Skip to main content
SpringerLink
Log in

The Cardiorenal Axis: Myocardial Perfusion, Metabolism, and Innervation

  • Nuclear Cardiology (V Dilsizian, Section Editor)
  • Published:
Current Cardiology Reports Aims and scope Submit manuscript

Abstract

Purpose of the Review

Cardiorenal syndrome (CRS), defined as concomitant heart and kidney disease, has been a focus of attention for nearly a decade. As more patients survive severe acute and chronic heart and kidney diseases, CRS has emerged as an “epidemic” of modern medicine. Significant advances have been made in unraveling the complex mechanisms that underlie CRS based on classification of the condition into five pathophysiologic subtypes. In types 1 and 2, acute or chronic heart disease results in renal dysfunction, while in types 3 and 4, acute or chronic kidney diseases are the inciting factors for heart disease. Type 5 CRS is defined as concomitant heart and kidney dysfunction as part of a systemic condition such as sepsis or autoimmune disease.

Recent Findings

There are ongoing efforts to better define subtypes of CRS based on historical information, clinical manifestations, laboratory data (including biomarkers), and imaging characteristics. Systematic evaluation of CRS by advanced cardiac imaging, however, has been limited in scope and mostly focused on type 4 CRS. This is in part related to lack of clinical trials applying advanced cardiac imaging in the acute setting and exclusion of patients with significant renal disease from studies of such techniques in chronic HF.

Summary

Advanced cardiac nuclear imaging is well poised for assessment of the pathophysiology of CRS by offering a myriad of molecular probes without the need for nephrotoxic contrast agents. In this review, we examine the current or potential future application of advanced cardiac imaging to evaluation of myocardial perfusion, metabolism, and innervation in patients with CRS.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Abbreviations

AKI:

Acute kidney injury

BMIPP:

β-Methyl-p-[123I]-iodophenyl-pentadecanoic acid

CAD:

Coronary artery disease

CKD:

Chronic kidney disease

CRS:

Cardiorenal syndrome

ESRD:

End-stage renal disease

FDG:

2-Deoxy-2-18Ffluoro-d-glucose

GFR:

Glomerular filtration rate

HF:

Heart failure

HMR:

Heart-to-mediastinal ratio

LV:

Left ventricle (ventricular)

mIBG:

Meta-iodobenzylguanidine

MPI:

Myocardial perfusion imaging

PET:

Positron emission tomography

RAAS:

Renin angiotensin aldosterone system

SNS:

Sympathetic nervous system

SPECT:

Single photon emission computed tomography

WR:

Washout rate

References

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

  1. Mensah GA, Wei GS, Sorlie PD, Fine LJ, Rosenberg Y, Kaufmann PG, et al. Decline in cardiovascular mortality: possible causes and implications. Circ Res. 2017;120:366–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Dunlay SM, Roger VL. Understanding the epidemic of heart failure: past, present, and future. Curr Heart Fail Rep. 2014;11:404–15.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Mentz RJ, Kelly JP, von Lueder TG, Voors AA, Lam CS, Cowie MR, et al. Noncardiac comorbidities in heart failure with reduced versus preserved ejection fraction. J Am Coll Cardiol. 2014;64:2281–93.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Tsao CW, Lyass A, Enserro D, Larson MG, Ho JE, Kizer JR, et al. Temporal trends in the incidence of and mortality associated with heart failure with preserved and reduced ejection fraction. JACC Heart Fail. 2018;6:678–85.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Conrad N, Judge A, Tran J, Mohseni H, Hedgecott D, Crespillo AP, et al. Temporal trends and patterns in heart failure incidence: a population-based study of 4 million individuals. Lancet. 2018;391:572–80.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Sharma A, Zhao X, Hammill BG, Hernandez AF, Fonarow GC, Felker GM, et al. Trends in noncardiovascular comorbidities among patients hospitalized for heart failure: insights from the Get With The Guidelines-Heart Failure Registry. Circ Heart Fail. 2018;11:e004646.

    PubMed  Google Scholar 

  7. Juillière Y, Venner C, Filippetti L, Popovic B, Huttin O, Selton-Suty C. Heart failure with preserved ejection fraction: a systemic disease linked to multiple comorbidities, targeting new therapeutic options. Arch Cardiovasc Dis. 2018: in press;111:766–81.

