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Prognostic value of combined coronary angiography-derived IMR and myocardial perfusion imaging by CZT SPECT in INOCA

  • Original Article
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Journal of Nuclear Cardiology Aims and scope

Abstract

Background

A significant proportion of ischemia with non-obstructive coronary artery disease (INOCA) demonstrate coronary microvascular dysfunction (CMD), a condition associated with abnormal myocardial perfusion imaging (MPI) and adverse outcomes. Coronary angiography-derived index of microvascular resistance (caIMR) is a novel non-invasive technique to assess CMD. We aimed to investigate the prognostic value of combined caIMR and MPI by CZT SPECT in INOCA patients.

Methods

Consecutive 151 patients with chest pain and < 50% coronary stenosis who underwent coronary angiography and MPI within 3 months were enrolled. caIMR was calculated by computational pressure-flow dynamics. CMD was defined as caIMR ≥ 25. The endpoint was major adverse cardiac events (MACE: cardiovascular death, nonfatal myocardial infarction, revascularization, angina-related rehospitalization, heart failure, and stroke).

Results

Of all INOCA patients, CMD was present in 93 (61.6%) patients. The prevalence of abnormal MPI was significantly higher in CMD compared with non-CMD patients (40.9% vs 13.8%, P < .001). CMD showed a higher risk of MACE than non-CMD patients. Patients with both CMD and abnormal MPI had the worst prognosis, followed by patients with CMD and normal MPI (log-rank P < .001). Cox regression analysis identified CMD (HR 3.121, 95%CI 1.221-7.974, P = .017) and MPI (HR 2.704, 95%CI 1.030-7.099, P = .043) as predictive of MACE. The prognostic value of INOCA patients enhanced significantly by adding CMD and MPI to the model with clinical risk factors (AUC = 0.777 vs 0.686, P = .030).

Conclusion

caIMR-derived CMD is associated with increased risk of MACE among INOCA patients. Patients with abnormalities on both caIMR and MPI had the worse outcomes.

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Abbreviations

INOCA:

Ischemia with non-obstructive coronary artery disease

CMD:

Coronary microvascular dysfunction

caIMR:

Coronary angiography-derived index of microcirculatory resistance

MPI:

Myocardial perfusion imaging

CZT:

Cadmium zinc telluride

MACE:

Major adverse cardiac events

References

  1. Bairey Merz CN, Pepine CJ, Walsh MN, Fleg JL. Ischemia and no obstructive coronary artery disease (INOCA): Developing evidence-based therapies and research agenda for the next decade. Circulation 2017;135:1075‐92.

    Article  PubMed  Google Scholar 

  2. Kunadian V, Chieffo A, Camici PG, Berry C, Escaned J, Maas A. An EAPCI Expert Consensus Document on Ischaemia with Non-Obstructive Coronary Arteries in Collaboration with European Society of Cardiology Working Group on Coronary Pathophysiology & Microcirculation Endorsed by Coronary Vasomotor Disorders International Study Group. Eur Heart J 2020;41:3504‐20.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  3. Jespersen L, Hvelplund A, Abildstrom SZ, Pedersen F, Galatius S, Madsen JK, et al. Stable angina pectoris with no obstructive coronary artery disease is associated with increased risks of major adverse cardiovascular events. Eur Heart J 2012;33:734‐44.

    Article  PubMed  Google Scholar 

  4. Patel MR, Dai D, Hernandez AF, Douglas PS, Messenger J, Garratt KN, et al. Prevalence and predictors of nonobstructive coronary artery disease identified with coronary angiography in contemporary clinical practice. Am Heart J 2014;167:846-852e842.

    Article  PubMed  Google Scholar 

  5. Radico F, Zimarino M, Fulgenzi F, Ricci F, Di Nicola M, Jespersen L, et al. Determinants of long-term clinical outcomes in patients with angina but without obstructive coronary artery disease: A systematic review and meta-analysis. Eur Heart J 2018;39:2135‐46.

    Article  PubMed  Google Scholar 

  6. Liu L, Abdu FA, Yin G, Xu B, Mohammed AQ, Xu S, et al. Prognostic value of myocardial perfusion imaging with D-SPECT camera in patients with ischemia and no obstructive coronary artery disease (INOCA). J Nucl Cardiol 2021;28:3025‐37.

    Article  PubMed  Google Scholar 

  7. Marinescu MA, Loffler AI, Ouellette M, Smith L, Kramer CM, Bourque JM. Coronary microvascular dysfunction, microvascular angina, and treatment strategies. JACC Cardiovasc Imaging 2015;8:210‐20.

