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Myocardial perfusion imaging for diabetes: Key points from the evidence and clinical questions to be answered

  • Wanda AcampaEmail author
  • Roberta Assante
  • Emilia Zampella
  • Mario Petretta
  • Alberto Cuocolo
Review Article
  • 8 Downloads

Abstract

Diabetes represents a worldwide increasing problem and cardiovascular disease is the most common cause of death in diabetic patients. Pathophysiology that links diabetes to cardiovascular disease is a complex and multifactorial phenomenon evolving over time and involving both large blood vessels (macrovasculature) and small blood vessels (microvasculature). Myocardial perfusion imaging (MPI) imaging by both single-photon emission computer tomography and positron emission tomography with different specific tracers has become an indispensable tool for discriminating normal from diseased myocardial tissues and left ventricular function and monitoring myocardial blood flows, leading to the evaluation of almost overall physiologic consequences of the macro- and microvascular impairment involved in diabetic patients. This review will provide an overview of the role of MPI in the diagnosis and risk assessment of patients with diabetes and suspected or known CAD.

Keywords

Diabetes MPI Gated SPECT PET Diagnostic and prognostic application 

Notes

Disclosure

Acampa, Assante, Zampella, Petretta, and Cuocolo declare that they have no conflict of interest to disclose.

Supplementary material

12350_2019_1846_MOESM1_ESM.pptx (391 kb)
Supplementary material 1 (PPTX 391 kb)

