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Perfusion

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Book cover Basic Principles of Cardiovascular MRI

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Abstract

Myocardial perfusion is an important measurement in the diagnosis and management of coronary artery disease. While clinical measurement of myocardial perfusion has long been dominated by nuclear imaging, MRI has recently emerged as an alternative method with many significant advantages. Compared to single photon emission computed tomography (SPECT), MRI has much higher resolution, requires no radiation dose, and has the potential for more quantitative measurements. MR perfusion measurement can be complex, however, and when designing an MR perfusion experiment there are a variety of choices to consider. Unfortunately, there is no consensus MRI perfusion implementation that is best for all situations, and choosing the ideal parameters for a given scan requires a careful understanding of the pros and cons of each component of an MRI perfusion experiment. In this chapter, we discuss the different components of cardiac perfusion MRI including pulse sequences, image readout, acceleration techniques, and image analysis. In each section, we review the basic theory behind each technique and then discuss their relative advantages and disadvantages. We conclude with a brief discussion of emerging techniques that are currently being researched.

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References

  1. Stirrat J, White JA. The prognostic role of late gadolinium enhancement magnetic resonance imaging in patients with cardiomyopathy. Can J Cardiol. 2013;29(3):329–36.

    Article  PubMed  Google Scholar 

  2. Cook SC, Ferketich AK, Raman SV. Myocardial ischemia in asymptomatic adults with repaired aortic coarctation. Int J Cardiol. 2009;133(1):95–101.

    Article  PubMed  Google Scholar 

  3. Wang L, et al. Coronary risk factors and myocardial perfusion in asymptomatic adults: the Multi-Ethnic Study of Atherosclerosis (MESA). J Am Coll Cardiol. 2006;47(3):565–72.

    Article  PubMed  Google Scholar 

  4. Klocke FJ, et al. ACC/AHA/ASNC guidelines for the clinical use of cardiac radionuclide imaging – executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (ACC/AHA/ASNC Committee to Revise the 1995 Guidelines for the Clinical Use of Cardiac Radionuclide Imaging). J Am Coll Cardiol. 2003;42(7):1318–33.

    Article  PubMed  Google Scholar 

  5. Jerosch-Herold M. Quantification of myocardial perfusion by cardiovascular magnetic resonance. J Cardiovasc Magn Reson. 2010;12:57.

    Article  PubMed Central  PubMed  Google Scholar 

  6. Kellman P, Arai AE. Imaging sequences for first pass perfusion – a review. J Cardiovasc Magn Reson. 2007;9(3):525–37.

    Article  PubMed  Google Scholar 

  7. Coelho-Filho OR, et al. MR myocardial perfusion imaging. Radiology. 2013;266(3):701–15.

    Article  PubMed  Google Scholar 

  8. Gerber BL, et al. Myocardial first-pass perfusion cardiovascular magnetic resonance: history, theory, and current state of the art. J Cardiovasc Magn Reson. 2008;10:18.

    Article  PubMed Central  PubMed  Google Scholar 

  9. Jerosch-Herold M, et al. Analysis of myocardial perfusion MRI. J Magn Reson Imaging. 2004;19(6):758–70.

    Article  PubMed  Google Scholar 

  10. Zhang H, et al. Accurate myocardial T1 measurements: toward quantification of myocardial blood flow with arterial spin labeling. Magn Reson Med. 2005;53(5):1135–42.

    Article  PubMed  Google Scholar 

  11. Wright KB, et al. Assessment of regional differences in myocardial blood flow using T2-weighted 3D BOLD imaging. Magn Reson Med. 2001;46(3):573–8.

    Article  CAS  PubMed  Google Scholar 

  12. Tsekos NV, et al. Fast anatomical imaging of the heart and assessment of myocardial perfusion with arrhythmia insensitive magnetization preparation. Magn Reson Med. 1995;34(4):530–6.

    Article  CAS  PubMed  Google Scholar 

  13. Kim D, Cernicanu A, Axel L. B(0) and B(1)-insensitive uniform T(1)-weighting for quantitative, first-pass myocardial perfusion magnetic resonance imaging. Magn Reson Med. 2005;54(6):1423–9.