    Article  PubMed Central  PubMed  Google Scholar 

  8. Patel MR, Peterson ED, Dai D, Brennan JM, Redberg RF, Anderson HV, et al. Low diagnostic yield of elective coronary angiography. N Engl J Med 2010;362:886‐95.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  9. Ford TJ, Corcoran D, Berry C. Stable coronary syndromes: Pathophysiology, diagnostic advances and therapeutic need. Heart 2018;104:284‐92.

    PubMed  Google Scholar 

  10. Knuuti J, Wijns W, Saraste A, Capodanno D, Barbato E, Funck-Brentano C, et al. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. Eur Heart J 2020;41:407‐77.

    Article  PubMed  Google Scholar 

  11. Rahman H, Corcoran D, Aetesam-Ur-Rahman M, Hoole SP, Berry C, Perera D. Diagnosis of patients with angina and non-obstructive coronary disease in the catheter laboratory. Heart 2019;105:1536‐42.

    Article  PubMed  Google Scholar 

  12. Fearon WF, Kobayashi Y. Invasive assessment of the coronary microvasculature: The index of microcirculatory resistance. Circ Cardiovasc Interv 2017;10:e005361.

    Article  PubMed  Google Scholar 

  13. Suda A, Takahashi J, Hao K, Kikuchi Y, Shindo T, Ikeda S, et al. Coronary functional abnormalities in patients with angina and nonobstructive coronary artery disease. J Am Coll Cardiol 2019;74:2350‐60.

    Article  CAS  PubMed  Google Scholar 

  14. Ai H, Feng Y, Gong Y, Zheng B, Jin Q, Zhang HP, et al. Coronary angiography-derived index of microvascular resistance. Front Physiol 2020;11:605356.

    Article  PubMed Central  PubMed  Google Scholar 

  15. De Maria GL, Scarsini R, Shanmuganathan M, Kotronias RA, Terentes-Printzios D, Borlotti A, et al. Angiography-derived index of microcirculatory resistance as a novel, pressure-wire-free tool to assess coronary microcirculation in ST elevation myocardial infarction. Int J Cardiovasc Imaging 2020;36:1395‐406.

    Article  PubMed Central  PubMed  Google Scholar 

  16. Choi KH, Dai N, Li Y, Kim J, Shin D, Lee SH, et al. Functional coronary angiography-derived index of microcirculatory resistance in patients with ST-segment elevation myocardial infarction. JACC Cardiovasc Interv 2021;14:1670‐84.

    Article  PubMed  Google Scholar 

  17. Scarsini R, Shanmuganathan M, Kotronias RA, Terentes-Printzios D, Borlotti A, Langrish JP, et al. Angiography-derived index of microcirculatory resistance (IMRangio) as a novel pressure-wire-free tool to assess coronary microvascular dysfunction in acute coronary syndromes and stable coronary artery disease. Int J Cardiovasc Imaging 2021;37:1801‐13.

    Article  PubMed  Google Scholar 

  18. Abdu FA, Liu L, Mohammed AQ, Yin G, Xu B, Zhang W, et al. Prognostic impact of coronary microvascular dysfunction in patients with myocardial infarction with non-obstructive coronary arteries. Eur J Intern Med 2021;92:79‐85.

    Article  PubMed  Google Scholar 

  19. Agostini D, Marie PY, Ben-Haim S, Rouzet F, Songy B, Giordano A, et al. Performance of cardiac cadmium–zinc–telluride gamma camera imaging in coronary artery disease: a review from the cardiovascular committee of the European Association of Nuclear Medicine (EANM). Eur J Nucl Med Mol Imaging 2016;43:2423‐32.

    Article  CAS  PubMed  Google Scholar 

  20. Cantoni V, Green R, Acampa W, Zampella E, Assante R, Nappi C, et al. Diagnostic performance of myocardial perfusion imaging with conventional and CZT single-photon emission computed tomography in detecting coronary artery disease: A meta-analysis. J Nucl Cardiol 2021;28:698‐715.

    Article  PubMed  Google Scholar 

  21. Perrin M, Djaballah W, Moulin F, Claudin M, Veran N, Imbert L, et al. Stress-first protocol for myocardial perfusion SPECT imaging with semiconductor cameras: High diagnostic performances with significant reduction in patient radiation doses. Eur J Nucl Med Mol Imaging 2015;42:1004‐11.

    Article  CAS  PubMed  Google Scholar 

  22. Taqueti VR, Dorbala S, Wolinsky D, Abbott B, Heller GV, Bateman TM, et al. Myocardial perfusion imaging in women for the evaluation of stable ischemic heart disease-state-of-the-evidence and clinical recommendations. J Nucl Cardiol 2017;24:1402‐26.

