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Review of cardiovascular imaging in the Journal of Nuclear Cardiology 2019: Single-photon emission computed tomography

  • REVIEW ARTICLE
  • Published:
Journal of Nuclear Cardiology Aims and scope

Abstract

In 2019, the Journal of Nuclear Cardiology published excellent articles pertaining to imaging in patients with cardiovascular disease. In this review, we will summarize a selection of these articles to provide a concise review of the main advancements that have recently occurred in the field and provide the reader with an opportunity to review a wide selection of articles. In the first article of this 2-part series, we focused on publications dealing with positron emission tomography, computed tomography, and magnetic resonance. This review will place emphasis on myocardial perfusion imaging using single-photon emission computed tomography summarizing advances in the field including in diagnosis and prognosis, non-perfusion variables, safety of testing, imaging in patients with heart failure and renal disease.

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Figure 1

Figure is reproduced with permission from Ref. 13.

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References

  1. AlJaroudi WA, Hage FG. Review of cardiovascular imaging in the Journal of Nuclear Cardiology 2018. Part 1 of 2: Positron emission tomography, computed tomography, and magnetic resonance. J Nucl Cardiol. 2019;26:524-35.

    PubMed  Google Scholar 

  2. Hage FG, AlJaroudi WA. Review of cardiovascular imaging in the Journal of Nuclear Cardiology in 2017. Part 2 of 2: Myocardial perfusion imaging. J Nucl Cardiol. 2018;25:1390-9.

    PubMed  Google Scholar 

  3. AlJaroudi WA, Hage FG. Review of cardiovascular imaging in the Journal of Nuclear Cardiology 2017. Part 1 of 2: Positron emission tomography, computed tomography, and magnetic resonance. J Nucl Cardiol. 2018;25:320-30.

    PubMed  Google Scholar 

  4. Hage FG, AlJaroudi WA. Review of cardiovascular imaging in the journal of nuclear cardiology in 2016: Part 2 of 2-myocardial perfusion imaging. J Nucl Cardiol. 2017;24:1190-9.

    PubMed  Google Scholar 

  5. AlJaroudi W, Hage FG. Review of cardiovascular imaging in the Journal of Nuclear Cardiology in 2016. Part 1 of 2: Positron emission tomography, computed tomography and magnetic resonance. J Nucl Cardiol. 2017;24:649-56.

    PubMed  Google Scholar 

  6. Hage FG, AlJaroudi WA. Review of cardiovascular imaging in the Journal of Nuclear Cardiology in 2015-Part 2 of 2: Myocardial perfusion imaging. J Nucl Cardiol. 2016;23:493-8.

    PubMed  Google Scholar 

  7. AlJaroudi WA, Hage FG. Review of cardiovascular imaging in the journal of nuclear cardiology in 2015. Part 1 of 2: Plaque imaging, positron emission tomography, computed tomography, and magnetic resonance. J Nucl Cardiol. 2016;23:122-30.

    PubMed  Google Scholar 

  8. Hage FG, AlJaroudi WA. Review of cardiovascular imaging in The Journal of Nuclear Cardiology in 2014: Part 2 of 2: Myocardial perfusion imaging. J Nucl Cardiol. 2015;22:714-9.

    PubMed  Google Scholar 

  9. AlJaroudi WA, Hage FG. Review of cardiovascular imaging in The Journal of Nuclear Cardiology in 2014: Part 1 of 2: Positron emission tomography, computed tomography, and neuronal imaging. J Nucl Cardiol. 2015;22:507-12.

    PubMed  Google Scholar 

  10. Shaw LJ, Hage FG, Berman DS, Hachamovitch R, Iskandrian A. Prognosis in the era of comparative effectiveness research: where is nuclear cardiology now and where should it be? J Nucl Cardiol. 2012;19:1026-43.

    PubMed  Google Scholar 

  11. Haro Alonso D, Wernick MN, Yang Y, Germano G, Berman DS, Slomka P. Prediction of cardiac death after adenosine myocardial perfusion SPECT based on machine learning. J Nucl Cardiol. 2019;26:1746-54.