    Article  PubMed  Google Scholar 

  14. Kim D, et al. Comparison of the effectiveness of saturation pulses in the heart at 3T. Magn Reson Med. 2008;59(1):209–15.

    Article  PubMed  Google Scholar 

  15. Haase A, et al. Inversion recovery snapshot FLASH MR imaging. J Comput Assist Tomogr. 1989;13(6):1036–40.

    Article  CAS  PubMed  Google Scholar 

  16. Ding S, Wolff SD, Epstein FH. Improved coverage in dynamic contrast-enhanced cardiac MRI using interleaved gradient-echo EPI. Magn Reson Med. 1998;39(4):514–9.

    Article  CAS  PubMed  Google Scholar 

  17. Schreiber WG, et al. Dynamic contrast-enhanced myocardial perfusion imaging using saturation-prepared TrueFISP. J Magn Reson Imaging. 2002;16(6):641–52.

    Article  PubMed  Google Scholar 

  18. Fenchel M, et al. Multislice first-pass myocardial perfusion imaging: comparison of saturation recovery (SR)-TrueFISP-two-dimensional (2D) and SR-TurboFLASH-2D pulse sequences. J Magn Reson Imaging. 2004;19(5):555–63.

    Article  PubMed  Google Scholar 

  19. Lyne JC, et al. Direct comparison of myocardial perfusion cardiovascular magnetic resonance sequences with parallel acquisition. J Magn Reson Imaging. 2007;26(6):1444–51.

    Article  PubMed  Google Scholar 

  20. Sodickson DK, Manning WJ. Simultaneous acquisition of spatial harmonics (SMASH): fast imaging with radiofrequency coil arrays. Magn Reson Med. 1997;38(4):591–603.

    Article  CAS  PubMed  Google Scholar 

  21. Pruessmann KP, et al. SENSE: sensitivity encoding for fast MRI. Magn Reson Med. 1999;42(5):952–62.

    Article  CAS  PubMed  Google Scholar 

  22. Griswold MA, et al. Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn Reson Med. 2002;47(6):1202–10.

    Article  PubMed  Google Scholar 

  23. Tsao J, Boesiger P, Pruessmann KP. k-t BLAST and k-t SENSE: dynamic MRI with high frame rate exploiting spatiotemporal correlations. Magn Reson Med. 2003;50(5):1031–42.

    Article  PubMed  Google Scholar 

  24. Mistretta CA, et al. Highly constrained backprojection for time-resolved MRI. Magn Reson Med. 2006;55(1):30–40.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  25. Ge L, et al. Myocardial perfusion MRI with sliding-window conjugate-gradient HYPR. Magn Reson Med. 2009;62(4):835–9.

    Article  PubMed  Google Scholar 

  26. Kozerke S, Tsao J. Reduced data acquisition methods in cardiac imaging. Top Magn Reson Imaging. 2004;15(3):161–8.

    Article  PubMed  Google Scholar 

  27. Grist TM, et al. Time-resolved angiography: past, present, and future. J Magn Reson Imaging. 2012;36(6):1273–86.

    Article  PubMed  Google Scholar 

  28. Deshmane A, et al. Parallel MR imaging. J Magn Reson Imaging. 2012;36(1):55–72.

    Article  PubMed Central  PubMed  Google Scholar 

  29. Pedersen H, et al. Quantification of myocardial perfusion using free-breathing MRI and prospective slice tracking. Magn Reson Med. 2009;61(3):734–8.

    Article  PubMed  Google Scholar 

  30. Milles J, et al. Fully automated motion correction in first-pass myocardial perfusion MR image sequences. IEEE Trans Med Imaging. 2008;27(11):1611–21.

    Article  PubMed  Google Scholar 

  31. Stegmann MB, Olafsdottir H, Larsson HB. Unsupervised motion-compensation of multi-slice cardiac perfusion MRI. Med Image Anal. 2005;9(4):394–410.

    Article  CAS  PubMed  Google Scholar 

  32. Bidaut LM, Vallee JP. Automated registration of dynamic MR images for the quantification of myocardial perfusion. J Magn Reson Imaging. 2001;13(4):648–55.

