Skip to main content
SpringerLink
Log in

Coronary Physiology and Quantitative Myocardial Perfusion

  • Chapter
  • First Online:
Atlas of Nuclear Cardiology

Abstract

Quantitative myocardial perfusion by positron emission tomography (PET) is the optimal guide for diagnosis and management or interventions for obstructive or non-obstructive coronary artery disease (CAD) for the following reasons documented in this chapter: PET guided elective revascularization in chronic CAD reduces death and myocardial infarction (MI) by 54% compared to medical treatment alone whereas FFR or FFRct or angiogram guided interventions show no reduced death or MI compared to medical treatment. In a large cohort with high prevalence of CAD, PET excludes 60–80% of elective coronary angiograms as unnecessary for mild or moderate, low risk CAD not needing angiogram versus identifying patients with CAD severity getting PCI or CABG in 78% of PET guided angiograms. By comparison, for FFRct ≤0.8, only 38% have pressure derived FFR ≤0.8 at angiogram, hence FFRct is false + in 62% of + FFRct cases. On head to head comparison with analysis for intent to diagnose, PET is superior to FFRct on a per patient and per artery analysis due FFRct variability of ±25% for predicting FFR ≤0.8 and due to 17% FFRct failures of acquiring useable data versus 0.7% failed data acquisition for PET that has ±10% variability. In addition to this data, PET quantitative perfusion is the accepted Gold Standard of physiologic CAD severity since: (i) PET is the reference standard to which FFR was compared for validation and for the extensive PET literature since validating FFR. (ii) Quantitative myocardial perfusion explains symptoms and abnormal physiologic function broadly in all coronary pathophysiologies to guide management. (iii) Quantitative myocardial perfusion by PET has mainstream status in cardiology texts including Hurst’s The Heart and The Atlas of Nuclear Cardiology (in press).

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 299.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 379.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 379.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Gould KL, Lipscomb K, Hamilton GW. Physiologic basis for assessing critical coronary stenosis. Instantaneous flow response and regional distribution during coronary hyperemia as measures of coronary flow reserve. Am J Cardiol. 1974;33:87–94.

    Article  CAS  PubMed  Google Scholar 

  2. Gould KL, Gewirtz H, Narula J. Coronary blood flow and myocardial ischemia. In: Fuster V, Harrington RA, Narula J, Eapen ZJ, editors. Hurst’s the heart. 14th ed. New York: McGraw Hill; 2017. p. 893–922.

    Google Scholar 

  3. Gould KL, Hamilton GW, Lipscomb K, Kennedy JW. A method for assessing stress induced regional malperfusion during coronary arteriography: experimental validation and clinical application. Am J Cardiol. 1974;34:557–64.

    Article  CAS  PubMed  Google Scholar 

  4. Gould KL. Noninvasive assessment of coronary stenoses by myocardial perfusion imaging during pharmacologic coronary vasodilatation. I. Physiologic basis and experimental validation. Am J Cardiol. 1978;41:267–78.

    Article  CAS  PubMed  Google Scholar 

  5. Gould KL, Westcott JR, Albro PC, Hamilton GW. Noninvasive assessment of coronary stenoses by myocardial imaging during coronary vasodilatation. II. Clinical methodology and feasibility. Am J Cardiol. 1978;41:279–87.

    Article  CAS  PubMed  Google Scholar 

  6. Albro PC, Gould KL, Westcott RJ, Hamilton GW, Ritchie JL, Williams DL. Noninvasive assessment of coronary stenoses by myocardial imaging during pharmacologic coronary vasodilatation. III. Clinical trial. Am J Cardiol. 1978;42:751–60.

    Article  CAS  PubMed  Google Scholar 

  7. Gould KL. Assessment of coronary stenoses by myocardial perfusion imaging during pharmacologic coronary vasodilatation. IV. Limits of stenosis detection by idealized, experimental, cross-sectional myocardial imaging. Am J Cardiol. 1978;42:761–8.

