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Data Processing Techniques to Analyze Large 3-D Deformations of Cardiac Cycles

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Advancement of Optical Methods in Experimental Mechanics, Volume 3

Abstract

Quantification of 3-D deformations of human organs plays an important role in the understanding phenomena that have an impact in medical diagnosis and treatment of diseases. One important example is the mechanics of heart functions. Comparing normal deformation patterns of the cardiac cycle in healthy and diseased individuals can be a diagnostic tool that provides early and accurate indications of the onset of heart diseases.

The tagging technique is an experimental mechanics method that makes it possible to utilize the extensive literature existing on the analysis of deformations utilizing the digital moiré method for accurate and fast quantification of the heart 3-D kinematics. MRI tagging is an imaging technique used in medicine to visualize the structures of tissues of the human body in detail. MRI uses of the phenomenon of nuclear magnetic resonance to image tissues by exciting the nuclei of atoms in the tissue. Because of the different chemical composition of the tissues it can provide details that cannot be visible with CT Scans. By modulating magnetization it is possible to inscribe lattice-patterns in the tissue volume. These lattices are fixed to the under laying tissues for periods of time long enough to follow a cardiac cycle.

The objective of this paper is to outline image processing techniques that can be utilized to decode the displacements and strains taking into consideration that one is dealing with large 3-D deformations that form a time sequence of images. These techniques are based on fundamental principles that have been developed in the field of digital moiré.

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References

  1. Sciammarella CA, Lamberti L, Sciammarella FM, Boccaccio A (2014) The kinematics and dynamics of 3-D displacement fields. In: Jin H, Sciammarella CA, Yoshida S, Lamberti L (eds) Advancement of optical methods in experimental mechanics. Springer, New York, NY, pp 43–67, Chapter 7

    Chapter  Google Scholar 

  2. Sciammarella CA, Lamberti L (2014) Basic models supporting experimental mechanics of deformations, geometrical representations, connections among different techniques. To appear in Meccanica, Special Issue on “Experimental Solid Mechanics: in honour of Professor Emmanuel Gdoutos”. Early View 8 January 2014. http://link.springer.com/article/10.1007%2Fs11012-013-9867-8

  3. Axel L, Dougherty L (1989) Heart wall motion: improved method of spatial modulation of magnetization for MR imaging. Radiology 172(2):349–350

    Article  Google Scholar 

  4. Axel L, Dougherty L (1989) MR imaging of motion with spatial modulation of magnetization. Radiology 171:841–845

    Article  Google Scholar 

  5. McVeigh E (1997) MRI of myocardial function: motion tracking techniques. Magn Reson Med 14(2):137–150

    Google Scholar 

  6. Fischer SE, McKinnon GC, Scheidegger MB, Prins W, Meier D, Boesiger P (1994) True myocardial motion tracking. Magn Reson Med 31(4):401–413

    Article  Google Scholar 

  7. Doyle M, Walsh EG, Foster RE, Pohost GM (1997) Common k-space acquisition: a method to improve myocardial grid-tag contrast. Magn Reson Med 37(5):754–763

    Article  Google Scholar 

  8. Zhang S, Douglas M, Yaroslavsky L, Summers R, Dilsizen V, Fananapazir L, Bacharach S (1996) A Fourier based algorithm for tracking spam tags in gated magnetic resonance cardiac images. Med Phys 23(8):1359–1369

    Article  Google Scholar 

  9. Liao JR, Pauly JM, Brosnan TJ, Pelc NJ (1997) Reduction of motion artifacts in cine MRI using variable-density spiral trajectory. Magn Reson Med 37(4):569–575

    Article  Google Scholar 

  10. Guttman MA, Prince JL, McVeigh ER (1994) Tag and contour detection in tagged MR images of the left ventricle. IEEE Trans Med Imaging 13(1):74–88

    Article  Google Scholar 

  11. Kumar S, Goldgof D (1993) Automatic tracking of SPAMM grid and the estimation of deformation parameters from cardiac MR images. IEEE Trans Med Imaging 13(1):122–132

    Article  Google Scholar 

  12. O'Dell WG, Moore CC, Hunter WC, Zerhouni EA, McVeigh ER (1995) Three-dimensional myocardial deformations: Calculations with displacement field fitting of tagged MR images. Radiology 195:829–835

    Article  Google Scholar 

  13. Denney TS, Prince JL (1995) Reconstruction of 3-D left ventricular motion from planar tagged cardiac MR images: an estimation theoretic approach. IEEE Trans Med Imaging 14(4):625–635

    Article  Google Scholar 

  14. Radeva P, Amini A, Huang J (1997) Deformable B-solids and implicit snakes for localization and tracking of SPAMM MRI-data. Comput Vis Image Underst 66(2):163–178

    Article  Google Scholar 

  15. Denney TS (1997) Identification of myocardial tags in tagged MR images without prior knowledge of myocardial contours. In: Inform. Processing in medical imaging—Lecture Notes in Computer Science 1230:327–340

    Google Scholar 

  16. Prince JL, McVeigh ER (1992) Motion estimation from tagged MR image sequences. IEEE Trans Med Imaging 11(2):238–249

    Article  Google Scholar 

  17. Gupta SN, Prince JL (1995) On variable brightness optical flow for tagged MRI. Technical Report 95-13, JHU/ECE

    Google Scholar 

  18. Gupta SN, Prince JL, Androutsellis-Theotokis S (1997) Bandpass optical flow for tagged MR imaging. In: Proceedings of the IEEE international conference on image processing, vol 3, Santa Barbara, CA, October 1997, pp 364–367