    PubMed  Google Scholar 

  12. Shrestha S, Sengupta PP. Machine learning for nuclear cardiology: The way forward. J Nucl Cardiol. 2019;26:1755-8.

    PubMed  Google Scholar 

  13. Morales DCV, Bhavnani SP, Ahlberg AW, Pullatt RC, Katten DM, Polk DM, et al. Coronary risk equivalence of diabetes assessed by SPECT-MPI. J Nucl Cardiol. 2019;26:1093-102.

    PubMed  Google Scholar 

  14. Naqvi SY, Wittlin SD, Schwartz RG. Refining risk in diabetes and CAD with SPECT MPI: New insights and future challenges. J Nucl Cardiol. 2019;26:1103-6.

    PubMed  Google Scholar 

  15. Barone-Rochette G, Zoreka F, Djaileb L, Piliero N, Calizzano A, Quesada JL, et al. Diagnostic value of stress thallium-201/rest technetium-99m-sestamibi sequential dual isotope high-speed myocardial perfusion imaging for the detection of haemodynamically relevant coronary artery stenosis. J Nucl Cardiol. 2019;26:1269-79.

    PubMed  Google Scholar 

  16. Malhotra S, Doukky R. Dual isotope stress Tl-201 and rest Tc-99m CZT SPECT: Are we truly leveraging CZT technology? J Nucl Cardiol. 2019;26:1280-3.

    PubMed  Google Scholar 

  17. Levy AE, Shah NR, Matheny ME, Reeves RM, Gobbel GT, Bradley SM. Determining post-test risk in a national sample of stress nuclear myocardial perfusion imaging reports: Implications for natural language processing tools. J Nucl Cardiol. 2019;26:1878-85.

    PubMed  Google Scholar 

  18. Wu E, Holly TA. Nuclear cardiology reporting: Leaving an impression. J Nucl Cardiol. 2019;26:1886-7.

    PubMed  Google Scholar 

  19. Oddstig J, Martinsson E, Jogi J, Engblom H, Hindorf C. Differences in attenuation pattern in myocardial SPECT between CZT and conventional gamma cameras. J Nucl Cardiol. 2019;26:1984-91.

    PubMed  Google Scholar 

  20. Moncayo VM, Galt J. Attenuation correction in multipinhole-CZT gamma camera: Differences in attenuation pattern in myocardial SPECT between CZT and conventional gamma cameras. Oddstig J, Martinsson E, Jogi J, Engblom H, Hindorf C. J Nucl Cardiol. 2018. J Nucl Cardiol. 2019;26:1992-5.

    PubMed  Google Scholar 

  21. Kennedy JA, Brodov Y, Weinstein AL, Israel O, Frenkel A. The effect of CT-based attenuation correction on the automatic perfusion score of myocardial perfusion imaging using a dedicated cardiac solid-state CZT SPECT/CT. J Nucl Cardiol. 2019;26:236-45.

    PubMed  Google Scholar 

  22. Peters A, Kumar J, Patil PV. Diagnostic implications of CZT SPECT and impact of CT attenuation correction. J Nucl Cardiol. 2019;26:246-9.

    PubMed  Google Scholar 

  23. Song C, Yang Y, Ramon AJ, Wernick MN, Pretorius PH, Johnson KL, et al. Improving perfusion defect detection with respiratory motion correction in cardiac SPECT at standard and reduced doses. J Nucl Cardiol. 2019;26:1526-38.

    PubMed  Google Scholar 

  24. Scabbio C, Zoccarato O, Malaspina S, Lucignani G, Del Sole A, Lecchi M. Impact of non-specific normal databases on perfusion quantification of low-dose myocardial SPECT studies. J Nucl Cardiol. 2019;26:775-85.

    PubMed  Google Scholar 

  25. Liga R, Gimelli A. Automatic evaluation of myocardial perfusion on SPECT: Need for “Normality”. J Nucl Cardiol. 2019;26:786-9.

    PubMed  Google Scholar 

  26. Bagrova A, Alsamarah AY, Winchester DE. Comparing two methods for determining appropriateness of myocardial perfusion imaging: Criteria from the American College of Cardiology Foundation and the American College of Radiology. J Nucl Cardiol. 2019;26:826-30.