    Article  CAS  PubMed  Google Scholar 

  8. Gould KL, Schelbert HR, Phelps ME, Hoffman EJ. Noninvasive assessment of coronary stenoses with myocardial perfusion imaging during pharmacologic coronary vasodilatation. V. Detection of 47 percent diameter coronary stenosis with intravenous nitrogen-13 ammonia and emission-computed tomography in intact dogs. Am J Cardiol. 1979;43:200–8. Awarded the George von Hevesy Prize for Research in Nuclear Medicine, at the World Federation of Nuclear Medicine, September 17, 1978, Washington, DC.

    Article  CAS  PubMed  Google Scholar 

  9. Schelbert HR, Wisenberg G, Phelps ME, Gould KL, Eberhard H, Hoffman EJ, et al. Noninvasive assessment of coronary stenosis by myocardial imaging during pharmacologic coronary vasodilation. VI. Detection of coronary artery disease in man with intravenous N-13 ammonia and positron computed tomography. Am J Cardiol. 1982;49:1197–207.

    Article  CAS  PubMed  Google Scholar 

  10. Kirkeeide R, Gould KL, Parsel L. Assessment of coronary stenoses by myocardial imaging during coronary vasodilation. VII. Validation of coronary flow reserve as a single integrated measure of stenosis severity accounting for all its geometric dimensions. J Am Coll Cardiol. 1986;7:103–13.

    Article  CAS  PubMed  Google Scholar 

  11. Gould KL, Goldstein RA, Mullani N, Kirkeeide R, Wong G, Smalling R, et al. Noninvasive assessment of coronary stenoses by myocardial imaging during pharmacologic coronary vasodilation. VIII. Feasibility of 3D cardiac positron imaging without a cyclotron using generator produced Rb-82. J Am Coll Cardiol. 1986;7:775–92.

    Article  CAS  PubMed  Google Scholar 

  12. Gould KL, Kirkeeide R, Johnson NP. Coronary branch steal – experimental validation and clinical implications of interacting stenosis in branching coronary arteries. Circ Cardiovasc Imaging. 2010;3:701–9.

    Google Scholar 

  13. Gould KL, Nakagawa Y, Nakagawa N, Sdringola S, Hess MJ, Haynie M, et al. Frequency and clinical implications of fluid dynamically significant diffuse coronary artery disease manifest as graded, longitudinal, base to apex, myocardial perfusion abnormalities by non-invasive positron emission tomography. Circulation. 2000;101:1931–9.

    Article  CAS  PubMed  Google Scholar 

  14. Gould KL. Coronary artery stenosis and reversing atherosclerosis. 2nd ed. London: Arnold Publishers; 1999. A textbook of coronary pathophysiology, quantitative coronary arteriography, and cardiac PET.

    Google Scholar 

  15. De Bruyne B, Hersbach F, Pijls NH, Bartunek J, Bech JW, Heyndrickx GR, et al. Abnormal epicardial coronary resistance in patients with diffuse atherosclerosis but “Normal” coronary angiography. Circulation. 2001;104:2401–6.

    Article  PubMed  Google Scholar 

  16. Johnson NP, Kirkeeide RL, Gould KL. Is discordance of coronary flow reserve and fractional flow reserve due to methodology or clinically relevant coronary pathophysiology? Supplement JACC Cardiovasc Imaging. 2012;5:193–202.

    Article  Google Scholar 

  17. Lipscomb K, Gould KL. Mechanism of the effect of coronary artery stenosis on coronary flow in the dog. Am Heart J. 1975;89:60–7.

    Article  CAS  PubMed  Google Scholar 

  18. Gould KL, Kirkeeide RL, Buchi M. Coronary flow reserve as a physiologic measure of stenosis severity. Part I. Relative and absolute coronary flow reserve during changing aortic pressure and cardiac workload. Part II. Determination from arteriographic stenosis dimensions under standardized conditions. J Am Coll Cardiol. 1990;15:459–74.

    Article  CAS  PubMed  Google Scholar 

  19. Pijls NHJ, van Son JAM, Kirkeeide RL, Bruyne BD, Gould KL. Experimental basis of determining maximal coronary myocardial and collateral blood flow by pressure measurements for assessing functional stenosis severity before and after PTCA. Circulation. 1993;86:1354–67.

    Article  Google Scholar 

  20. Smalling RW, Kelley K, Kirkeeide RL, Fisher DJ. Regional myocardial function is not affected by severe coronary depressurization provided coronary blood flow is maintained. J Am Coll Cardiol. 1985;5:948–55.

