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Quantitative PET/CT Measures of Myocardial Flow Reserve and Atherosclerosis for Cardiac Risk Assessment and Predicting Adverse Patient Outcomes

  • Nuclear Cardiology (V Dilsizian, Section Editor)
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Abstract

Conventional scintigraphic myocardial perfusion imaging with SPECT/CT or with PET/CT has evolved as an important clinical tool for the diagnostic assessment of flow-limiting epicardial lesions and risk stratification of patients with suspected CAD. By determining the relative distribution of radiotracer-uptake in the left-ventricular (LV) myocardium during stress, the presence of flow-limiting CAD lesions can be identified. While this approach successfully identifies epicardial coronary artery lesions, the presence of subclinical and non-obstructive CAD may go undetected. In this direction, the concurrent ability of PET/CT to assess absolute myocardial blood flow (MBF) in ml/g/min, rather that relative regional distribution of radiotracer-uptake, and myocardial flow reserve (MFR), expands the scope of conventional myocardial perfusion imaging from the identification of more advanced and flow-limiting epicardial lesions to (1) subclinical CAD, (2) an improved characterization of the extent and severity of CAD burden, and (3) the discovery of “balanced” reduction in myocardial blood flow as a consequence of 3 vessel CAD. Concurrent to the PET data, the CT component of the hybrid PET/CT allows the assessment of coronary artery calcification as an indirect surrogate for CAD burden, without contrast, or with contrast angiography to directly denote coronary stenosis and/or plaque morphology with CT. Hybrid PET/CT system, therefore, has the potential to not only identify and characterize flow-limiting epicardial lesions but also subclinical stages of functional and/or structural stages of CAD. Whether the application of PET/CT for an optimal assessment of coronary pathology, its downstream effects on myocardial perfusion, and coronary circulatory function will in effect lead to changes in clinical decision-making process, investiture in preventive health care, and improved long-term outcome, awaits scientific verification.

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References

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

  1. Leber AW, Knez A, von Ziegler F, Becker A, Nikolaou K, Wintersberger B, et al. Quantification of obstructive and nonobstructive coronary lesions by 64-slice computed tomography: a comparative study with quantitative coronary angiography and intravascular ultrasound. J Am Coll Cardiol. 2005;46:147–54.

    Article  PubMed  Google Scholar 

  2. Gould KL. Quantification of coronary artery stenosis in vivo. Circ Res. 1985;57:341–53.

    Article  PubMed  CAS  Google Scholar 

  3. Gould KL, Lipscomb K, Calvert C. Compensatory changes of the distal coronary vascular bed during progressive coronary constriction. Circulation. 1975;51:1085–94.

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  5. Uren NG, Melin JA, De Bruyne B, Wijns W, Baudhuin T, Camici PG. Relation between myocardial blood flow and the severity of coronary-artery stenosis. N Engl J Med. 1994;330:1782–8.

    Google Scholar 

  6. Krivokapich J, Czernin J, Schelbert HR. Dobutamine positron emission tomography: absolute quantitation of rest and dobutamine myocardial blood flow and correlation with cardiac work and percent diameter stenosis in patients with and without coronary artery disease. J Am Coll Cardiol. 1996;28:565–72.

    Article  PubMed  CAS  Google Scholar 

  7. Di Carli M, Czernin J, Hoh CK, Gerbaudo VH, Brunken RC, Huang SC, et al. Relation among stenosis severity, myocardial blood flow, and flow reserve in patients with coronary artery disease. Circulation. 1995;91:1944–51.

    Article  PubMed  Google Scholar 

  8. Demer LL, Gould KL, Goldstein RA, Kirkeeide RL, Mullani NA, Smalling RW, et al. Assessment of coronary artery disease severity by positron emission tomography. Comparison with quantitative arteriography in 193 patients. Circulation. 1989;79:825–35.

    Article  PubMed  CAS  Google Scholar 

  9. Schelbert HR DL. Evaluation of myocardial blood flow in cardiac disease: second edition. Philadelphia: W.B. Saunders; 1996.