    PubMed  Google Scholar 

  27. Phillips LM, Shaw LJ. More or less appropriate: The new rule of law for cardiac imaging. J Nucl Cardiol. 2019;26:831-2.

    PubMed  Google Scholar 

  28. Bajaj NS, Singh S, Farag A, El-Hajj S, Heo J, Iskandrian AE, et al. The prognostic value of non-perfusion variables obtained during vasodilator stress myocardial perfusion imaging. J Nucl Cardiol. 2016;23:390-413.

    PubMed  Google Scholar 

  29. Christopoulos G, Bois J, Allison TG, Rodriguez-Porcel M, Chareonthaitawee P. The impact of combined cardiopulmonary exercise testing and SPECT myocardial perfusion imaging on downstream evaluation and management. J Nucl Cardiol. 2019;26:92-106.

    PubMed  Google Scholar 

  30. Holmes AA, Phillips LM. Cardiopulmonary exercise testing and SPECT myocardial perfusion imaging: Pre-test probability is the key. J Nucl Cardiol. 2019;26:107-8.

    PubMed  Google Scholar 

  31. Bateman TM, Lance Gould K, Di Carli MF. Proceedings of the Cardiac PET Summit, 12 May 2014, Baltimore, MD: 3: Quantitation of myocardial blood flow. J Nucl Cardiol. 2015;22:571-8.

    PubMed  Google Scholar 

  32. Iskandrian AE, Dilsizian V, Garcia EV, Beanlands RS, Cerqueira M, Soman P, et al. Myocardial perfusion imaging: Lessons learned and work to be done-update. J Nucl Cardiol. 2018;25:39-52.

    PubMed  Google Scholar 

  33. Yoshinaga K, Manabe O, Tamaki N. Absolute quantification of myocardial blood flow. J Nucl Cardiol. 2018;25:635-51.

    PubMed  Google Scholar 

  34. Sciammarella M, Shrestha UM, Seo Y, Gullberg GT, Botvinick EH. A combined static-dynamic single-dose imaging protocol to compare quantitative dynamic SPECT with static conventional SPECT. J Nucl Cardiol. 2019;26:763-71.

    PubMed  Google Scholar 

  35. deKemp RA, Wells RG, Ruddy TD. SPECT quantification of myocardial blood flow: A journey of a thousand miles begins with a single step (Lao Tzu, Chinese philosopher, 604-531 BC). J Nucl Cardiol. 2019;26:772-4.

    PubMed  Google Scholar 

  36. Bestetti A, Cuko B, Decarli A, Galli A, Lombardi F. Additional value of systolic wall thickening in myocardial stunning evaluated by stress-rest gated perfusion SPECT. J Nucl Cardiol. 2019;26:833-40.

    PubMed  Google Scholar 

  37. AlJaroudi WA, Hage FG. Myocardial stunning by gated SPECT: An old tool reinvented in a stunning turn. J Nucl Cardiol. 2019;26:841-4.

    PubMed  Google Scholar 

  38. Sillanmaki S, Lipponen JA, Tarvainen MP, Laitinen T, Hedman M, Hedman A, et al. Relationships between electrical and mechanical dyssynchrony in patients with left bundle branch block and healthy controls. J Nucl Cardiol. 2019;26:1228-39.

    PubMed  Google Scholar 

  39. Fudim M, Borges-Neto S. A troubled marriage: When electrical and mechanical dyssynchrony don’t go along. J Nucl Cardiol. 2019;26:1240-2.

    PubMed  Google Scholar 

  40. Farag AA, Heo J, Tauxe L, Bhambhvani P, Germano G, Kavanagh P, et al. Detection and quantitation of right ventricular reversible perfusion defects by stress SPECT myocardial perfusion imaging: A proof-of-principle study. J Nucl Cardiol. 2019;26:266-71.

    PubMed  Google Scholar 

  41. Sciagra R. Right ventricular perfusion: Do we need additional evidence or just a simple methodology? J Nucl Cardiol. 2019;26:272-4.

