Advertisement

Quantification of PET Myocardial Blood Flow

  • Matthieu Pelletier-Galarneau
  • Patrick Martineau
  • Georges El FakhriEmail author
Nuclear Cardiology (V Dilsizian, Section Editor)
  • 61 Downloads
Part of the following topical collections:
  1. Topical Collection on Nuclear Cardiology

Abstract

Purpose of Review

The aim of this review is to provide an update on quantification of myocardial blood flow (MBF) with positron emission tomography (PET) imaging. Technical and clinical aspects of flow quantification with PET are reviewed.

Recent Findings

The diagnostic and prognostic values of myocardial flow quantification have been established in numerous studies and in various populations. MBF quantification has also shown itself to be particularly useful in the assessment of coronary microvascular dysfunction and in evaluation of cardiac allograft vasculopathy. Overall, myocardial flow reserve (MFR) and hyperemic MBF can lead to improved risk stratification by providing information complementary to that of other markers of disease severity, such as fractional flow reserve.

Summary

Flow quantification enhances MPI’s ability to detect both significant epicardial disease and microvascular dysfunction. With recent technological and methodological advances, flow quantification with PET is no longer restricted to cyclotron-equipped academic centers.

Keywords

Positron emission tomography Myocardial blood flow Myocardial flow reserve Coronary artery disease Myocardial perfusion imaging 

Notes

Compliance with Ethical Standards

Conflict of Interest

Matthieu Pelletier-Galarneau and Patrick Martineau declare that they have no conflict of interest.