    Article  PubMed Central  PubMed  Google Scholar 

  23. Nudi F, Iskandrian AE, Schillaci O, Peruzzi M, Frati G, Biondi-Zoccai G. Diagnostic accuracy of myocardial perfusion imaging with CZT technology: Systemic review and meta-analysis of comparison with invasive coronary angiography. JACC Cardiovasc Imaging 2017;10:787‐94.

    Article  PubMed  Google Scholar 

  24. Diamond GA, Forrester JS. Analysis of probability as an aid in the clinical diagnosis of coronary-artery disease. N Engl J Med 1979;300:1350‐8.

    Article  CAS  PubMed  Google Scholar 

  25. Li J, Gong Y, Wang W, Yang Q, Liu B, Lu Y, et al. Accuracy of computational pressure-fluid dynamics applied to coronary angiography to derive fractional flow reserve: FLASH FFR. Cardiovasc Res 2020;116:1349‐56.

    Article  CAS  PubMed  Google Scholar 

  26. Henzlova MJ, Duvall WL, Einstein AJ, Travin MI, Verberne HJ. ASNC imaging guidelines for SPECT nuclear cardiology procedures: Stress, protocols, and tracers. J Nucl Cardiol 2016;23:606‐39.

    Article  PubMed  Google Scholar 

  27. Hachamovitch R, Berman DS, Shaw LJ, Kiat H, Cohen I, Cabico JA, et al. Incremental prognostic value of myocardial perfusion single photon emission computed tomography for the prediction of cardiac death: Differential stratification for risk of cardiac death and myocardial infarction. Circulation 1998;97:535‐43.

    Article  CAS  PubMed  Google Scholar 

  28. Sharir T, Germano G, Kang X, Lewin HC, Miranda R, Cohen I, et al. Prediction of myocardial infarction versus cardiac death by gated myocardial perfusion SPECT: Risk stratification by the amount of stress-induced ischemia and the poststress ejection fraction. J Nucl Med 2001;42:831‐7.

    CAS  PubMed  Google Scholar 

  29. Thygesen K, Alpert JS, Jaffe AS, Simoons ML, Chaitman BR, White HD, et al. Third universal definition of myocardial infarction. J Am Coll Cardiol 2012;60:1581‐98.

    Article  PubMed  Google Scholar 

  30. Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JGF, Coats AJS, et al. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J 2016;37:2129‐200.

    Article  PubMed  Google Scholar 

  31. Pencina M, D’Agostino R, Steyerberg E. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med 2011;30:11‐21.

    Article  PubMed  Google Scholar 

  32. Pencina M, D’Agostino R, Pencina K, Janssens A, Greenland P. Interpreting incremental value of markers added to risk prediction models. Am J Epidemiol 2012;176:473‐81.

    Article  PubMed Central  PubMed  Google Scholar 

  33. Pepine CJ, Anderson RD, Sharaf BL, Reis SE, Smith KM, Handberg EM, et al. Coronary microvascular reactivity to adenosine predicts adverse outcome in women evaluated for suspected ischemia results from the National Heart, Lung and Blood Institute WISE (Women’s Ischemia Syndrome Evaluation) study. J Am Coll Cardiol 2010;55:2825‐32.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  34. Masi S, Rizzoni D, Taddei S, Widmer RJ, Montezano AC, Luscher TF, et al. Assessment and pathophysiology of microvascular disease: Recent progress and clinical implications. Eur Heart J 2021;42:2590‐604.

    Article  CAS  PubMed  Google Scholar 

  35. Lee JM, Jung JH, Hwang D, Park J, Fan Y, Na SH, et al. Coronary flow reserve and microcirculatory resistance in patients with intermediate coronary stenosis. J Am Coll Cardiol 2016;67:1158‐69.

    Article  PubMed  Google Scholar 

  36. Nishi T, Murai T, Ciccarelli G, Shah SV, Kobayashi Y, Derimay F, et al. Prognostic value of coronary microvascular function measured immediately after percutaneous coronary intervention in stable coronary artery disease: An international multicenter study. Circ Cardiovasc Interv 2019;12:e007889.

    Article  PubMed  Google Scholar 

  37. Takahashi T, Theodoropoulos K, Latib A, Okura H, Kobayashi Y. Coronary physiologic assessment based on angiography and intracoronary imaging. J Cardiol 2021;9:S0914-5087(0921)00184-00182.

  38. Chowdhury FU, Vaidyanathan S, Bould M, Marsh J, Trickett C, Dodds K, et al. Rapid-acquisition myocardial perfusion scintigraphy (MPS) on a novel gamma camera using multipinhole collimation and miniaturized cadmium-zinc-telluride (CZT) detectors: Prognostic value and diagnostic accuracy in a ‘real-world’ nuclear cardiology service. Eur Heart J Cardiovasc Imaging 2014;15:275‐83.