    Article  PubMed  Google Scholar 

  8. Conrad N, Judge A, Tran J, Mohseni H, Hedgecott D, Perez Crespillo A, et al. Temporal trends and patterns in heart failure incidence: a population-based study of 4 million individuals. Lancet. 2018;391:572–80.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Heywood JT, Fonarow GC, Costanzo MR, Mathur VS, Wigneswaran JR, Wynne J. High prevalence of renal dysfunction and its impact on outcome in 118,465 patients hospitalized with acute decompensated heart failure: a report from the ADHERE database. J Card Fail. 2007;13:422–30.

    Article  PubMed  Google Scholar 

  10. Stevens LA, Li S, Wang C, Huang C, Becker BN, Bomback AS, et al. Prevalence of CKD and comorbid illness in elderly patients in the United States: results from the Kidney Early Evaluation Program (KEEP). Am J Kidney Dis. 2010;55(suppl 2):S23–33.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Collins AJ, Foley RN, Chavers B, Gilbertson D, Herzog C, Ishani A, et al. US Renal Data System 2013 annual data report. Am J Kidney Dis. 2014;63(suppl 1):e1–e420.

    Google Scholar 

  12. House AA. Management of heart failure in advancing CKD: Core Curriculum 2018. Am J Kidney Dis. 2018;72:284–95.

    Article  PubMed  Google Scholar 

  13. House AA, Anand I, Bellomo R, Cruz D, Bobek I, Anker SD, et al. Definition and classification of cardio-renal syndromes: workgroup statements from the 7th ADQI Consensus Conference. Nephrol Dial Transplant. 2010;25:1416–20.

    Article  PubMed  Google Scholar 

  14. Brisco MA, Testani JM. Novel renal biomarkers to assess cardiorenal syndrome. Curr Heart Fail Rep. 2014;11:485–99.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. • Roncoa C, Di Lullob L. Cardiorenal Syndrome in western countries: epidemiology, diagnosis and management approaches. Kidney Dis (Basel). 2017;2:151–63 This is a comprehensive review of cardiorenal syndrome with examples of each type, epidemiology of the condition and discussion of diagnosis and management.

    Article  Google Scholar 

  16. Fonarow GC, Adams KF Jr, Abraham WT, Yancy CW, Boscardin WJ, ADHERE Scientific Advisory Committee, Study Group, and Investigators. Risk stratification for in-hospital mortality in acutely decompensated heart failure: classification and regression tree analysis. JAMA 2005;293:572–580.

  17. • Mavrakanas TA, Khattak A, Singh K, Charytan DM. Epidemiology and natural history of the cardiorenal syndromes in a cohort with echocardiography. Clin J Am Soc Nephrol. 2017;12:1624–33 This is a retrospective cohort study of adults who underwent transthoracic echocardiography between 2004 and 2014 used to derive the prevalence and natural history of various types of cardiorenal syndrome .

    Article  PubMed  PubMed Central  Google Scholar 

  18. • Harjola VP, Mullens W, Banaszewski M, Bauersachs J, Brunner-La Rocca HP, Chioncel O, et al. Organ dysfunction, injury and failure in acute heart failure: from pathophysiology to diagnosis and management. A review on behalf of the acute heart failure Committee of the Heart Failure Association (HFA) of the European Society of Cardiology (ESC). Eur J Heart Fail. 2017;19:821–36 This is an authoritative and informative review of the current understanding of the presentation and management of concurrent organ impairment, including kidney dysfunction, in acute heart failure.

    Article  PubMed  Google Scholar 

  19. Gnanaraj J, von Haehling S, Anker SD, Raj DS, Radhakrishnan J. The relevance of congestion in the cardio-renal syndrome. Kidney Int. 2013;83:384–91.

    Article  CAS  Google Scholar 

  20. Nohria A, Hasselblad V, Stebbins A, Pauly DF, Fonarow GC, Shah M, et al. Cardio-renal interactions: insights from the ESCAPE trial. J Am Coll Cardiol. 2008;51:1268–74.

    Article  PubMed  Google Scholar 

  21. Damman K, van Deursen VM, Navis G, Voors AA, van Veldhuisen DJ, Hillege HL. Increased central venous pressure is associated with impaired renal function and mortality in a broad spectrum of patients with cardiovascular disease. J Am Coll Cardiol. 2009;53:582–8.