    PubMed  Google Scholar 

  42. Hage FG. Regadenoson for myocardial perfusion imaging: Is it safe? J Nucl Cardiol. 2014;21:871-6.

    PubMed  Google Scholar 

  43. Dilsizian V, Gewirtz H, Paivanas N, Kitsiou AN, Hage FG, Crone NE et al. Serious and potentially life threatening complications of cardiac stress testing: Physiological mechanisms and management strategies. J Nucl Cardiol 2015;22:1198-213; quiz 5-7.

  44. Abidov A, Dilsizian V, Doukky R, Duvall WL, Dyke C, Elliott MD, et al. Aminophylline shortage and current recommendations for reversal of vasodilator stress: An ASNC information statement endorsed by SCMR. J Nucl Cardiol. 2019;26:1007-14.

    PubMed  Google Scholar 

  45. Katsikis A, Theodorakos A, Papaioannou S, Kalkinis A, Kolovou G, Konstantinou K, et al. Adenosine stress myocardial perfusion imaging in octogenarians: Safety, tolerability, and long-term prognostic implications of hemodynamic response and SPECT-related variables. J Nucl Cardiol. 2019;26:250-62.

    PubMed  Google Scholar 

  46. Cliffe S, Reyes E. Adenosine MPS in octogenarians: Looking safely into the future. J Nucl Cardiol. 2019;26:263-5.

    PubMed  Google Scholar 

  47. Andrikopoulou E, Morgan CJ, Brice L, Bajaj NS, Doppalapudi H, Iskandrian AE, et al. Incidence of atrioventricular block with vasodilator stress SPECT: A meta-analysis. J Nucl Cardiol. 2019;26:616-28.

    PubMed  Google Scholar 

  48. Cho SG, Jabin Z, Bom HH. Safer stress tests for myocardial perfusion imaging. J Nucl Cardiol. 2019;26:629-32.

    PubMed  Google Scholar 

  49. He BJ, Malm BJ, Carino M, Sadeghi MM. Prevalence and variability in reporting of clinically actionable incidental findings on attenuation-correction CT scans in a veteran population. J Nucl Cardiol. 2019;26:1688-93.

    PubMed  Google Scholar 

  50. Port S. Incidental findings on hybrid SPECT-CT and PET-CT scanners: Is it time for new training and reporting guidelines? J Nucl Cardiol. 2019;26:1694-6.

    PubMed  Google Scholar 

  51. Wu D, Zhang Z, Ma R, Guo F, Wang L, Fang W. Comparison of CZT SPECT and conventional SPECT for assessment of contractile function, mechanical synchrony and myocardial scar in patients with heart failure. J Nucl Cardiol. 2019;26:443-52.

    PubMed  Google Scholar 

  52. Daou D. Dedicated cardiac CZT SPECT is steadily moving to achieve its destiny. J Nucl Cardiol. 2019;26:453-5.

    PubMed  Google Scholar 

  53. Hage FG, Aggarwal H, Patel K, Chen J, Jacobson AF, Heo J, et al. The relationship of left ventricular mechanical dyssynchrony and cardiac sympathetic denervation to potential sudden cardiac death events in systolic heart failure. J Nucl Cardiol. 2014;21:78-85.

    PubMed  Google Scholar 

  54. Yamamoto H, Yamada T, Tamaki S, Morita T, Furukawa Y, Iwasaki Y, et al. Prediction of sudden cardiac death in patients with chronic heart failure by regional washout rate in cardiac MIBG SPECT imaging. J Nucl Cardiol. 2019;26:109-17.

    PubMed  Google Scholar 

  55. Travin MI. Assessing arrhythmic risk with (123)I-mIBG and analogous tracers: Image interpretation from a different viewpoint. J Nucl Cardiol. 2019;26:118-22.

    PubMed  Google Scholar 

  56. Payne GA, Hage FG, Acharya D. Transplant allograft vasculopathy: Role of multimodality imaging in surveillance and diagnosis. J Nucl Cardiol. 2016;23:713-27.