    Article  CAS  PubMed  Google Scholar 

  21. Seiler C. Collateral circulation of the heart. Dordrecht: Springer; 2009.

    Book  Google Scholar 

  22. Gould KL, Kelley KO, Bolson EL. Experimental validation of quantitative coronary arteriography for determining pressure-flow characteristics of coronary stenoses. Circulation. 1982;66:930–7.

    Article  CAS  PubMed  Google Scholar 

  23. Gould KL, Kelley KO. Physiological significance of coronary flow velocity and changing stenosis geometry during coronary vasodilation in awake dogs. Circ Res. 1982;50:695–704.

    Article  CAS  PubMed  Google Scholar 

  24. Hoffman JIE, Buckberg GD. The myocardial oxygen supply:demand index revisited. J Am Heart Assoc. 2014;3:e000285. https://doi.org/10.1161/JAHA.113.000285285.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Gould KL, Johnson NP. Coronary physiology: beyond CFR in microvascular angina. J Am Coll Cardiol. 2018;72:2642–62.

    Article  PubMed  Google Scholar 

  26. 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.

    Article  PubMed  Google Scholar 

  27. Gould KL, Johnson NP, Bateman TM, Beanlands RS, Bengel FM, Bober R, et al. Anatomic versus physiologic assessment of coronary artery disease: role of CFR, FFR, and PET imaging in revascularization decision-making. J Am Coll Cardiol. 2013;62:1639–53.

    Article  PubMed  Google Scholar 

  28. Gupta A, Taqueti VR, van de Hoef TP, Bajaj NS, Bravo PE, Murthy VL, et al. Integrated noninvasive physiological assessment of coronary circulatory function and impact on cardiovascular mortality in patients with stable coronary artery disease. Circulation. 2017;136:2325–36.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Danad I, Raijmakers PG, Appelman YE, Harms HJ, de Haan S, van den Oever ML, 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.

    Article  CAS  PubMed  Google Scholar 

  30. 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.

    Article  PubMed  Google Scholar 

  31. Driessen RS, Danad I, Stuijfzand WJ, Raijmakers PG, Schumacher SP, van Diemen PA, et al. Comparison of coronary computed tomography angiography, fractional flow reserve, and perfusion imaging for ischemia diagnosis. J Am Coll Cardiol. 2019;73:161–73.

    Article  PubMed  Google Scholar 

  32. Danad I, Raijmakers PG, Driessen RS, Leipsic J, Raju R, Naoum C, et al. Comparison of coronary CT angiography, SPECT, PET, and hybrid imaging for diagnosis of ischemic heart disease determined by fractional flow reserve. JAMA Cardiol. 2017;2:1100–7.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Maaniitty T, Stenström I, Bax JJ, Uusitalo V, Ukkonen H, Kajander S, et al. Prognostic value of coronary CT angiography with selective PET perfusion imaging in coronary artery disease. JACC Cardiovasc Imaging. 2017;10:1361–70.

    Article  PubMed  Google Scholar 

  34. Knuuti J, Ballo H, Juarez-Orozco LE, Saraste A, Kolh P, Rutjes AW, et al. The performance of non-invasive tests to rule-in and rule-out significant coronary artery stenosis in patients with stable angina: a meta-analysis focused on post-test disease probability. Eur Heart J. 2018;39:3322–30.

    Article  PubMed  Google Scholar 

  35. Koo BK, Erglis A, Doh JH, Daniels DV, Jegere S, Kim HS, et al. Diagnosis of ischemia-causing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms. Results from the prospective multicenter DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained Via Noninvasive Fractional Flow Reserve) study. J Am Coll Cardiol. 2011;58:1989–97.

    Article  PubMed  Google Scholar 

  36. Tu S, Barbato E, Koszegi Z, Yang J, Sun Z, Holm N, et al. Fractional flow reserve calculation from 3-dimensional quantitative coronary angiography and TIMI frame count. JACC Cardiovasc Interv. 2014;7:768–77.