  10. •• Schindler TH, Schelbert HR, Quercioli A, Dilsizian V. Cardiac PET imaging for the detection and monitoring of coronary artery disease and microvascular health. JACC Cardiovasc Imaging. 2010;3:623–40. This review provides an excellent update on clinical and research possibilities of noninvasive MBF quantification with PET/CT.

    Article  PubMed  Google Scholar 

  11. Goldstein RA, Kirkeeide RL, Demer LL, Merhige M, Nishikawa A, Smalling RW, et al. Relation between geometric dimensions of coronary artery stenoses and myocardial perfusion reserve in man. J Clin Invest. 1987;79:1473–8.

    Article  PubMed  CAS  Google Scholar 

  12. Marcus ML, Skorton DJ, Johnson MR, Collins SM, Harrison DG, Kerber RE. Visual estimates of percent diameter coronary stenosis: “a battered gold standard”. JAm Coll Cardiol. 1988;11:882–5.

    Article  CAS  Google Scholar 

  13. Vogel RA. Assessing stenosis significance by coronary arteriography: are the best variables good enough? J Am Coll Cardiol. 1988;12:692–3.

    Article  PubMed  CAS  Google Scholar 

  14. White CW, Wright CB, Doty DB, Hiratza LF, Eastham CL, Harrison DG, et al. Does visual interpretation of the coronary arteriogram predict the physiologic importance of a coronary stenosis? N Engl J Med. 1984;310:819–24.

    Article  PubMed  CAS  Google Scholar 

  15. Tamaki N, Yonekura Y, Senda M, Yamashita K, Koide H, Saji H, et al. Value and limitation of stress thallium-201 single photon emission computed tomography: comparison with nitrogen-13 ammonia positron tomography. J Nucl Med. 1988;29:1181–8.

    PubMed  CAS  Google Scholar 

  16. Machac J, Bacharach SL, Bateman TM, Bax JJ, Beanlands R, Bengel F, et al. Positron emission tomography myocardial perfusion and glucose metabolism imaging. J Nucl Cardiol. 2006;13:e121–51.

    Article  PubMed  Google Scholar 

  17. Knuuti J. Hybrid SPECT-CT and PET-CT: current concepts and developments. Curr Cardiovasc Imaging Rep. 2011;3:468–75.

    Article  Google Scholar 

  18. •• Bengel FM, Higuchi T, Javadi MS, Lautamäki R. Cardiac positron emission tomography. J Am Coll Cardiol. 2009;54:1–15. This review provides very valuable information on the clinical role of PET-determined myocardial perfusion and flow.

    Article  PubMed  Google Scholar 

  19. Sampson UK, Dorbala S, Limaye A, Kwong R, Di Carli MF. Diagnostic accuracy of rubidium-82 myocardial perfusion imaging with hybrid positron emission tomography/computed tomography in the detection of coronary artery disease. J Am Coll Cardiol. 2007;49:1052–8.

    Article  PubMed  CAS  Google Scholar 

  20. Hsiao EM, Ali B, Dorbala S. Clinical role of hybrid imaging. Curr Cardiovasc Imaging Rep. 2010;3:325–35.

    Article  Google Scholar 

  21. Flotats A, Bravo PE, Fukushima K, Chaudhry MA, Merrill FM, Bengel FM. 82-Rb PET myocardial perfusion imaging is superior to (99m)Tc-labelled agent SPECT in patients with known or suspected coronary artery disease. Eur J Nucl Med Mol Imaging. 2012;39:1233–9.

    Article  PubMed  Google Scholar 

  22. Bateman TM, Heller GV, McGhie AI, Friedman JD, Case JA, Bryngelson JR, et al. Diagnostic accuracy of rest/stress ECG-gated Rb-82 myocardial perfusion PET: comparison with ECG-gated Tc-99m sestamibi SPECT. J Nucl Cardiol. 2006;13:24–33.

    Article  PubMed  Google Scholar 

  23. Achenbach S, Dilsizian V, Kramer CM, Zoghbi WA. The year in coronary artery disease. JACC Cardiovasc Imaging. 2009;2:774–86.