    Google Scholar 

  19. Pelc NJ, Herfkens RJ, Shimakawa A, Enzmann DR (1991) Phase contrast cine magnetic resonance imaging. Magn Reson Q 7(4):229–254

    Google Scholar 

  20. Pelc NJ, Drangova M, Pelc LR, Zhu Y, Noll DC, Bowman BS, Herfkens RJ (1995) Tracking of cyclic motion with phase-contrast cine MR velocity data. J Magn Reson Imaging 5(3):339–345

    Article  Google Scholar 

  21. Constable RT, Rath KM, Sinusas AJ, Gore JC (1994) Development and evaluation of tracking algorithms for cardiac wall motion analysis using phase velocity MR imaging. Magn Reson Med 32(1):33–42

    Article  Google Scholar 

  22. Meyer FG, Constable RT, Sinusas AJ, Duncan JS (1996) Tracking myocardial deformation using phase contrast MR velocity fields: a stochastic approach. IEEE Trans Med Imaging 15(4):453–465

    Article  Google Scholar 

  23. Wedeen VJ (1992) Magnetic resonance imaging of myocardial kinematics. Technique to detect, localize and quantify the strain rates of the active human myocardium. Magn Reson Med 27(1):52–67

    Article  Google Scholar 

  24. Robson MD, Constable RT (1996) Three-dimensional strain-rate imaging. Magn Reson Med 36(4):537–546

    Article  Google Scholar 

  25. Perman WH, Creswell LL, Wyers SG, Moulton MJ, Pasque MK (1995) Hybrid DANTE and phase-contrast imaging technique for measurement of three-dimensional myocardial wall motion. J Magn Reson Imaging 5(1):101–106

    Article  Google Scholar 

  26. Osman NF, Kerwin WS, McVeigh ER, Prince JL (1999) Cardiac motion tracking using CINE harmonic phase (HARP) magnetic resonance imaging. Magn Reson Med 42(6):1048–1060

    Article  Google Scholar 

  27. Zerhouni EA, Parish DM, Rogers WJ, Yang A, Shapiro EP (1988) Human heart: tagging with MR imaging—a method for noninvasive assessment of myocardial motion. Radiology 169(1):59–63

    Article  Google Scholar 

  28. Nguyen TD, Reeves SJ, Denney TS (1998) New magnetic resonance tagging technique for directly measuring the strain tensor of the in vivo human heart. In: Proceedings of IEEE conference on image processing, Chicago, IL, October 1998

    Google Scholar 

  29. Moon-Ho Song S, Napel S, Pelc NJ, Glover GH (1995) Phase unwrapping of MR phase images using Poisson equation. IEEE Trans Image Process 4(5):667–676

    Article  Google Scholar 

  30. Waks E, Prince JL, Douglas AS (1996) Cardiac motion simulator for tagged MRI. In: Proceedings of workshop on mathematical methods in biomedical image analysis, San Francisco, CA, pp 182–191

    Google Scholar 

  31. Wyman BT, Hunter WC, Prinzen FW, McVeigh ER (1999) Mapping propagation of mechanical activation in the paced heart with MRI tagging. Am J Physiol 276:H881–H891

    Google Scholar 

  32. Garot J, Bluemke DA, Osman NF, Rochitte CE, McVeigh ER, Zerhouni EA, Prince JL, Lima JAC (2000) Fast determination of regional myocardial strain fields from tagged cardiac images using harmonic phase MRI. Circulation 101:981–988

    Article  Google Scholar 

  33. Sciammarella CA, Sciammarella FM (2012) Experimental mechanics of solids. Wiley, Chichester

    Book  Google Scholar 

  34. Durelli AJ, Parks VJ (1970) Moiré analysis of strain. Prentice-Hall, Englewood Cliffs, NJ

    Google Scholar 

  35. General Stress Optics Inc. Holo-Moiré Strain Analyzer Software HoloStrain Version 2.0. General Stress Optics Inc., Chicago, IL, http://www.stressoptics.com

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Author information

Authors and Affiliations

  1. Department of Mechanical, Materials and Aerospace Engineering, Illinois Institute of Technology, 10 SW 32nd Street, 60616, Chicago, IL, USA

    C. A. Sciammarella

  2. Department of Mechanical Engineering, College of Engineering and Engineering Technology, Northern Illinois University, 590 Garden Road, 60115, DeKalb, IL, USA

    C. A. Sciammarella

  3. Dipartimento Meccanica, Matematica e Management, Politecnico di Bari, Viale Japigia 182, 70126, Bari, Italy

    L. Lamberti & A. Boccaccio

Authors
  1. C. A. Sciammarella
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  2. L. Lamberti
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  3. A. Boccaccio
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Corresponding author

Correspondence to C. A. Sciammarella .

Editor information

Editors and Affiliations

  1. Sandia National Laboratories, Livermore, USA

    Helena Jin

  2. Illinois Institute of Technology, Chicago, Illinois, USA

    Cesar Sciammarella

  3. Southeastern Louisiana University, Hammond, USA

    Sanichiro Yoshida

  4. Bari, Italy

    Luciano Lamberti

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Sciammarella, C.A., Lamberti, L., Boccaccio, A. (2015). Data Processing Techniques to Analyze Large 3-D Deformations of Cardiac Cycles. In: Jin, H., Sciammarella, C., Yoshida, S., Lamberti, L. (eds) Advancement of Optical Methods in Experimental Mechanics, Volume 3. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-06986-9_7

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  • DOI: https://doi.org/10.1007/978-3-319-06986-9_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06985-2

  • Online ISBN: 978-3-319-06986-9

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