Georges El Fakhri reports a patent issued that is titled Fast, Unique and Robust Factor Analysis (on estimation of Inout Function and Quantification of MBF) with royalties paid to INVIA, LLC.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. 1.
    Ward RP, Al-Mallah MH, Grossman GB, Hansen CL, Hendel RC, Kerwin TC, et al. American Society of Nuclear Cardiology review of the ACCF/ASNC appropriateness criteria for single-photon emission computed tomography myocardial perfusion imaging (SPECT MPI). J Nucl Cardiol. 2007;14:e26–38.CrossRefGoogle Scholar
  2. 2.
    Jaarsma C, Leiner T, Bekkers SC, Crijns HJ, Wildberger JE, Nagel E, et al. Diagnostic performance of noninvasive myocardial perfusion imaging using single-photon emission computed tomography, cardiac magnetic resonance, and positron emission tomography imaging for the detection of obstructive coronary artery disease: a meta-analysis. J Am Coll Cardiol. 2012;59:1719–28.CrossRefGoogle Scholar
  3. 3.
    Shanoudy H, Raggi P, Beller GA, Soliman A, Ammermann EG, Kastner RJ, et al. Comparison of technetium-99m tetrofosmin and thallium-201 single-photon emission computed tomographic imaging for detection of myocardial perfusion defects in patients with coronary artery disease. J Am Coll Cardiol. 1998;31:331–7.CrossRefGoogle Scholar
  4. 4.
    Burrell S, MacDonald A. Artifacts and pitfalls in myocardial perfusion imaging. J Nucl Med Technol. 2006;34:193–211.PubMedGoogle Scholar
  5. 5.
    Lima RSL, Watson DD, Goode AR, Siadaty MS, Ragosta M, Beller GA, et al. Incremental value of combined perfusion and function over perfusion alone by gated SPECT myocardial perfusion imaging for detection of severe three-vessel coronary artery disease. J Am Coll Cardiol. 2003;42:64–70.CrossRefGoogle Scholar
  6. 6.
    Bing RJ, Bennish A, Bluemchen G, Cohen A, Gallagher JP, Zaleski EJ. Determination of coronary flow equivalent with coincidence counting technic. Circulation. 1964;29:833–46.CrossRefGoogle Scholar
  7. 7.
    RUBY-FILL® (Rubidium Rb82 Generator) [package insert]. Jubilant DRAXIMAGE Inc., Kirkland, Québec, Canada. 2016.Google Scholar
  8. 8.
    Ghotbi AA, Kjær A, Hasbak P. Review: comparison of PET rubidium-82 with conventional SPECT myocardial perfusion imaging. Clin Physiol Funct Imaging. 2014;34:163–70.CrossRefGoogle Scholar
  9. 9.
    Dilsizian V, Taillefer R. Journey in evolution of nuclear cardiology: will there be another quantum leap with the F-18-labeled myocardial perfusion tracers? JACC Cardiovasc Imaging. 2012;5:1269–84.CrossRefGoogle Scholar
  10. 10.
    Sherif HM, Nekolla SG, Saraste A, Reder S, Yu M, Robinson S, et al. Simplified quantification of myocardial flow reserve with flurpiridaz F 18: validation with microspheres in a pig model. J Nucl Med. 2011;52:617–24.CrossRefGoogle Scholar
  11. 11.
    •• Murthy VL, Bateman TM, Beanlands RS, Berman DS, Borges-Neto S, Chareonthaitawee P, et al. Clinical quantification of myocardial blood flow using PET: joint position paper of the SNMMI cardiovascular council and the ASNC. J Nucl Med. 2018;59:273–93. Recent joint position paper of the SNMMI and ASNC with extensive and critical literature review as well as procedural recommendations for PET MPI and MBF quantification. CrossRefGoogle Scholar
  12. 12.
    •• Dilsizian V, Bacharach SL, Beanlands RS, Bergmann SR, Delbeke D, Dorbala S, et al. ASNC imaging guidelines/SNMMI procedure standard for positron emission tomography (PET) nuclear cardiology procedures. J Nucl Cardiol. 2016;23:1187–226. Joint position paper of the SNMMI and ASNC with extensive and critical literature review as well as procedural recommendations for PET quality control. CrossRefGoogle Scholar
  13. 13.
    Dekemp RA, Declerck J, Klein R, Pan X-B, Nakazato R, Tonge C, et al. Multisoftware reproducibility study of stress and rest myocardial blood flow assessed with 3D dynamic PET/CT and a 1-tissue-compartment model of 82Rb kinetics. J Nucl Med. 2013;54:571–7.CrossRefGoogle Scholar
  14. 14.
    Alpert N, Dean Fang Y-H, Fakhri GE. Single-scan rest/stress imaging 18F-labeled flow tracers. Med Phys. 2012;39:6609–20.CrossRefGoogle Scholar
  15. 15.
    Guehl NJ, Normandin MD, Wooten DW, Rozen G, Ruskin JN, Shoup TM, et al. Rapid computation of single PET scan rest-stress myocardial blood flow parametric images by table look up. Med Phys. 2017;44:4643–51.CrossRefGoogle Scholar