    PubMed  Google Scholar 

  57. Veenis JF, Boiten HJ, van den Berge JC, Caliskan K, Maat A, Valkema R, et al. Prediction of long-term (> 10 year) cardiovascular outcomes in heart transplant recipients: Value of stress technetium-99m tetrofosmin myocardial perfusion imaging. J Nucl Cardiol. 2019;26:845-52.

    PubMed  Google Scholar 

  58. Acharya D, Rajapreyar I. Myocardial perfusion imaging for cardiac allograft vasculopathy assessment: Evidence grows, but questions remain. J Nucl Cardiol. 2019;26:853-6.

    PubMed  Google Scholar 

  59. Singh V, Falk R, Di Carli MF, Kijewski M, Rapezzi C, Dorbala S. State-of-the-art radionuclide imaging in cardiac transthyretin amyloidosis. J Nucl Cardiol. 2019;26:158-73.

    PubMed  Google Scholar 

  60. Dorbala S, Ando Y, Bokhari S, Dispenzieri A, Falk RH, Ferrari VA, et al. ASNC/AHA/ASE/EANM/HFSA/ISA/SCMR/SNMMI Expert Consensus Recommendations for Multimodality Imaging in Cardiac Amyloidosis: Part 1 of 2-Evidence Base and Standardized Methods of Imaging. J Card Fail. 2019;25:e1-39.

    PubMed  Google Scholar 

  61. Dorbala S, Ando Y, Bokhari S, Dispenzieri A, Falk RH, Ferrari VA, et al. ASNC/AHA/ASE/EANM/HFSA/ISA/SCMR/SNMMI expert consensus recommendations for multimodality imaging in cardiac amyloidosis: Part 2 of 2-diagnostic criteria and appropriate utilization. J Card Fail. 2019;25:854-65.

    PubMed  Google Scholar 

  62. Sperry BW, Gonzalez MH, Brunken R, Cerqueira MD, Hanna M, Jaber WA. Non-cardiac uptake of technetium-99m pyrophosphate in transthyretin cardiac amyloidosis. J Nucl Cardiol. 2019;26:1630-7.

    PubMed  Google Scholar 

  63. Rapezzi C, Gagliardi C, Milandri A. Analogies and disparities among scintigraphic bone tracers in the diagnosis of cardiac and non-cardiac ATTR amyloidosis. J Nucl Cardiol. 2019;26:1638-41.

    PubMed  Google Scholar 

  64. Hage FG, Smalheiser S, Zoghbi GJ, Perry GJ, Deierhoi M, Warnock D, et al. Predictors of survival in patients with end-stage renal disease evaluated for kidney transplantation. Am J Cardiol. 2007;100:1020-5.

    PubMed  Google Scholar 

  65. Doukky R, Fughhi I, Campagnoli T, Wassouf M, Ali A. The prognostic value of regadenoson SPECT myocardial perfusion imaging in patients with end-stage renal disease. J Nucl Cardiol. 2017;24:112-8.

    PubMed  Google Scholar 

  66. Nakamura S, Kawano Y, Nakajima K, Hase H, Joki N, Hatta T, et al. Prognostic study of cardiac events in Japanese patients with chronic kidney disease using ECG-gated myocardial Perfusion imaging: Final 3-year report of the J-ACCESS 3 study. J Nucl Cardiol. 2019;26:431-40.

    PubMed  Google Scholar 

  67. Tamaki N. Ischemia and inflammation on chronic kidney disease. J Nucl Cardiol. 2019;26:441-2.

    PubMed  Google Scholar 

  68. Andrikopoulou E, Hage FG. Heart rate response to regadenoson: Making the case for its value in clinical practice. J Nucl Cardiol. 2016;23:575-80.

    PubMed  Google Scholar 

  69. Hage FG, Dean P, Iqbal F, Heo J, Iskandrian AE. A blunted heart rate response to regadenoson is an independent prognostic indicator in patients undergoing myocardial perfusion imaging. J Nucl Cardiol. 2011;18:1086-94.

    PubMed  Google Scholar 

  70. Venkataraman R, Hage FG, Dorfman TA, Heo J, Aqel RA, de Mattos AM, et al. Relation between heart rate response to adenosine and mortality in patients with end-stage renal disease. Am J Cardiol. 2009;103:1159-64.