    Article  PubMed  Google Scholar 

  24. Fiechter M, Ghadri JR, Wolfrum M, Kuest SM, Pazhenkottil AP, Herzog BA, et al. Downstream resource utilization following hybrid cardiac imaging with an integrated cadmium-zinc-telluride/64-slice CT device. Eur J Nucl Med Mol Imaging. 2011;39:430–6.

    Google Scholar 

  25. Pazhenkottil AP, Nkoulou RN, Ghadri JR, Herzog BA, Kuest SM, Husmann L, et al. Impact of cardiac hybrid single-photon emission computed tomography/computed tomography imaging on choice of treatment strategy in coronary artery disease. Eur Heart J. 2011;32:2824–9.

    Article  PubMed  Google Scholar 

  26. Sato A, Hiroe M, Tamura M, Ohigashi H, Nozato T, Hikita H, et al. Quantitative measures of coronary stenosis severity by 64-Slice CT angiography and relation to physiologic significance of perfusion in nonobese patients: comparison with stress myocardial perfusion imaging. J Nucl Med. 2008;49:564–72.

    Article  PubMed  Google Scholar 

  27. Boogers MJ, Broersen A, van Velzen JE, de Graaf FR, El-Naggar HM, Dijkstra J, et al. Automated quantification of coronary plaque with computed tomography: comparison with intravascular ultrasound using a dedicated registration algorithm for fusion-based quantification. Eur Heart J. 2012;33:1007–16.

    Article  PubMed  Google Scholar 

  28. • Gould KL. Does coronary flow trump coronary anatomy. JACC Cardiovasc Imaging. 2009;2:1009–23. Excellent article which compares the clinical value of coronary flow vs coronary stenosis assessment.

    Article  PubMed  Google Scholar 

  29. •• Gould KL. Coronary flow reserve and pharmacologic stress perfusion imaging: beginnings and evolution. JACC Cardiovasc Imaging. 2009;2:664–9. This review article provides a very thorough update on the evaluation and interpretation of the coronary flow reserve.

    Article  PubMed  Google Scholar 

  30. Keane D, Haase J, Slager CJ, Montauban van Swijndregt E, Lehmann KG, Ozaki Y, et al. Comparative validation of quantitative coronary angiography systems. Results and implications from a multicenter study using a standardized approach. Circulation. 1995;91:2174–83.

    Article  PubMed  CAS  Google Scholar 

  31. Baller D, Notohamiprodjo G, Gleichmann U, Holzinger J, Weise R, Lehmann J. Improvement in coronary flow reserve determined by positron emission tomography after 6 months of cholesterol-lowering therapy in patients with early stages of coronary atherosclerosis. Circulation. 1999;99:2871–5.

    Article  PubMed  CAS  Google Scholar 

  32. Mancini GB, Henry GC, Macaya C, O’Neill BJ, Pucillo AL, Carere RG, et al. Angiotensin-converting enzyme inhibition with quinapril improves endothelial vasomotor dysfunction in patients with coronary artery disease. The TREND (Trial on Reversing ENdothelial Dysfunction) Study. Circulation. 1996;94:258–65.

    Article  PubMed  CAS  Google Scholar 

  33. • Shaw LJ, Berman DS, Maron DJ, Mancini GB, Hayes SW, Hartigan PM, et al. Optimal medical therapy with or without percutaneous coronary intervention to reduce ischemic burden: results from the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation (COURAGE) trial nuclear substudy. Circulation. 2008;117:283–91. This substudy of the COURAGE trial emphasizes that reduction in ischemic burden via PCI or optimal medical treatment results in a substantial lower risk for death and myocardial infarction.

    Google Scholar 

  34. Berry C, Balachandran KP, L’Allier PL, Lespérance J, Bonan R, Oldroyd KG. Importance of collateral circulation in coronary heart disease. Eur Heart J. 2007;28:278–91.

    Article  PubMed  Google Scholar 

  35. • Ziadi MC, Dekemp RA, Williams K, Guo A, Renaud JM, Chow BJ, 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. These observations are first to describe the use of MFR to enhance the detection of multivessel disease in clinical routine.

    Article  PubMed  Google Scholar 

  36. Joye JD, Schulman DS, Lasorda D, Farah T, Donohue BC, Reichek N. Intracoronary Doppler guide wire vs stress single-photon emission computed tomographic thallium-201 imaging in assessment of intermediate coronary stenoses. J Am Coll Cardiol. 1994;24:940–7.