    Article  PubMed  Google Scholar 

  37. Murthy VL, Naya M, Taqueti VR, Foster CR, Gaber M, Hainer J, et al. Effects of sex on coronary microvascular dysfunction and cardiac outcomes. Circulation. 2014;129:2518–27.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Stenström I, Maaniitty T, Uusitalo V, Pietilä M, Ukkonen H, Kajander S, et al. Frequency and angiographic characteristics of coronary microvascular dysfunction in stable angina: a hybrid imaging study. Eur Heart J Cardiovasc Imaging. 2017;18:1206–13.

    Article  PubMed  Google Scholar 

  39. Gould KL, Johnson NP, Roby AE, Nguyen T, Kirkeeide R, Haynie M, et al. Regional artery specific thresholds of quantitative myocardial perfusion by PET associated with reduced MI and death after revascularization in stable coronary artery disease. J Nucl Med. 2019;60:410–7.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Gould KL. Does coronary flow trump coronary anatomy? JACC Cardiovasc Imaging. 2009;2:1009–23.

    Article  PubMed  Google Scholar 

  41. Sdringola S, Johnson NP, Kirkeeide RL, Cid E, Gould KL. Impact of unexpected factors on quantitative myocardial perfusion and coronary flow reserve in young, asymptomatic volunteers. JACC Cardiovasc Imaging. 2011;4:402–12.

    Article  PubMed  Google Scholar 

  42. Johnson NP, Gould KL. Physiologic basis for angina and ST change: PET-verified thresholds of quantitative stress myocardial perfusion and coronary flow reserve. JACC Cardiovasc Imaging. 2011;4:990–8. Awarded the 2011 Young Author Achievement Award by the Journal of the American College of Cardiology Cardiovascular Imaging.

    Article  PubMed  Google Scholar 

  43. Johnson NP, Gould KL. Integrating noninvasive absolute flow, coronary flow reserve, and ischemic thresholds into a comprehensive map of physiologic severity. JACC Cardiovasc Imaging. 2012;5:430–40.

    Article  PubMed  Google Scholar 

  44. Johnson NP, Pijls NH, De Bruyne B, Bech GJ, Kirkeeide RL, Gould KL. A black and white response to the “gray zone” for fractional flow reserve measurements. JACC Cardiovasc Interv. 2014;7:227–8.

    Article  PubMed  Google Scholar 

  45. Johnson NP, Gould KL. Regadenoson versus dipyridamole hyperemia for cardiac PET imaging. JACC Cardiovasc Imaging. 2015;8:438–47.

    Article  PubMed  Google Scholar 

  46. Johnson NP, Gould KL, Di Carli MF, Taqueti VR. Invasive FFR and noninvasive CFR in the evaluation of ischemia: what is the future? J Am Coll Cardiol. 2016;67:2772–88.

    Article  PubMed  Google Scholar 

  47. Kitkungvan D, Johnson NP, Roby AE, Patel MB, Kirkeeide R, Gould KL. Routine clinical quantitative rest stress myocardial perfusion for managing coronary artery disease: clinical relevance of test-retest variability. JACC Cardiovasc Imaging. 2017;10:565–77.

    Article  PubMed  Google Scholar 

  48. Kitkungvan D, Lai D, Zhu H, Roby AE, Johnson NP, Steptoe DD, et al. Optimal adenosine stress for maximum stress perfusion, coronary flow reserve, and pixel distribution of coronary flow capacity by Kolmogorov-Smirnov analysis. Circ Cardiovasc Imaging. 2017;10. pii:e005650. https://doi.org/10.1161/CIRCIMAGING.116.005650.

  49. Gould KL, Schelbert H, Narula J. Positron emission tomography in heart disease. In: Fuster V, Harrington RA, Narula J, Eapen ZJ, editors. Hurst’s the heart. 14th ed. New York: McGraw Hill; 2017. p. 553–605.

    Google Scholar 

  50. Javadi MS, Lautamäki R, Merrill J, Voicu C, Epley W, McBride G, Bengel FM. Definition of vascular territories on myocardial perfusion images by integration with true coronary anatomy: a hybrid PET/CT analysis. J Nucl Med. 2010;51:198–203.