    CAS  PubMed  Google Scholar 

  71. Hage FG, Dean P, Bhatia V, Iqbal F, Heo J, Iskandrian AE. The prognostic value of the heart rate response to adenosine in relation to diabetes mellitus and chronic kidney disease. Am Heart J. 2011;162:356-62.

    CAS  PubMed  Google Scholar 

  72. Ives CW, AlJaroudi WA, Kumar V, Farag A, Rizk DV, Oparil S, et al. Prognostic value of myocardial perfusion imaging performed pre-renal transplantation: Post-transplantation follow-up and outcomes. Eur J Nucl Med Mol Imaging. 2018;45:1998-2008.

    PubMed  Google Scholar 

  73. AlJaroudi W, Anokwute C, Fughhi I, Campagnoli T, Wassouf M, Vij A, et al. The prognostic value of heart rate response during vasodilator stress myocardial perfusion imaging in patients with end-stage renal disease undergoing renal transplantation. J Nucl Cardiol. 2019;26:814-22.

    PubMed  Google Scholar 

  74. Topel M, Shaw LJ, Xie JX. Risk stratification for renal transplantation: A role for heart rate response? J Nucl Cardiol. 2019;26:823-5.

    PubMed  Google Scholar 

  75. Aggarwal H, AlJaroudi WA, Mehta S, Mannon R, Heo J, Iskandrian AE, et al. The prognostic value of left ventricular mechanical dyssynchrony using gated myocardial perfusion imaging in patients with end-stage renal disease. J Nucl Cardiol. 2014;21:739-46.

    PubMed  Google Scholar 

  76. Mori H, Isobe S, Suzuki S, Unno K, Morimoto R, Kano N, et al. Prognostic value of left ventricular dyssynchrony evaluated by gated myocardial perfusion imaging in patients with chronic kidney disease and normal perfusion defect scores. J Nucl Cardiol. 2019;26:288-97.

    PubMed  Google Scholar 

  77. Nakajima K, Okuda K, Matsuo S, Slomka P. Making the invisible visible: Phase dyssynchrony has potential as a new prognostic marker. J Nucl Cardiol. 2019;26:298-302.

    PubMed  Google Scholar 

  78. Crosland W, Aggarwal H, Farag A, Mehta S, Mannon RB, Heo J, et al. The effect of renal transplantation on left ventricular function, electrocardiography, and mechanical synchrony by gated myocardial perfusion imaging. J Nucl Cardiol. 2019;26:1962-70.

    PubMed  Google Scholar 

  79. Marie PY, Rossignol P. Stress myocardial perfusion gated-SPECT imaging in advanced chronic kidney disease. J Nucl Cardiol. 2019;26:1971-3.

    PubMed  Google Scholar 

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Disclosure

Dr. Hage reports research grant support from Astellas Pharma and GE Healthcare. Dr. AlJaroudi reports no disclosures.

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Authors and Affiliations

  1. Division of Cardiovascular Disease, Department of Medicine, University of Alabama at Birmingham, Lyons Harrison Research Building 306, 1900 University BLVD, Birmingham, AL, 35294, USA

    Fadi G. Hage MD, FAHA, FACC, MASNC

  2. Section of Cardiology, Birmingham Veterans Affairs Medical Center, Birmingham, AL, USA

    Fadi G. Hage MD, FAHA, FACC, MASNC

  3. Division of Cardiovascular Medicine, Clemenceau Medical Center, Beirut, Lebanon

    Wael A. AlJaroudi MD, FASNC

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  1. Fadi G. Hage MD, FAHA, FACC, MASNC
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Correspondence to Fadi G. Hage MD, FAHA, FACC, MASNC.

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Hage, F.G., AlJaroudi, W.A. Review of cardiovascular imaging in the Journal of Nuclear Cardiology 2019: Single-photon emission computed tomography. J. Nucl. Cardiol. 27, 1171–1179 (2020). https://doi.org/10.1007/s12350-020-02167-4

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