References

  1. 1.
    Guariguata L, Whiting DR, Hambleton I, Beagley J, Linnenkamp U, Shaw JE. Global estimates of diabetes prevalence for 2013 and projections for 2035. Diabetes Res Clin Pract 2014;103:137-49.CrossRefGoogle Scholar
  2. 2.
    International Diabetes Federation. https://idf.org. Last connection 11 Jun 2018.
  3. 3.
    Haffner SM, Lehto S, Rönnemaa T, Pyörälä K, Laakso M. Mortality from coronary heart disease in subjects with type 2 diabetes and in nondiabetic subjects with and without prior myocardial infarction. N Engl J Med 1998;339:229-34.CrossRefGoogle Scholar
  4. 4.
    Goraya TY, Leibson CL, Palumbo PJ, Weston SA, Killian JM, Pfeifer EA, et al. Coronary atherosclerosis in diabetes mellitus: A population-based autopsy study. J Am Coll Cardiol 2002;40:946-53.CrossRefGoogle Scholar
  5. 5.
    Taskinen MR, Borén J. New insights into the pathophysiology of dyslipidemia in type 2 diabetes. Atherosclerosis 2015;239:483-95.CrossRefGoogle Scholar
  6. 6.
    Burke AP, Kolodgie FD, Zieske A, Fowler DR, Weber DK, Varghese PJ, et al. Morphologic findings of coronary atherosclerotic plaques in diabetics: A postmortem study. Arterioscler Thromb Vasc Biol 2004;24:1266-71.CrossRefGoogle Scholar
  7. 7.
    Langer A, Freeman MR, Josse RG, Steiner G, Armstrong PW. Detection of silent myocardial ischemia in diabetes mellitus. Am J Cardiol. 1991;67:1073-8.CrossRefGoogle Scholar
  8. 8.
    Weir MR. Microalbuminuria and cardiovascular disease. Clin J Am Soc Nephrol 2007;2:581-90.CrossRefGoogle Scholar
  9. 9.
    Hendel RC, Berman DS, Di Carli MF, Heidenreich PA, Henkin RE, Pellikka PA, American College of Cardiology Foundation Appropriate Use Criteria Task Force; American Society of Nuclear Cardiology; American College of Radiology; American Heart Association; American Society of Echocardiography; Society of Cardiovascular Computed Tomography; Society for Cardiovascular Magnetic Resonance; Society of Nuclear Medicine, et al. ACCF/ASNC/ACR/AHA/ASE/SCCT/SCMR/SNM 2009 appropriate use criteria for cardiac radionuclide imaging: A report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, the American Society of Nuclear Cardiology, the American College of Radiology, the American Heart Association, the American Society of Echocardiography, the Society of Cardiovascular Computed Tomography, the Society for Cardiovascular Magnetic Resonance, and the Society of Nuclear Medicine. Circulation 2009;119:e561-87.Google Scholar
  10. 10.
    Grundy SM. Diabetes and coronary risk equivalency: What does it mean? Diabetes Care 2006;29:457-60.CrossRefGoogle Scholar
  11. 11.
    Cuocolo A, Concilio C, Acampa W, Ferro A, Evangelista L, Daniele S, et al. Cardiovascular risk stratification of diabetic patients. Minerva Endocrinol 2009;34:205-21.Google Scholar
  12. 12.
    Saely CH, Aczel S, Koch L, Schmid F, Marte T, Huber K, et al. Diabetes as a coronary artery disease risk equivalent: Before a change of paradigm? Eur J Cardiovasc Prev Rehabil 2010;17:94-9.CrossRefGoogle Scholar
  13. 13.
    Fox CS, Golden SH, Anderson C, Bray GA, Burke LE, de Boer IH, American Heart Association Diabetes Committee of the Council on Lifestyle and Cardiometabolic Health, Council on Clinical Cardiology, Council on Cardiovascular and Stroke Nursing, Council on Cardiovascular Surgery and Anesthesia, Council on Quality of Care and Outcomes Research, and the American Diabetes Association, et al. Update on prevention of cardiovascular disease in adults with type 2 diabetes mellitus in light of recent evidence: A scientific statement from the American Heart Association and the American Diabetes Association. Circulation 2015;132:691-718.CrossRefGoogle Scholar
  14. 14.
    Acampa W, Petretta M, Evangelista L, Daniele S, Xhoxhi E, De Rimini ML, et al. Myocardial perfusion imaging and risk classification for coronary heart disease in diabetic patients. The IDIS study: A prospective, multicentre trial. Eur J Nucl Med Mol Imaging 2012;39:387-95.CrossRefGoogle Scholar
  15. 15.
    Acampa W, Petretta M, Daniele S, Del Prete G, Assante R, Zampella E, et al. Incremental prognostic value of stress myocardial perfusion imaging in asymptomatic diabetic patients. Atherosclerosis 2013;227:307-12.CrossRefGoogle Scholar
  16. 16.
    Acampa W, Petretta M, Cuocolo R, Daniele S, Cantoni V, Cuocolo A. Warranty period of normal stress myocardial perfusion imaging in diabetic patients: A propensity score analysis. J Nucl Cardiol 2014;21:50-6.CrossRefGoogle Scholar
  17. 17.
    Gaudieri V, Nappi C, Acampa W, Zampella E, Assante R, Mannarino T, et al. Added prognostic value of left ventricular shape by gated SPECT imaging in patients with suspected coronary artery disease and normal myocardial perfusion. J Nucl Cardiol 2017.  https://doi.org/10.1007/s12350-017-1090-x.Google Scholar
  18. 18.
    Nappi C, Gaudieri V, Acampa W, Assante R, Zampella E, Mainolfi CG, et al. Comparison of left ventricular shape by gated SPECT imaging in diabetic and nondiabetic patients with normal myocardial perfusion: A propensity score analysis. J Nucl Cardiol 2018;25:394-403.CrossRefGoogle Scholar
  19. 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.CrossRefGoogle Scholar
  20. 20.
    Bybee KA, Lee J, Markiewicz R, Longmore R, McGhie AI, O’Keefe JH, et al. Diagnostic and clinical benefit of combined coronary calcium and perfusion assessment in patients undergoing PET/CT myocardial perfusion stress imaging. J Nucl Cardiol 2010;17:188-96.CrossRefGoogle Scholar
  21. 21.
    Nakanishi R, Ceponiene I, Osawa K, Luo Y, Kanisawa M, Megowan N, et al. Plaque progression assessed by a novel semi-automated quantitative plaque software on coronary computed tomography angiography between diabetes and non-diabetes patients: A propensity-score matching study. Atherosclerosis 2016;255:73-9.CrossRefGoogle Scholar
  22. 22.
    Lee JM, Bang JI, Koo BK, Hwang D, Park J, Zhang J, et al. Clinical relevance of 18F-sodium fluoride positron-emission tomography in noninvasive identification of high-risk plaque in patients with coronary artery disease. Circ Cardiovasc Imaging 2017;10:e006704.CrossRefGoogle Scholar