    Article  PubMed  Google Scholar 

  51. Bom MJ, Schumacher SP, Driessen RS, Raijmakers PG, Everaars H, van Diemen PA, et al. Impact of individualized segmentation on diagnostic performance of quantitative positron emission tomography for haemodynamically significant coronary artery disease. Eur Heart J Cardiovasc Imaging. 2019;20:525–32. https://doi.org/10.1093/ehjci/jey201.

    Article  PubMed  Google Scholar 

  52. Ortiz-Perez JT, Rodriguez J, Meyers SN, Lee DC, Davidson C, Wu E. Correspondence between the 17-segment model and coronary arterial anatomy using contrast-enhanced cardiac magnetic resonance imaging. JACC Cardiovasc Imaging. 2008;1:282–93.

    Article  PubMed  Google Scholar 

  53. Pereztol-Valdés O, Candell-Riera J, Santana-Boado C, Angel J, Aguadé-Bruix S, Castell-Conesa J, et al. Correspondence between left ventricular 17 myocardial segments and coronary arteries. Eur Heart J. 2005;26:2637–43.

    Article  PubMed  Google Scholar 

  54. Thomassen A, Petersen H, Johansen A, Braad PE, Diederichsen AC, Mickley H, et al. Quantitative myocardial perfusion by O-15-water PET: individualized vs. standardized vascular territories. Eur Heart J Cardiovasc Imaging. 2015;16:970–6.

    PubMed  Google Scholar 

  55. Donato P, Coelho P, Santos C, Bernardes A, Caseiro-Alves F. Correspondence between left ventricular 17 myocardial segments and coronary anatomy obtained by multi-detector computed tomography: an ex vivo contribution. Surg Radiol Anat. 2012;34:805–10.

    Article  PubMed  Google Scholar 

  56. Cerci RJ, Arbab-Zadeh A, George RT, Miller JM, Vavere AL, Mehra V, et al. Aligning coronary anatomy and myocardial perfusion territories: an algorithm for the CORE320 multicenter study. Circ Cardiovasc Imaging. 2012;5:587–95.

    Article  PubMed  Google Scholar 

  57. Yoshida K, Mullani N, Gould KL. Coronary flow and flow reserve by positron emission tomography simplified for clinical application using Rb-82 or N-13 ammonia. J Nucl Med. 1996;37:1701–12.

    CAS  PubMed  Google Scholar 

  58. Vasquez AF, Johnson NP, Gould KL. Variation in quantitative myocardial perfusion due to arterial input selection. JACC Cardiovasc Imaging. 2013;6:559–68.

    Article  PubMed  Google Scholar 

  59. Bachrach SL, Carson RE. In hot blood—quantifying the arterial input. JACC Cardiovasc Imaging. 2013;6:569–73.

    Article  Google Scholar 

  60. Renaud JM, DaSilva JN, Beanlands RS, DeKemp RA. Characterizing the normal range of myocardial blood flow with 82rubidium and 13N-ammonia PET imaging. J Nucl Cardiol. 2013;20:578–91.

    Article  PubMed  Google Scholar 

  61. Araujo L, Lammertsma AA, Rhodes CG, McFalls EO, Iida H, Rechavia E, et al. Noninvasive quantification of regional myocardial blood flow in coronary artery disease with oxygen-15-labeled carbon dioxide inhalation and positron emission tomography. Circulation. 1991;83:875–85.

    Article  CAS  PubMed  Google Scholar 

  62. Bol A, Melin JA, Vanoverschelde JL, Baudhuin T, Vogelaers D, De Pauw M, et al. Direct comparison of [13N]ammonia and [15O]water estimates of perfusion with quantification of regional myocardial blood flow by microspheres. Circulation. 1993;87:512–25.

    Article  CAS  PubMed  Google Scholar 

  63. Johnson NP, Gould KL. Partial volume correction incorporating Rb-82 positron range for quantitative myocardial perfusion PET based on systolic-diastolic activity ratios and phantom measurements. J Nucl Cardiol. 2011;18:247–58.

    Article  PubMed  Google Scholar 

  64. Gould KL, Pan T, Loghin C, Johnson N, Guha A, Sdringola S. Frequent diagnostic errors in cardiac PET-CT due to misregistration of CT attenuation and emission PET images: a definitive analysis of causes, consequences and corrections. J Nucl Med. 2007;48:1112–21.