    Article  CAS  PubMed  Google Scholar 

  39. Lima R, Peclat T, Soares T, Ferreira C, Souza AC, Camargo G. Comparison of the prognostic value of myocardial perfusion imaging using a CZT-SPECT camera with a conventional anger camera. J Nucl Cardiol 2017;24:245‐51.

    Article  PubMed  Google Scholar 

  40. Camici PG, d’Amati G, Rimoldi O. Coronary microvascular dysfunction: Mechanisms and functional assessment. Nat Rev Cardiol 2015;12:48‐62.

    Article  PubMed  Google Scholar 

  41. Thomson LE, Wei J, Agarwal M, Haft-Baradaran A, Shufelt C, Mehta PK, et al. Cardiac magnetic resonance myocardial perfusion reserve index is reduced in women with coronary microvascular dysfunction. A National Heart, Lung, and Blood Institute-sponsored study from the Women’s Ischemia Syndrome Evaluation. Circ Cardiovasc Imaging 2015. https://doi.org/10.1161/CIRCIMAGING.114.002481.

    Article  PubMed Central  PubMed  Google Scholar 

  42. Nkoulou R, Fuchs TA, Pazhenkottil AP, Kuest SM, Ghadri JR, Stehli J, et al. Absolute myocardial blood flow and flow reserve assessed by gated SPECT with cadmium-zinc-telluride detectors using 99mTc-tetrofosmin: Head-to-head comparison with 13N-ammonia PET. J Nucl Med 2016;57:1887‐92.

    Article  CAS  PubMed  Google Scholar 

  43. Giubbini R, Bertoli M, Durmo R, Bonacina M, Peli A, Faggiano I, et al. Comparison between N(13)NH3-PET and (99m)Tc-Tetrofosmin-CZT SPECT in the evaluation of absolute myocardial blood flow and flow reserve. J Nucl Cardiol 2021;28:1906‐18.

    Article  PubMed  Google Scholar 

  44. Schindler TH. Myocardial blood flow: Putting it into clinical perspective. J Nucl Cardiol 2016;23:1056‐71.

    Article  PubMed  Google Scholar 

  45. Bateman TM, Dilsizian V, Beanlands RS, DePuey EG, Heller GV, Wolinsky DA. American Society of Nuclear Cardiology and Society of Nuclear Medicine and Molecular Imaging Joint Position Statement on the Clinical Indications for Myocardial Perfusion PET. J Nucl Med 2016;57:1654‐6.

    Article  PubMed  Google Scholar 

  46. Agostini D, Roule V, Nganoa C, Roth N, Baavour R, Parienti JJ, et al. First validation of myocardial flow reserve assessed by dynamic (99m)Tc-sestamibi CZT-SPECT camera: Head to head comparison with (15)O-water PET and fractional flow reserve in patients with suspected coronary artery disease. The WATERDAY study. Eur J Nucl Med Mol Imaging 2018;45:1079‐90.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  47. Liu FS, Wang SY, Shiau YC, Wu YW. Integration of quantitative absolute myocardial blood flow estimates from dynamic CZT-SPECT improves the detection of coronary artery disease. J Nucl Cardiol 2021. https://doi.org/10.1007/s12350-021-02713-8.

    Article  PubMed Central  PubMed  Google Scholar 

  48. Ford TJ, Ong P, Sechtem U, Beltrame J, Camici PG, Crea F, et al. Assessment of vascular dysfunction in patients without obstructive coronary artery disease: Why, how, and when. JACC Cardiovasc Interv 2020;13:1847‐64.

    Article  PubMed Central  PubMed  Google Scholar 

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Acknowledgments

Those who contributed to the work and meet the authorship criteria are listed as authors of the article. We also are indebted to the participants of this study.

Funding

This work was supported by Chinese National Natural Science Foundation (82170521), Shanghai Natural Science Foundation of China (21ZR1449500), Foundation of Shanghai Municipal Health Commission (202140263), the Fundamental Research Funds for Central Universities (NO.22120190211), Foundation of Chongming (CKY2021-21, CKY2020-29), and Clinical Research Plan of SHDC (SHDC2020CR4065).

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Correspondence to Xuejing Yu MD, PhD, Fuad A. Abdu MD, PhD, Fei Yu MD, PhD or Wenliang Che MD, PhD.

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Liu, L., Dai, N., Yin, G. et al. Prognostic value of combined coronary angiography-derived IMR and myocardial perfusion imaging by CZT SPECT in INOCA. J. Nucl. Cardiol. 30, 684–701 (2023). https://doi.org/10.1007/s12350-022-03038-w

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