    Article  PubMed  CAS  Google Scholar 

  37. Miller DD, Donohue TJ, Younis LT, Bach RG, Aguirre FV, Wittry MD, et al. Correlation of pharmacological 99mTc-sestamibi myocardial perfusion imaging with poststenotic coronary flow reserve in patients with angiographically intermediate coronary artery stenoses. Circulation. 1994;89:2150–60.

    Article  PubMed  CAS  Google Scholar 

  38. Deychak YA, Segal J, Reiner JS, Nachnani S. Doppler guide wire-derived coronary flow reserve distal to intermediate stenoses used in clinical decision making regarding interventional therapy. Am Heart J. 1994;128:178–81.

    Article  PubMed  CAS  Google Scholar 

  39. Donohue TJ, Miller DD, Bach RG, Tron C, Wolford T, Caracciolo EA, et al. Correlation of poststenotic hyperemic coronary flow velocity and pressure with abnormal stress myocardial perfusion imaging in coronary artery disease. Am J Cardiol. 1996;77:948–54.

    Article  PubMed  CAS  Google Scholar 

  40. Kern MJ. Coronary physiology revisited: practical insights from the cardiac catheterization laboratory. Circulation. 2000;101:1344–51.

    Article  PubMed  CAS  Google Scholar 

  41. 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 vs relative myocardial tracer content for physiological assessment of coronary artery stenosis severity and location. JACC Cardiovasc Imaging. 2009;2:751–8.

    Article  PubMed  Google Scholar 

  42. Nesterov SV, Han C, Maki M, Kajander S, Naum AG, Helenius H, et al. Myocardial perfusion quantitation with 15O-labelled water PET: high reproducibility of the new cardiac analysis software (Carimas). Eur J Nucl Med Mol Imaging. 2009;36:1594–602.

    Article  PubMed  Google Scholar 

  43. Yoshinaga K, Katoh C, Noriyasu K, Iwado Y, Furuyama H, Ito Y, et al. Reduction of coronary flow reserve in areas with and without ischemia on stress perfusion imaging in patients with coronary artery disease: a study using oxygen 15-labeled water PET. J Nucl Cardiol. 2003;10:275–83.

    Article  PubMed  Google Scholar 

  44. Anagnostopoulos C, Almonacid A, El Fakhri G, Curillova Z, Sitek A, Roughton M, et al. Quantitative relationship between coronary vasodilator reserve assessed by 82Rb PET imaging and coronary artery stenosis severity. Eur J Nucl Med Mol Imaging. 2008;35:1593–601.

    Article  PubMed  Google Scholar 

  45. Quercioli A, Pataky Z, Vincenti G, Makoundou V, Di Marzo V, Montecucco F, et al. Elevated endocannabinoid plasma levels are associated with coronary circulatory dysfunction in obesity. Eur Heart J. 2011;32:1369–78.

    Article  PubMed  CAS  Google Scholar 

  46. 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.

    Article  PubMed  Google Scholar 

  47. • Valenta I, Dilsizian V, Quercioli A, Schelbert HR, Schindler TH. The influence of insulin resistance, obesity, and diabetes mellitus on vascular tone and myocardial blood flow. Curr Cardiol Rep. 2012;14:217–25. Excellent review article describing the potential of PET flow quantification in the assessment of coronary circulatory dysfunction in the pre-diabetic and diabetic state.

    Article  PubMed  Google Scholar 

  48. •• 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. This is a retrospectively performed study 725 in 245 patients with suspicion for CAD. In patients with normal PET perfusion imaging the evaluation of the MFR proved to be a strong outcome predictor, whereas a reduced MFR in those with stress-induced perfusion defects improved the prediction of an adverse outcome.

    Article  PubMed  Google Scholar 

  49. •• Ziadi MC, Dekemp RA, Williams KA, Guo A, Chow BJ, 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. This study enrolled prospectively 704 patients with suspected and known CAD who underwent 82Rb PET perfusion measurements and MFR calculation. The noninvasively calculated MFR predicted hard cardiac events and major adverse cardiac events independent of the presence of stress-induced myocardial perfusion defects and other parameters.