    Article  PubMed  Google Scholar 

  65. Loghin C, Sdringola S, Gould KL. Common artifacts in PET myocardial perfusion images due to attenuation-emission misregistration. J Nucl Med. 2004;45:1029–39.

    PubMed  Google Scholar 

  66. Johnson NP, Pan T, Gould KL. Shifted helical computed tomography to optimize cardiac positron emission tomography–computed tomography coregistration: quantitative improvement and limitations. Mol Imaging. 2010;9:256–67.

    Article  PubMed  Google Scholar 

  67. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  68. 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.

    Article  PubMed  Google Scholar 

  69. Taqueti VR, Hachamovitch R, Murthy VL, Naya M, Foster CR, Hainer J, et al. Global coronary flow reserve is associated with adverse cardiovascular events independently of luminal angiographic severity and modifies the effect of early revascularization. Circulation. 2015;131:19–27.

    Article  PubMed  Google Scholar 

  70. van de Hoef TP, Echavarría-Pinto M, van Lavieren MA, Meuwissen M, Serruys PW, Tijssen JG, et al. Diagnostic and prognostic implications of coronary flow capacity: a comprehensive cross-modality physiological concept in ischemic heart disease. JACC Cardiovasc Interv. 2015;8:1670–80.

    Article  PubMed  Google Scholar 

  71. van de Hoef TP, van Lavieren MA, Damman P, Delewi R, Piek MA, Chamuleau SA, et al. Physiological basis and long-term clinical outcome of discordance between fractional flow reserve and coronary flow velocity reserve in coronary stenoses of intermediate severity. Circ Cardiovasc Interv. 2014;7:301–11.

    Article  PubMed  Google Scholar 

  72. Hamaya R, Yonetsu T, Kanaji Y, Usui E, Hoshino M, Yamaguchi M, et al. Diagnostic and prognostic efficacy of coronary flow capacity obtained using pressure-temperature sensor-tipped wire–derived physiological indices. JACC Cardiovasc Interv. 2018;11:728–37.

    Article  PubMed  Google Scholar 

  73. Hoshino M, Kanaji Y, Hamaya R, Kanno Y, Hada M, Yamaguchi M, et al. Prognostic value of thermodilution-derived coronary flow capacity in patients with deferred revascularization. EuroIntervention. 2019. pii: EIJ-D-19-00029. https://doi.org/10.4244/EIJ-D-19-00029. [Epub ahead of print].

  74. 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. pii: e002400. https://doi.org/10.1161/CIRCIMAGING.114.002400.

  75. Virmani R. Are our tools for the identification of TCFA ready and do we know them? JACC Cardiovasc Imaging. 2011;4:656–8.

    Article  PubMed  Google Scholar 

  76. Tian J, Ren X, Vergallo R, Xing L, Yu H, Jia H, et al. Distinct morphological features of ruptured culprit plaque for acute coronary events compared to those with silent rupture and thin-cap fibroatheroma: a combined optical coherence tomography and intravascular ultrasound study. J Am Coll Cardiol. 2014;63:2209–16.

    Article  PubMed  Google Scholar 

  77. Arbab-Zadeh A, Fuster V. The myth of the “vulnerable plaque”: transitioning from a focus on individual lesions to atherosclerotic disease burden for coronary artery disease risk assessment. J Am Coll Cardiol. 2015;65:846–55.

    Article  PubMed  PubMed Central  Google Scholar 

  78. Bom MJ, Schumacher SP, Driessen RS, Raijmakers PG, Everaars H, van Diemen PA, et al. Impact of individualized segmentation on diagnostic performance of quantitative positron emission tomography for haemodynamically significant coronary artery disease. Eur Heart J Cardiovasc Imaging. 2019;20:21–30.

    Article  PubMed  Google Scholar 

  79. De Bruyne B, Baudhuin T, Melin JA, Pijls NH, Sys SU, Bol A, et al. Coronary flow reserve calculated from pressure measurements in humans. Validation with positron emission tomography. Circulation. 1994;89:1013–22.