    Article  PubMed  Google Scholar 

  22. Anand IS, Greenberg BH, Katra RP, Fogoros RN, Libbus I, Katra RP, et al. Design of the Multi-Sensor Monitoring in Congestive HF (MUSIC) study: prospective trial to assess the utility of continuous wireless physiologic monitoring in heart failure. J Card Fail. 2011;17:11–6.

    Article  PubMed  Google Scholar 

  23. •• Puzzovivo A, Monitillo F, Guida P, Leone M, Rizzo C, Grande D, et al. Renal venous pattern: a new parameter for predicting prognosis in heart failure outpatients. J Cardiovasc Dev Dis. 2018;5:E52 This is an insightful study that demonstrates the significance of renal congestion in predicting progression of heart failure and characterization of cardiorenal syndrome through the eyes of renal vein Doppler pattern.

    Article  PubMed  Google Scholar 

  24. Cruz DN, Fard A, Clementi A, Ronco C, Maisel A. Role of biomarkers in the diagnosis and management of cardio-renal syndromes. Semin Nephrol. 2012;32:79–92.

    Article  CAS  PubMed  Google Scholar 

  25. Shirani J, Singh A, Agrawal S, Dilsizian V. Cardiac molecular imaging to track left ventricular remodeling in heart failure. J Nucl Cardiol. 2017;24:574–90.

    Article  PubMed  Google Scholar 

  26. Shirani J, Narula J, Eckelman WC, Narula N, Dilsizian V. Early imaging in heart failure: exploring novel molecular targets. J Nucl Cardiol. 2007;14:100–10.

    Article  PubMed  Google Scholar 

  27. Konstantinidis K, Whelan RS, Kitsis RN. Mechanisms of cell death in heart disease. Arterioscler Thromb Vasc Biol. 2012;32:1552–62.

    Article  CAS  PubMed  Google Scholar 

  28. Mohammed SF, Hussain S, Mirzoyev SA, Edwards WD, Maleszewski JJ, Redfield MM. Coronary microvascular rarefaction and myocardial fibrosis in heart failure with preserved ejection fraction. Circulation. 2015;131:550–9.

    Article  PubMed  Google Scholar 

  29. Zhang DY, Anderson AS. The sympathetic nervous system and heart failure. Cardiol Clin. 2014;32:33–45.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Sayer G, Bhat G. The renin-angiotensin-aldosterone system and heart failure. Cardiol Clin. 2014;32:21–32.

    Article  PubMed  Google Scholar 

  31. McCullough PA, Kellum JA, Mehta RL, Murray PT, Ronco C. ADQI consensus on AKI biomarkers and cardiorenal syndromes. Contrib Nephrol. 2013;182:82–98.

    Article  PubMed  Google Scholar 

  32. Preeti J, Alexandre M, Pupalan I, Merlin TC, Claudio R. Chronic heart failure and comorbid renal dysfunction—a focus on type 2 cardiorenal syndrome. Curr Cardiol Rev. 2016;12:186–94.

    Article  PubMed  PubMed Central  Google Scholar 

  33. •• Fu S, Zhao S, Ye P, Luo L. Biomarkers in cardiorenal syndromes. Biomed Res Int. 2018:9617363 This is a comprehensive review of established and possibly useful biomarkers that are predictive of heart failure and renal diseases with a potential for identifying cardiac dysfunction in renal diseases and renal injury in heart failure.

  34. Clementi A, Virzì GM, Brocca A, de Cal M, Pastori S, Clementi M, et al. Advances in the pathogenesis of cardiorenal syndrome type 3. Oxidative Med Cell Longev. 2015;2015:148082.

    Article  CAS  Google Scholar 

  35. Petrucci I, Clementi A, Sessa C, Torrisi I, Meola M. Ultrasound and color Doppler applications in chronic kidney disease. J Nephrol. 2018;31:863–79.

    Article  PubMed  Google Scholar 

  36. Zoccali C, Vanholder R, Massy ZA, Ortiz A, Sarafidis P, Dekker FW, Fliser D, Fouque D, Heine GH, Jager KJ, Kanbay M, Mallamaci F, Parati G, Rossignol P, Wiecek A, London G; European Renal and Cardiovascular Medicine (EURECA-m) Working Group of the European Renal Association - European Dialysis Transplantation Association (ERA-EDTA). The systemic nature of CKD. Nat Rev Nephrol 2017;13:344–358.

    Article  PubMed  Google Scholar 

  37. Roberts WC, Taylor MA, Shirani J. Cardiac findings at necropsy in patients with chronic kidney disease maintained on chronic hemodialysis. Medicine (Baltimore). 2012;91:165–78.