    Article  CAS  PubMed  Google Scholar 

  33. Yang GZ, et al. Motion and deformation tracking for short-axis echo-planar myocardial perfusion imaging. Med Image Anal. 1998;2(3):285–302.

    Article  CAS  PubMed  Google Scholar 

  34. Scott AD, Keegan J, Firmin DN. Motion in cardiovascular MR imaging. Radiology. 2009;250(2):331–51.

    Article  PubMed  Google Scholar 

  35. Di Bella EV, Parker DL, Sinusas AJ. On the dark rim artifact in dynamic contrast-enhanced MRI myocardial perfusion studies. Magn Reson Med. 2005;54(5):1295–9.

    Article  PubMed Central  PubMed  Google Scholar 

  36. Sharma P, et al. Effect of Gd-DTPA-BMA on blood and myocardial T1 at 1.5T and 3T in humans. J Magn Reson Imaging. 2006;23(3):323–30.

    Article  PubMed  Google Scholar 

  37. Kim D, Axel L. Multislice, dual-imaging sequence for increasing the dynamic range of the contrast-enhanced blood signal and CNR of myocardial enhancement at 3T. J Magn Reson Imaging. 2006;23(1):81–6.

    Article  PubMed  Google Scholar 

  38. Noeske R, et al. Human cardiac imaging at 3 T using phased array coils. Magn Reson Med. 2000;44(6):978–82.

    Article  CAS  PubMed  Google Scholar 

  39. Lee DC, Johnson NP. Quantification of absolute myocardial blood flow by magnetic resonance perfusion imaging. JACC Cardiovasc Imaging. 2009;2(6):761–70.

    Article  PubMed  Google Scholar 

  40. Klem I, et al. Improved detection of coronary artery disease by stress perfusion cardiovascular magnetic resonance with the use of delayed enhancement infarction imaging. J Am Coll Cardiol. 2006;47(8):1630–8.

    Article  PubMed  Google Scholar 

  41. Christian TF, et al. Absolute myocardial perfusion in canines measured by using dual-bolus first-pass MR imaging. Radiology. 2004;232(3):677–84.

    Article  PubMed  Google Scholar 

  42. Aquaro GD, et al. A fast and effective method of quantifying myocardial perfusion by magnetic resonance imaging. Int J Cardiovasc Imaging. 2013;29(6):1313–24.

    Article  PubMed  Google Scholar 

  43. Thompson Jr HK, et al. Indicator transit time considered as a gamma variate. Circ Res. 1964;14:502–15.

    Article  PubMed  Google Scholar 

  44. Gatehouse PD, et al. Accurate assessment of the arterial input function during high-dose myocardial perfusion cardiovascular magnetic resonance. J Magn Reson Imaging. 2004;20(1):39–45.

    Article  PubMed  Google Scholar 

  45. Fluckiger JU, et al. Absolute quantification of myocardial blood flow with constrained estimation of the arterial input function. J Magn Reson Imaging. 2013;38(3):603–9.

    Article  PubMed  Google Scholar 

  46. Cernicanu A, Axel L. Theory-based signal calibration with single-point T1 measurements for first-pass quantitative perfusion MRI studies. Acad Radiol. 2006;13(6):686–93.

    Article  PubMed  Google Scholar 

  47. Hsu LY, Kellman P, Arai AE. Nonlinear myocardial signal intensity correction improves quantification of contrast-enhanced first-pass MR perfusion in humans. J Magn Reson Imaging. 2008;27(4):793–801.

    Article  PubMed  Google Scholar 

  48. Jacquier A, et al. Quantification of myocardial blood flow and flow reserve in rats using arterial spin labeling MRI: comparison with a fluorescent microsphere technique. NMR Biomed. 2011;24(9):1047–53.

    Article  PubMed  Google Scholar 

  49. Troalen T, et al. Cine-ASL: a steady-pulsed arterial spin labeling method for myocardial perfusion mapping in mice. Part I. Experimental study. Magn Reson Med. 2013;70(5):1389–98.

    Article  PubMed  Google Scholar 

  50. Abeykoon S, Sargent M, Wansapura JP. Quantitative myocardial perfusion in mice based on the signal intensity of flow sensitized CMR. J Cardiovasc Magn Reson. 2012;14:73.