    Article  PubMed  Google Scholar 

  80. Marques KM, Knaapen P, Boellaard R, Lammertsma AA, Westerhof N, Visser FC. Microvascular function in viable myocardium after chronic infarction does not influence fractional flow reserve measurements. J Nucl Med. 2007;48:1987–92.

    Article  PubMed  Google Scholar 

  81. deKemp RA, Yoshinaga K, Beanlands RSB. Will 3-dimensional PET-CT enable the routine quantification of myocardial blood flow? J Nucl Cardiol. 2007;14:380–97.

    Article  PubMed  Google Scholar 

  82. Gould KL, Martucci JP, Goldberg DI, Hess MJ, Edens RP, Latifi R, Dudrick SJ. Short-term cholesterol lowering decreases size and severity of perfusion abnormalities by positron emission tomography after dipyridamole in patients with coronary artery disease. Circulation. 1994;89:1530–8.

    Article  CAS  PubMed  Google Scholar 

  83. Gould KL, Ornish D, Scherwitz L, Brown S, Edens RP, Hess MJ, et al. Changes in myocardial perfusion abnormalities by positron emission tomography after long-term, intense risk factor modification. JAMA. 1995;274:894–901.

    Article  CAS  PubMed  Google Scholar 

  84. Sdringola S, Nakagawa K, Nakagawa Y, Yusuf W, Mullani N, Haynie M, et al. Combined intense lifestyle and pharmacologic lipid treatment further reduce coronary events and myocardial perfusion abnormalities compared to usual care cholesterol lowering drugs in coronary artery disease. J Am Coll Cardiol. 2003;41:262–72. Chosen for Highlights of the Year in J Am Coll Cardiol. 2003 (JACC 2003;42:2164).

    Google Scholar 

  85. Sdringola S, Boccalandro F, Loghin C, Gould KL. Mechanisms of progression and regression of coronary artery disease by PET related to treatment intensity and clinical events at long-term follow-up. J Nucl Med. 2006;47:59–67.

    PubMed  Google Scholar 

  86. Gould KL. From experimental to clinical coronary physiology. Circ Res. 2018;123:1124–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Financial Support and Relationships with Industry

Research supported by internal funds of the Weatherhead PET Center.

NPJ received institutional licensing and consulting agreement with Boston Scientific for the smart minimum FFR algorithm; received significant institutional research support from St. Jude Medical (CONTRAST, NCT02184117) and Philips Volcano Corporation (DEFINE-FLOW, NCT02328820) for studies using intracoronary pressure and flow sensors; and has a patent pending on diagnostic methods for quantifying aortic stenosis and TAVI physiology.

KLG receives internal funding from the Weatherhead PET Center for Preventing and Reversing Atherosclerosis and is the 510(k) applicant for FDA approved HeartSee K171303 PET software. To avoid any conflict of interest, KLG has assigned any royalties to the University of Texas for research or student scholarships; has no consulting, speakers, or board agreements; and receives no funding from PET-related or other corporate entities.

Author information

Authors and Affiliations

  1. Weatherhead PET Center for Preventing and Reversing Atherosclerosis, University of Texas Medical School at Houston, Houston, TX, USA

    K. Lance Gould

  2. Division of Cardiology, University of Texas Medical School at Houston, Houston, TX, USA

    Tung T. Nguyen & Nils P. Johnson

  3. Department of Internal Medicine, McGovern Medical School, University of Texas Health Sciences Center at Houston, Houston, TX, USA

    Richard Kirkeeide

Authors
  1. K. Lance Gould
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tung T. Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Richard Kirkeeide
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nils P. Johnson
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to K. Lance Gould .

Editor information

Editors and Affiliations

  1. University of Maryland School of Medicine, Baltimore, MD, USA

    Vasken Dilsizian

  2. Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Jagat Narula

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Gould, K.L., Nguyen, T.T., Kirkeeide, R., Johnson, N.P. (2021). Coronary Physiology and Quantitative Myocardial Perfusion. In: Dilsizian, V., Narula, J. (eds) Atlas of Nuclear Cardiology. Springer, Cham. https://doi.org/10.1007/978-3-030-49885-6_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-49885-6_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-49884-9

  • Online ISBN: 978-3-030-49885-6

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics

Search

Navigation