{3n} \left( {x,y,z,t} \right) = \left[ { - \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial x}\sin \left( \theta \right) + \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial y}\cos \left( \theta \right)} \right]\mathop \sum \limits_{{t^{\prime} = 0}}^{{t_{a} }} s_{w} \left( {z,t - t^{\prime}} \right)T_{n} \left( {\frac{{t^{\prime}}}{{t_{a} }}} \right)$$
$$B_{4n} \left( {x,y,z,t} \right) = \left[ { - \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial x}x \sin \left( \theta \right) + \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial y}x \cos \left( \theta \right)} \right]\mathop \sum \limits_{{t^{\prime} = 0}}^{{t_{a} }} s_{w} \left( {z,t - t^{\prime}} \right)T_{n} \left( {\frac{{t^{\prime}}}{{t_{a} }}} \right)$$
$$B_{5n} \left( {x,y,z,t} \right) = \left[ { - \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial x}y \sin \left( \theta \right) + \frac{{\partial I\left( {x,y,z,t} \right)}}{\partial y}y \cos \left( \theta \right)} \right]\mathop \sum \limits_{{t^{\prime} = 0}}^{{t_{a} }} s_{w} \left( {z,t - t^{\prime}} \right)T_{n} \left( {\frac{{t^{\prime}}}{{t_{a} }}} \right)$$

where n={0, 1, 2,…, N} is the order of the Chebyshev polynomial Tn(t), I(x,y.z,t) represents a real-time image voxel (x,y) in the slice z and at the time t, (r,θ) is the radial coordinates of the image voxel (x,y) in the slice z, ∂I(x,y,z,t)/∂x represents the partial derivative of the real-time image along the x direction and ∂I(x,y,z,t)/∂y along the y direction, sv(z,t) and sw(z,t) are the systole/diastole and expiration/inspiration binary indicator functions (Fig. 2(c)), and [0,ta] is the data acquisition window.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, Y.Y., Craft, J., Cheng, Y. et al. Optical Flow Analysis of Left Ventricle Wall Motion with Real-Time Cardiac Magnetic Resonance Imaging in Healthy Subjects and Heart Failure Patients. Ann Biomed Eng 50, 195–210 (2022). https://doi.org/10.1007/s10439-022-02907-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10439-022-02907-2

Keywords