  16. 16.
    • Guehl NJ, Normandin MD, Wooten DW, Rozen G, Sitek A, Ruskin J, et al. Single-scan rest/stress imaging: validation in a porcine model with 18F-Flurpiridaz. Eur J Nucl Med Mol Imaging. 2017;44:1538–46. This paper validates a shortened PET MPI protocol with flurpiridaz. With the proposed protocol, both rest and stress acquisitions can be obtained within less than 15 min and during a single scan. CrossRefGoogle Scholar
  17. 17.
    Pelletier-Galarneau M, Guehl N, Kim SJW, Osborne M, Radfar A, Normandin M, et al. Two-injection single-scan rest/stress imaging with 13N-ammonia: first human studies. J Nucl Med. 2018;59:1515.CrossRefGoogle Scholar
  18. 18.
    Gonzalez JA, Beller GA. Choosing exercise or pharmacologic stress imaging, or exercise ECG testing alone: how to decide. J Nucl Cardiol. 2017;24:555–7.CrossRefGoogle Scholar
  19. 19.
    Valenta I, Quercioli A, Vincenti G, Nkoulou R, Dewarrat S, Rager O, et al. Structural epicardial disease and microvascular function are determinants of an abnormal longitudinal myocardial blood flow difference in cardiovascular risk individuals as determined with PET/CT. J Nucl Cardiol. 2010;17:1023–33.CrossRefGoogle Scholar
  20. 20.
    Johnson NP, Gould KL. Integrating noninvasive absolute flow, coronary flow reserve, and ischemic thresholds into a comprehensive map of physiological severity. JACC Cardiovasc Imaging. 2012;5:430–40.CrossRefGoogle Scholar
  21. 21.
    Lortie M, Beanlands RSB, Yoshinaga K, Klein R, Dasilva JN, DeKemp RA. Quantification of myocardial blood flow with 82Rb dynamic PET imaging. Eur J Nucl Med Mol Imaging. 2007;34:1765–74.CrossRefGoogle Scholar
  22. 22.
    Prior JO, Schindler TH, Facta AD, Hernandez-Pampaloni M, Campisi R, Dahlbom M, et al. Determinants of myocardial blood flow response to cold pressor testing and pharmacologic vasodilation in healthy humans. Eur J Nucl Med Mol Imaging. 2007;34:20–7.CrossRefGoogle Scholar
  23. 23.
    Aquaro GD, Todiere G, Barison A, Strata E, Marzilli M, Pingitore A, et al. Myocardial blood flow and fibrosis in hypertrophic cardiomyopathy. J Card Fail. 2011;17:384–91.CrossRefGoogle Scholar
  24. 24.
    Czernin J, Müller P, Chan S, Brunken RC, Porenta G, Krivokapich J, et al. Influence of age and hemodynamics on myocardial blood flow and flow reserve. Circulation. 1993;88:62–9.CrossRefGoogle Scholar
  25. 25.
    Motivala AA, Rose PA, Kim HM, Smith YR, Bartnik C, Brook RD, et al. Cardiovascular risk, obesity, and myocardial blood flow in postmenopausal women. J Nucl Cardiol. 2008;15:510–7.CrossRefGoogle Scholar
  26. 26.
    Tawakol A, Sims K, MacRae C, Friedman JR, Alpert NM, Fischman AJ, et al. Myocardial flow regulation in people with mitochondrial myopathy, encephalopathy, lactic acidosis, stroke-like episodes/myoclonic epilepsy and ragged red fibers and other mitochondrial syndromes. Coron Artery Dis. 2003;14:197–205.PubMedGoogle Scholar
  27. 27.
    Ramanathan T, Skinner H. Coronary blood flow. Contin Educ Anaesth Crit Care Pain. 2005;5:61–4.CrossRefGoogle Scholar
  28. 28.
    • Gewirtz H. Coronary circulation: pressure/flow parameters for assessment of ischemic heart disease. J Nucl Cardiol. 2018.  https://doi.org/10.1007/s12350-018-1270-3. This paper is an elegant review of the physiological principles behind flow measurements with different modalities, allowing a better understanding of those parameters.
  29. 29.
    Pelletier-Galarneau M, deKemp RA, Hunter CRRN, Klein R, Klein M, Ironstone J, et al. Effects of hypercapnia on myocardial blood flow in healthy human subjects. J Nucl Med. 2018;59:100–6.CrossRefGoogle Scholar
  30. 30.
    Germino M, Ropchan J, Mulnix T, Fontaine K, Nabulsi N, Ackah E, et al. Quantification of myocardial blood flow with (82)Rb: validation with (15)O-water using time-of-flight and point-spread-function modeling. EJNMMI Res. 2016;6:68.CrossRefGoogle Scholar
  31. 31.
    Tadamura E, Iida H, Matsumoto K, Mamede M, Kubo S, Toyoda H, et al. Comparison of myocardial blood flow during dobutamine-atropine infusion with that after dipyridamole administration in normal men. J Am Coll Cardiol. 2001;37:130–6.CrossRefGoogle Scholar
  32. 32.