    Article  PubMed Central  PubMed  Google Scholar 

  51. McCommis KS, et al. Feasibility study of myocardial perfusion and oxygenation by noncontrast MRI: comparison with PET study in a canine model. Magn Reson Imaging. 2008;26(1):11–9.

    Article  PubMed Central  PubMed  Google Scholar 

  52. Zun Z, Wong EC, Nayak KS. Assessment of myocardial blood flow (MBF) in humans using arterial spin labeling (ASL): feasibility and noise analysis. Magn Reson Med. 2009;62(4):975–83.

    Article  PubMed  Google Scholar 

  53. Northrup BE, et al. Resting myocardial perfusion quantification with CMR arterial spin labeling at 1.5 T and 3.0 T. J Cardiovasc Magn Reson. 2008;10:53.

    Article  PubMed Central  PubMed  Google Scholar 

  54. Do HP, Jao TR, Nayak KS. Myocardial arterial spin labeling perfusion imaging with improved sensitivity. J Cardiovasc Magn Reson. 2014;16(1):15.

    Article  PubMed Central  PubMed  Google Scholar 

  55. Walcher T, et al. Myocardial perfusion reserve assessed by T2-prepared steady-state free precession blood oxygen level-dependent magnetic resonance imaging in comparison to fractional flow reserve. Circ Cardiovasc Imaging. 2012;5(5):580–6.

    Article  PubMed  Google Scholar 

  56. Arnold JR, et al. Myocardial oxygenation in coronary artery disease: insights from blood oxygen level-dependent magnetic resonance imaging at 3 tesla. J Am Coll Cardiol. 2012;59(22):1954–64.

    Article  PubMed  Google Scholar 

  57. Shea SM, et al. T2-prepared steady-state free precession blood oxygen level-dependent MR imaging of myocardial perfusion in a dog stenosis model. Radiology. 2005;236(2):503–9.

    Article  PubMed  Google Scholar 

  58. Tsaftaris SA, et al. Ischemic extent as a biomarker for characterizing severity of coronary artery stenosis with blood oxygen-sensitive MRI. J Magn Reson Imaging. 2012;35(6):1338–48.

    Article  PubMed Central  PubMed  Google Scholar 

  59. Ghugre NR, et al. Myocardial BOLD imaging at 3 T using quantitative T2: application in a myocardial infarct model. Magn Reson Med. 2011;66(6):1739–47.

    Article  PubMed  Google Scholar 

  60. Fieno DS, et al. Myocardial perfusion imaging based on the blood oxygen level-dependent effect using T2-prepared steady-state free-precession magnetic resonance imaging. Circulation. 2004;110(10):1284–90.

    Article  PubMed  Google Scholar 

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Author information

Authors and Affiliations

  1. Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

    Daniel C. Lee MD

  2. Northwestern University Feinberg School of Medicine, Chicago, IL, USA

    Neil R. Chatterjee BS

  3. Department of Radiology, Northwestern Memorial Hospital, Chicago, IL, USA

    Timothy J. Carroll PhD

Authors
  1. Daniel C. Lee MD
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  2. Neil R. Chatterjee BS
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  3. Timothy J. Carroll PhD
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Corresponding author

Correspondence to Daniel C. Lee MD .

Editor information

Editors and Affiliations

  1. Department of Medicine, Loyola University Medical Center, Maywood, Illinois, USA

    Mushabbar A. Syed

  2. The Ohio State University, Columbus, Ohio, USA

    Subha V. Raman

  3. The Ohio State University, Columbus, Ohio, USA

    Orlando P. Simonetti

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© 2015 Springer International Publishing Switzerland

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Lee, D.C., Chatterjee, N.R., Carroll, T.J. (2015). Perfusion. In: Syed, M., Raman, S., Simonetti, O. (eds) Basic Principles of Cardiovascular MRI. Springer, Cham. https://doi.org/10.1007/978-3-319-22141-0_13

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  • DOI: https://doi.org/10.1007/978-3-319-22141-0_13

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22140-3

  • Online ISBN: 978-3-319-22141-0

  • eBook Packages: MedicineMedicine (R0)

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