  50. Fukushima K, Javadi MS, Higuchi T, Lautamäki R, Merrill J, Nekolla SG, et al. Prediction of short-termcardiovascular events using quantification of global myocardial flow reserve in patients referred for clinical 82Rb PET perfusion imaging. J Nucl Med. 2011;52:726–32.

    Article  PubMed  Google Scholar 

  51. • Schindler TH, Nitzsche EU, Schelbert HR, Olschewski M, Sayre J, Mix M, et al. Positron emission tomography-measured abnormal responses of myocardial blood flow to sympathetic stimulation are associated with the risk of developing cardiovascular events. J Am Coll Cardiol. 2005;45:1505–12. This study was the first to describe that impaired myocardial blood flow increases to sympathetic stimulation with cold pressor test as determined with 13N-ammonia PET was predictive of future cardiovascular events in cardiovascular risk patients with normal coronary angiograms.

    Article  PubMed  Google Scholar 

  52. • 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(15):1858–68. Interesting retrospective analysis in 2783 consecutive patients undergoing PET perfusion and flow measurements. As it was observed, among diabetic patients without CAD, those with impaired CFR have event rates comparable with patients with prior CAD while those with preserved CFR have event rates comparable to non-diabetics.

    Article  PubMed  CAS  Google Scholar 

  53. Tio RA, Dabeshlim A, Siebelink HM, 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.

    Article  PubMed  Google Scholar 

  54. Smith WH, Kastner RJ, Calnon DA, Segalla D, Beller GA, Watson DD. Quantitative gated single photon emission computed tomography imaging: a counts-based method for display and measurement of regional and global 768 ventricular systolic function. J Nucl Cardiol. 1997;4:451–63.

    Article  PubMed  CAS  Google Scholar 

  55. Dorbala S, Vangala D, Sampson U, Limaye A, Kwong R, Di Carli MF. Value of vasodilator left ventricular ejection fraction reserve in evaluating the magnitude of myocardium at risk and the extent of angiographic coronary artery disease: a 82Rb PET/CT study. J Nucl Med. 2007;48:349–58.

    PubMed  Google Scholar 

  56. Zeiher AM, Drexler H, Wollschlager H, Just H. Modulation of coronary vasomotor tone in humans. Progressive endothelial dysfunction with different early stages of coronary atherosclerosis. Circulation. 1991;83:391–401.

    Article  PubMed  CAS  Google Scholar 

  57. Schindler TH, Nitzsche EU, Olschewski M, Brink I, Mix M, Facta A, et al. PET-Measured responses of MBF to cold pressor testing correlate with indices of coronary vasomotion on quantitative coronary angiography. J Nucl Med. 2004;45:419–28.

    PubMed  Google Scholar 

  58. Dimmeler S, Fleming I, Fisslthaler B, Hermann C, Busse R, Zeiher AM. Activation of nitric oxide synthase in endothelial cells by Akt-dependent phosphorylation. Nature. 1999;399:601–5.

    Article  PubMed  CAS  Google Scholar 

  59. Campisi R, Czernin J, Schoder H, Sayre JW, Schelbert HR. L-Arginine normalizes coronary vasomotion in long-term smokers. Circulation. 1999;99:491–7.

    Article  PubMed  CAS  Google Scholar 

  60. Czernin J, Barnard RJ, Sun KT, Krivokapich J, Nitzsche E, Dorsey D, et al. Effect of short-term cardiovascular conditioning and low-fat diet on myocardial blood flow and flow reserve. Circulation. 1995;92:197–204.

    Article  PubMed  CAS  Google Scholar 

  61. Lerman A, Zeiher AM. Endothelial function: cardiac events. Circulation. 2005;111:363–8.

    Article  PubMed  Google Scholar 

  62. Rubinshtein R, Yang EH, Rihal CS, Prasad A, Lennon RJ, Best PJ, et al. Coronary microcirculatory vasodilator function in relation to risk factors among patients without obstructive coronary disease and low to intermediate Framingham score. Eur Heart J. 2010;31:936–42.