    Kofoed KF, Czernin J, Johnson J, Kobashigawa J, Phelps ME, Laks H, et al. Effects of cardiac allograft vasculopathy on myocardial blood flow, vasodilatory capacity, and coronary vasomotion. Circulation. 1997;95:600–6.CrossRefGoogle Scholar
  33. 33.
    Hajjiri MM, Leavitt MB, Zheng H, Spooner AE, Fischman AJ, Gewirtz H. Comparison of positron emission tomography measurement of adenosine-stimulated absolute myocardial blood flow versus relative myocardial tracer content for physiological assessment of coronary artery stenosis severity and location. JACC Cardiovasc Imaging. 2009;2:751–8.CrossRefGoogle Scholar
  34. 34.
    Fiechter M, Ghadri JR, Gebhard C, Fuchs TA, Pazhenkottil AP, Nkoulou RN, et al. Diagnostic value of 13N-ammonia myocardial perfusion PET: added value of myocardial flow reserve. J Nucl Med. 2012;53:1230–4.CrossRefGoogle Scholar
  35. 35.
    Muzik O, Duvernoy C, Beanlands RS, Sawada S, Dayanikli F, Wolfe ER, et al. Assessment of diagnostic performance of quantitative flow measurements in normal subjects and patients with angiographically documented coronary artery disease by means of nitrogen-13 ammonia and positron emission tomography. J Am Coll Cardiol. 1998;31:534–40.CrossRefGoogle Scholar
  36. 36.
    Ziadi MC, Dekemp RA, Williams K, Guo A, Renaud JM, Chow BJW, et al. Does quantification of myocardial flow reserve using rubidium-82 positron emission tomography facilitate detection of multivessel coronary artery disease? J Nucl Cardiol. 2012;19:670–80.CrossRefGoogle Scholar
  37. 37.
    Naya M, Murthy VL, Taqueti VR, Foster CR, Klein J, Garber M, et al. Preserved coronary flow reserve effectively excludes high-risk coronary artery disease on angiography. J Nucl Med. 2014;55:248–55.CrossRefGoogle Scholar
  38. 38.
    Danad I, Uusitalo V, Kero T, Saraste A, Raijmakers PG, Lammertsma AA, et al. Quantitative assessment of myocardial perfusion in the detection of significant coronary artery disease: cutoff values and diagnostic accuracy of quantitative [(15)O]H2O PET imaging. J Am Coll Cardiol. 2014;64:1464–75.CrossRefGoogle Scholar
  39. 39.
    Danad I, Raijmakers PG, Harms HJ, Heymans MW, van Royen N, Lubberink M, et al. Impact of anatomical and functional severity of coronary atherosclerotic plaques on the transmural perfusion gradient: a [15O]H2O PET study. Eur Heart J. 2014;35:2094–105.CrossRefGoogle Scholar
  40. 40.
    Joutsiniemi E, Saraste A, Pietilä M, Mäki M, Kajander S, Ukkonen H, et al. Absolute flow or myocardial flow reserve for the detection of significant coronary artery disease? Eur Heart J Cardiovasc Imaging. 2014;15:659–65.CrossRefGoogle Scholar
  41. 41.
    Lee JM, Kim CH, Koo B-K, Hwang D, Park J, Zhang J, et al. Integrated myocardial perfusion imaging diagnostics improve detection of functionally significant coronary artery stenosis by 13N-ammonia positron emission tomography. Circ Cardiovasc Imaging. 2016;9:e004768.Google Scholar
  42. 42.
    Williams MC, Mirsadraee S, Dweck MR, Weir NW, Fletcher A, Lucatelli C, et al. Computed tomography myocardial perfusion vs 15O-water positron emission tomography and fractional flow reserve. Eur Radiol. 2017;27:1114–24.CrossRefGoogle Scholar
  43. 43.
    Stuijfzand WJ, Uusitalo V, Kero T, Danad I, Rijnierse MT, Saraste A, et al. Relative flow reserve derived from quantitative perfusion imaging may not outperform stress myocardial blood flow for identification of hemodynamically significant coronary artery disease. Circ Cardiovasc Imaging. 2015;8:e002400.Google Scholar
  44. 44.
    Danad I, Raijmakers PG, Appelman YE, Harms HJ, de Haan S, van den Oever MLP, et al. Hybrid imaging using quantitative H215O PET and CT-based coronary angiography for the detection of coronary artery disease. J Nucl Med. 2013;54:55–63.CrossRefGoogle Scholar
  45. 45.
    Murthy VL, Naya M, Foster CR, Hainer J, Gaber M, Di Carli G, et al. Improved cardiac risk assessment with noninvasive measures of coronary flow reserve. Circulation. 2011;124:2215–24.CrossRefGoogle Scholar
  46. 46.
    Ziadi MC, Dekemp RA, Williams KA, Guo A, Chow BJW, Renaud JM, et al. Impaired myocardial flow reserve on rubidium-82 positron emission tomography imaging predicts adverse outcomes in patients assessed for myocardial ischemia. J Am Coll Cardiol. 2011;58:740–8.CrossRefGoogle Scholar