  23. 23.
    Raggi P, Senior P, Shahbaz S, Kaul P, Hung R, Coulden R, et al. 18F-sodium fluoride imaging of coronary atherosclerosis in ambulatory patients with diabetes mellitus. Arterioscler Thromb Vasc Biol 2019;39:276-84.CrossRefGoogle Scholar
  24. 24.
    Zaha VG, Joshi PH, McGuire DK. Probing for vulnerable plaque in patients with diabetes mellitus. Arterioscler Thromb Vasc Biol 2019;39:124-5.CrossRefGoogle Scholar
  25. 25.
    Kiramijyan S, Ahmadi N, Isma’eel H, Flores F, Shaw LJ, Raggi P, et al. Impact of coronary artery calcium progression and statin therapy on clinical outcome in subjects with and without diabetes mellitus. Am J Cardiol 2013;111:356-61.CrossRefGoogle Scholar
  26. 26.
    Valenti V, Hartaigh BÓ, Cho I, Schulman-Marcus J, Gransar H, Heo R, et al. Absence of coronary artery calcium identifies asymptomatic diabetic individuals at low near-term but not long-term risk of mortality: A 15-year follow-up study of 9715 patients. Circ Cardiovasc Imaging 2016;9:e003528.CrossRefGoogle Scholar
  27. 27.
    Schindler TH, Facta AD, Prior JO, Cadenas J, Zhang XL, Li Y, et al. Structural alterations of the coronary arterial wall are associated with myocardial flow heterogeneity in type 2 diabetes mellitus. Eur J Nucl Med Mol Imaging 2009;36:219-29.CrossRefGoogle Scholar
  28. 28.
    Schindler TH, Cadenas J, Facta AD, Li Y, Olschewski M, Sayre J, et al. Improvement in coronary endothelial function is independently associated with a slowed progression of coronary artery calcification in type 2 diabetes mellitus. Eur Heart J 2009;30:3064-73.CrossRefGoogle Scholar
  29. 29.
    Assante R, Acampa W, Zampella E, Arumugam P, Nappi C, Gaudieri V, et al. Coronary atherosclerotic burden vs. coronary vascular function in diabetic and nondiabetic patients with normal myocardial perfusion: A propensity score analysis. Eur J Nucl Med Mol Imaging 2017;44:1129-35.CrossRefGoogle Scholar
  30. 30.
    Lloyd-Jones DM, Braun LT, Ndumele CE, Smith SC Jr, Sperling LS, Virani SS, et al. Use of risk assessment tools to guide decision making in the primary prevention of atherosclerotic cardiovascular disease. Circulation 2019;73:3153-67.  https://doi.org/10.1161/cir.0000000000000638.Google Scholar
  31. 31.
    Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, et al. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: A report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol 2018;1:1.  https://doi.org/10.1016/j.jacc.2018.11.003.Google Scholar
  32. 32.
    Zellweger MJ, Maraun M, Osterhues HH, Keller U, Müller-Brand J, Jeger R, et al. Progression to overt or silent CAD in asymptomatic patients with diabetes mellitus at high coronary risk: Main findings of the prospective multicenter BARDOT trial with a pilot randomized treatment substudy. JACC Cardiovasc Imaging 2014;7:1001-10.CrossRefGoogle Scholar
  33. 33.
    Caobelli F, Haaf P, Chronis J, Haenny G, Brinkert M, Pfisterer ME, Basel Asymptomatic High-Risk Diabetics’ Outcome Trial (BARDOT) Investigators, et al. Prognostic usefulness of cardiac stress test modalities in patients with type 2 diabetes mellitus who underwent myocardial perfusion scintigraphy (from the Basel Asymptomatic High-Risk Diabetics’ Outcome Trial). Am J Cardiol 2017;120:1098-103.CrossRefGoogle Scholar
  34. 34.
    De Lorenzo A, Souza VF, Glerian L, Lima RS. Prognostic assessment of diabetics using myocardial perfusion imaging: Diabetes mellitus is still a coronary artery disease equivalent. Open Cardiovasc Med J 2017;11:76-83.CrossRefGoogle Scholar
  35. 35.
    Shaw LJ, Iskandrian AE. Prognostic value of gated myocardial perfusion SPECT. J Nucl Cardiol 2004;11:171-85.CrossRefGoogle Scholar
  36. 36.
    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
  37. 37.
    Assante R, Acampa W, Zampella E, Arumugam P, Nappi C, Gaudieri V, et al. Prognostic value of atherosclerotic burden and coronary vascular function in patients with suspected coronary artery disease. Eur J Nucl Med Mol Imaging 2017;44:2290-8.CrossRefGoogle Scholar
  38. 38.
    American Diabetes Association. 10. Cardiovascular disease and risk management: Standards of medical care in diabetes-2019. Diabetes Care 2019;42:S103-23.CrossRefGoogle Scholar
  39. 39.
    Greenland P, Alpert JS, Beller GA, Benjamin EJ, Budoff MJ, Fayad ZA, American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines, et al. ACCF/AHA guideline for assessment of cardiovascular risk in asymptomatic adults: A report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation 2010;2010:e584-636.Google Scholar
  40. 40.
    Lima EG, Hueb W, Garcia RM, Pereira AC, Soares PR, Favarato D, et al. Impact of diabetes on 10-year outcomes of patients with multivessel coronary artery disease in the Medicine, Angioplasty, or Surgery Study II (MASS II) trial. Am Heart J 2013;166:250-7.CrossRefGoogle Scholar
  41. 41.
    Rozanski A, Muhlestein JB, Berman DS. Primary prevention of CVD: The role of imaging trials. JACC Cardiovasc Imaging 2017;10:304-17.CrossRefGoogle Scholar
  42. 42.
    Young LH, Wackers FJ, Chyun DA, Davey JA, Barrett EJ, Taillefer R, DIAD Investigators, et al. Cardiac outcomes after screening for asymptomatic coronary artery disease in patients with type 2 diabetes: The DIAD study: A randomized controlled trial. JAMA 2009;301:1547-55.CrossRefGoogle Scholar
  43. 43.
    Muhlestein JB, Lappé DL, Lima JA, Rosen BD, May HT, Knight S, et al. Effect of screening for coronary artery disease using CT angiography on mortality and cardiac events in high-risk patients with diabetes: The FACTOR-64 randomized clinical trial. JAMA 2014;312:2234-43.CrossRefGoogle Scholar

Copyright information

© American Society of Nuclear Cardiology 2019

Authors and Affiliations

  • Wanda Acampa
    • 1
    Email author
  • Roberta Assante
    • 1
  • Emilia Zampella
    • 1
  • Mario Petretta
    • 2
  • Alberto Cuocolo
    • 1
  1. 1.Department of Advanced Biomedical SciencesUniversity Federico IINaplesItaly
  2. 2.Department of Translational Medical SciencesUniversity Federico IINaplesItaly

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