    Article  PubMed  Google Scholar 

  63. Reddy KG, Nair RN, Sheehan HM, Hodgson JM. Evidence that selective endothelial dysfunction may occur in the absence of angiographic or ultrasound atherosclerosis in patients with risk factors for atherosclerosis. J Am Coll Cardiol. 1994;23:833–43.

    Article  PubMed  CAS  Google Scholar 

  64. Schindler TH, Zhang XL, Vincenti G, Lerch R, Schelbert HR. Role of PET in the evaluation and understanding of coronary physiology. J Nucl Cardiol. 2007;14:589–603.

    Article  PubMed  Google Scholar 

  65. Buus NH, Bottcher M, Hermansen F, Sander M, Nielsen TT, Mulvany MJ. Influence of nitric oxide synthase and adrenergic inhibition on adenosine-induced myocardial hyperemia. Circulation. 2001;104:2305–10.

    Article  PubMed  CAS  Google Scholar 

  66. Tawakol A, Forgione MA, Stuehlinger M, Alpert NM, Cooke JP, Loscalzo J, et al. Homocysteine impairs coronary microvascular dilator function in humans. J Am Coll Cardiol. 2002;40:1051–8.

    Article  PubMed  CAS  Google Scholar 

  67. Schindler TH, Cardenas J, Prior JO, Facta AD, Kreissl MC, Zhang XL, et al. Relationship between increasing body weight, insulin resistance, inflammation, adipocytokine leptin, and coronary circulatory function. J Am Coll Cardiol. 2006;47:1188–95.

    Article  PubMed  CAS  Google Scholar 

  68. Munzel T, Daiber A, Ullrich V, Mülsch A. Vascular consequences of endothelial nitric oxide synthase uncoupling for the activity and expression of the soluble guanylyl cyclase and the cGMP- dependent protein kinase. Arterioscler Thromb Vasc Biol. 2005;25:551–7.

    Article  Google Scholar 

  69. Prior JO, Quinones MJ, Hernandez-Pampaloni M, Facta AD, Schindler TH, Sayre JW, et al. Coronary circulatory dysfunction in insulin resistance, impaired glucose tolerance, and type 2 diabetes mellitus. Circulation. 2005;111:2291–8.

    Article  PubMed  CAS  Google Scholar 

  70. Di Carli MF, Janisse J, Grunberger G, Ager J. Role of chronic hyperglycemia in the pathogenesis of coronary microvascular dysfunction in diabetes. J Am Coll Cardiol. 2003;41:1387–93.

    Article  PubMed  Google Scholar 

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Acknowledgments

This work was supported by Research Grant 3200B0-122237 of the Swiss National Science Foundation (SNF), with contributions of the Clinical Research Center, University Hospital and Faculty of Medicine, Geneva, and the Louis-Jeantet Foundation, Gustave and Simone Prevot, and Swiss Heart Foundation.

Disclosure

Conflicts of interest: I. Valenta: none; V. Dilsizian: none; A. Quercioli: none; T.D. Ruddy: has received grant support from Nordion Inc. (unrestricted Investigator-initiated research grant); GE Healthcare (unrestricted Investigator-initiated research grant); and AstraZeneca (unrestricted Investigator-initiated research grant); T.H. Schindler: none.

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  1. Department of Specialties in Medicine, Division of Cardiology, 6th Floor, Nuclear Cardiology and Cardiac PET/CT, University Hospitals of Geneva, Rue Gabrielle-Perret-Gentil 4, CH-1211, Geneva, Switzerland

    Ines Valenta, Alessandra Quercioli & Thomas H. Schindler

  2. Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA

    Vasken Dilsizian

  3. Divisions of Cardiology and Nuclear Medicine, University of Ottawa, Ottawa, ON, Canada

    Terrence D. Ruddy

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  1. Ines Valenta
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Correspondence to Thomas H. Schindler.

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Valenta, I., Dilsizian, V., Quercioli, A. et al. Quantitative PET/CT Measures of Myocardial Flow Reserve and Atherosclerosis for Cardiac Risk Assessment and Predicting Adverse Patient Outcomes. Curr Cardiol Rep 15, 344 (2013). https://doi.org/10.1007/s11886-012-0344-0

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