  47. 47.
    Johnson NP, Gould KL. Physiological basis for angina and ST-segment change PET-verified thresholds of quantitative stress myocardial perfusion and coronary flow reserve. JACC Cardiovasc Imaging. 2011;4:990–8.CrossRefGoogle Scholar
  48. 48.
    Tio RA, Dabeshlim A, Siebelink H-MJ, de Sutter J, Hillege HL, Zeebregts CJ, et al. Comparison between the prognostic value of left ventricular function and myocardial perfusion reserve in patients with ischemic heart disease. J Nucl Med. 2009;50:214–9.CrossRefGoogle Scholar
  49. 49.
    Slart RHJA, Zeebregts CJ, Hillege HL, de Sutter J, Dierckx RAJO, van Veldhuisen DJ, et al. Myocardial perfusion reserve after a PET-driven revascularization procedure: a strong prognostic factor. J Nucl Med. 2011;52:873–9.CrossRefGoogle Scholar
  50. 50.
    Herzog BA, Husmann L, Valenta I, Gaemperli O, Siegrist PT, Tay FM, et al. Long-term prognostic value of 13N-ammonia myocardial perfusion positron emission tomography added value of coronary flow reserve. J Am Coll Cardiol. 2009;54:150–6.CrossRefGoogle Scholar
  51. 51.
    Murthy VL, Naya M, Foster CR, Gaber M, Hainer J, Klein J, et al. Association between coronary vascular dysfunction and cardiac mortality in patients with and without diabetes mellitus. Circulation. 2012;126:1858–68.CrossRefGoogle Scholar
  52. 52.
    Murthy VL, Naya M, Foster CR, Hainer J, Gaber M, Dorbala S, et al. Coronary vascular dysfunction and prognosis in patients with chronic kidney disease. JACC Cardiovasc Imaging. 2012;5:1025–34.CrossRefGoogle Scholar
  53. 53.
    • Shah NR, Charytan DM, Murthy VL, Skali Lami H, Veeranna V, Cheezum MK, et al. Prognostic value of coronary flow reserve in patients with dialysis-dependent ESRD. J Am Soc Nephrol JASN. 2016;27:1823–9. This study shows the independent and incremental value of MFR for risk stratification of patients with end-stage renal disease. CrossRefGoogle Scholar
  54. 54.
    Dorbala S, Vangala D, Bruyere J, Quarta C, Kruger J, Padera R, et al. Coronary microvascular dysfunction is related to abnormalities in myocardial structure and function in cardiac amyloidosis. JACC Heart Fail. 2014;2:358–67.CrossRefGoogle Scholar
  55. 55.
    Kalliokoski RJ, Kalliokoski KK, Sundell J, Engblom E, Penttinen M, Kantola I, et al. Impaired myocardial perfusion reserve but preserved peripheral endothelial function in patients with Fabry disease. J Inherit Metab Dis. 2005;28:563–73.CrossRefGoogle Scholar
  56. 56.
    Neglia D, Michelassi C, Trivieri MG, Sambuceti G, Giorgetti A, Pratali L, et al. Prognostic role of myocardial blood flow impairment in idiopathic left ventricular dysfunction. Circulation. 2002;105:186–93.CrossRefGoogle Scholar
  57. 57.
    Sciagrà R, Calabretta R, Cipollini F, Passeri A, Castello A, Cecchi F, et al. Myocardial blood flow and left ventricular functional reserve in hypertrophic cardiomyopathy: a 13NH3 gated PET study. Eur J Nucl Med Mol Imaging. 2017;44:866–75.CrossRefGoogle Scholar
  58. 58.
    Majmudar MD, Murthy VL, Shah RV, Kolli S, Mousavi N, Foster CR, et al. Quantification of coronary flow reserve in patients with ischaemic and non-ischaemic cardiomyopathy and its association with clinical outcomes. Eur Heart J Cardiovasc Imaging. 2015;16:900–9.CrossRefGoogle Scholar
  59. 59.
    Kajander S, Joutsiniemi E, Saraste M, Pietilä M, Ukkonen H, Saraste A, et al. Cardiac positron emission tomography/computed tomography imaging accurately detects anatomically and functionally significant coronary artery disease. Circulation. 2010;122:603–13.CrossRefGoogle Scholar
  60. 60.
    Gewirtz H, Dilsizian V. Integration of quantitative positron emission tomography absolute myocardial blood flow measurements in the clinical management of coronary artery disease. Circulation. 2016;133:2180–96.CrossRefGoogle Scholar
  61. 61.
    Juneau D, Erthal F, Ohira H, Mc Ardle B, Hessian R, Beanlands RS, et al. Clinical PET myocardial perfusion imaging and flow quantification. Cardiol Clin. 2016;34:69–85.CrossRefGoogle Scholar
  62. 62.
    Juneau D, deKemp RA, Beanlands RSB. Reporting myocardial flow reserve with PET. Ready or not, here it is! But walk before you fly! J Nucl Cardiol. 2018;25:164–8.CrossRefGoogle Scholar
  63. 63.
    Xaplanteris P, Fournier S, Pijls NHJ, Fearon WF, Barbato E, Tonino PAL, et al. Five-year outcomes with PCI guided by fractional flow reserve. N Engl J Med. 2018;379:250–9.CrossRefGoogle Scholar
  64. 64.
    De Bruyne B, Pijls NHJ, Kalesan B, Barbato E, Tonino PAL, Piroth Z, et al. Fractional flow reserve-guided PCI versus medical therapy in stable coronary disease. N Engl J Med. 2012;367:991–1001.CrossRefGoogle Scholar
  65. 65.
    De Bruyne B, Fearon WF, Pijls NHJ, Barbato E, Tonino P, Piroth Z, et al. Fractional flow reserve-guided PCI for stable coronary artery disease. N Engl J Med. 2014;371:1208–17.CrossRefGoogle Scholar
  66. 66.
    Johnson NP, Kirkeeide RL, Gould KL. Is discordance of coronary flow reserve and fractional flow reserve due to methodology or clinically relevant coronary pathophysiology? JACC Cardiovasc Imaging. 2012;5:193–202.CrossRefGoogle Scholar
  67. 67.
    Meimoun P, Sayah S, Luycx-Bore A, Boulanger J, Elmkies F, Benali T, et al. Comparison between non-invasive coronary flow reserve and fractional flow reserve to assess the functional significance of left anterior descending artery stenosis of intermediate severity. J Am Soc Echocardiogr. 2011;24:374–81.CrossRefGoogle Scholar
  68. 68.
    Lund LH, Edwards LB, Dipchand AI, Goldfarb S, Kucheryavaya AY, Levvey BJ, et al. The registry of the International Society for Heart and Lung Transplantation: thirty-third adult heart transplantation report-2016; focus theme: primary diagnostic indications for transplant. J Heart Lung Transplant. 2016;35:1158–69.CrossRefGoogle Scholar
  69. 69.
    Ramzy D, Rao V, Brahm J, Miriuka S, et al. Cardiac allograft vasculopathy: a review. Can J Surg. 2005;48:319.PubMedPubMedCentralGoogle Scholar
  70. 70.
    Thompson D, Koster MJ, Wagner RH, Heroux A, Barron JT. Single photon emission computed tomography myocardial perfusion imaging to detect cardiac allograft vasculopathy. Eur Heart J Cardiovasc Imaging. 2012;13:271–5.CrossRefGoogle Scholar
  71. 71.
    Manrique A, Bernard M, Hitzel A, Bubenheim M, Tron C, Agostini D, et al. Diagnostic and prognostic value of myocardial perfusion gated SPECT in orthotopic heart transplant recipients. J Nucl Cardiol. 2010;17:197–206.CrossRefGoogle Scholar
  72. 72.
    Wu Y-W, Chen Y-H, Wang S-S, Jui H-Y, Yen R-F, Tzen K-Y, et al. PET assessment of myocardial perfusion reserve inversely correlates with intravascular ultrasound findings in angiographically normal cardiac transplant recipients. J Nucl Med. 2010;51:906–12.CrossRefGoogle Scholar
  73. 73.
    Allen-Auerbach M, Schöder H, Johnson J, Kofoed K, Einhorn K, Phelps ME, et al. Relationship between coronary function by positron emission tomography and temporal changes in morphology by intravascular ultrasound (IVUS) in transplant recipients. J Heart Lung Transplant. 1999;18:211–9.CrossRefGoogle Scholar
  74. 74.
    Mc Ardle BA, Davies RA, Chen L, Small GR, Ruddy TDR, Dwivedi G, et al. The prognostic value of Rb-82 positron emission tomography in patients following heart transplant. Circ Cardiovasc Imaging. 2014;7:930–7.Google Scholar
  75. 75.
    •• Chih S, Chong AY, Erthal F, de Kemp RA, Davies RA, Stadnick E, et al. PET assessment of epicardial intimal disease and microvascular dysfunction in cardiac allograft vasculopathy. J Am Coll Cardiol. 2018;71:1444–56. This recent prospective study showed that flow quantification with PET can diagnose CAV with high accuracy. The authors also proposed an investigation algorithm which uses PET flow quantification as a potential tool for noninvasive screening of CAV. CrossRefGoogle Scholar
  76. 76.
    Kushwaha SS, Narula J, Narula N, Zervos G, Semigran MJ, Fischman AJ, et al. Pattern of changes over time in myocardial blood flow and microvascular dilator capacity in patients with normally functioning cardiac allografts. Am J Cardiol. 1998;82:1377–81.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Matthieu Pelletier-Galarneau
    • 1
    • 2
  • Patrick Martineau
    • 1
    • 3
  • Georges El Fakhri
    • 1
    Email author
  1. 1.Gordon Center for Medical ImagingMassachusetts General Hospital and Harvard Medical SchoolBostonUSA
  2. 2.Department of Medical ImagingMontreal Heart InstituteMontrealCanada
  3. 3.Department of Radiology, Health Sciences CentreUniversity of ManitobaWinnipegCanada

Personalised recommendations