    Article  Google Scholar 

  38. Bhatti NK, Karimi GK, Paz Y, Nazif T, Moses JW, Leon MB, et al. Diagnosis and management of cardiovascular disease in advanced and end-stage renal disease. J Am Heart Assoc. 2016;5:e003648.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Stromp TA, Spear TJ, Holtkamp RM, Andres KN, Kaine JC, Alghuraibawi WH, et al. Quantitative gadolinium-free cardiac fibrosis imaging in end stage renal disease patients reveals a longitudinal correlation with structural and functional decline. Sci Rep. 2018;8:16972.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Mehta RL, Rabb H, Shaw AD, Singbartl K, Ronco C, McCullough PA, et al. Cardiorenal syndrome type 5: clinical presentation, pathophysiology and management strategies from the eleventh consensus conference of the acute dialysis quality initiative (ADQI). Contrib Nephrol. 2013;182:174–94.

    Article  PubMed  Google Scholar 

  41. Lekawanvijit S. Cardiotoxicity of uremic toxins: a driver of cardiorenal syndrome. Toxins (Basel). 2018;10:E352.

    Article  CAS  Google Scholar 

  42. Russo D, Corrao S, Miranda I, Ruocco C, Manzi S, Elefante R, et al. Progression of coronary artery calcification in predialysis patients. Am J Nephrol. 2007;27:152–8.

    Article  PubMed  Google Scholar 

  43. Schwarz U, Buzello M, Ritz E, Stein G, Raabe G, Wiest G, et al. Morphology of coronary atherosclerotic lesions in patients with end-stage renal failure. Nephrol Dial Transplant. 2000;15:218–23.

    Article  CAS  PubMed  Google Scholar 

  44. Amann K. Media calcification and intima calcification are distinct entities in chronic kidney disease. Clin J Am Soc Nephrol. 2008;3:1599–605.

    Article  PubMed  Google Scholar 

  45. •• Moody WE, Lin EL, Stoodley M, McNulty D, Thomson LE, Berman DS, et al. Prognostic utility of calcium scoring as an adjunct to stress myocardial perfusion scintigraphy in end-stage renal disease. Am J Cardiol. 2016;117:1387–96 This study showed that coronary artery calcium score does not have an incremental value to myocardial perfusion imaging for prediction of adverse cardiac outcomes in renal transplant candidates.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Wang LW, Fahim MA, Hayen A, Mitchell RL, Lord SW, Baines LA, et al. Cardiac testing for coronary artery disease in potential kidney transplant recipients: a systematic review of test accuracy studies. Am J Kidney Dis. 2011;57:476–87.

    Article  PubMed  Google Scholar 

  47. Herzog CA, Natwick T, Li S, Charytan DM. Comparative utilization and temporal trends in cardiac stress testing in U.S. medicare beneficiaries with and without chronic kidney disease. JACC Cardiovasc Imaging 2018 [Epub ahead of print].

  48. Gewirtz H, Dilsizian V. Integration of quantitative PET absolute myocardial blood flow in the clinical management of coronary artery disease. Circulation. 2016;133:2180–96.

    Article  PubMed  Google Scholar 

  49. Dilsizian V, Chandrashekhar Y, Narula J. Quantitative PET myocardial blood flow: trust, but verify. JACC Cardiovasc Imaging. 2017;10:609–10.

    Article  PubMed  Google Scholar 

  50. Schindler TH, Dilsizian V. PET-determined hyperemic myocardial blood flow: further progress to clinical application. J Am Coll Cardiol. 2014;64:1476–8.

    Article  PubMed  Google Scholar 

  51. Dilsizian V. Transition from SPECT to PET myocardial perfusion imaging: a desirable change in nuclear cardiology to approach perfection. J Nucl Cardiol. 2016;23:337–8.

    Article  PubMed  Google Scholar 

  52. Dilsizian V, Bacharach SL, Beanlands SR, Bergmann SR, Delbeke D, Dorbala S, et al. ASNC imaging guidelines/SNMMI procedure standard for positron emission tomography (PET) nuclear cardiology procedures. J Nucl Cardiol. 2016;23:1187–226.

    Article  PubMed  Google Scholar 

  53. Golzar Y, Doukky R. Stress SPECT myocardial perfusion imaging in end-stage renal disease. Curr Cardiovasc Imaging Rep 2017;10:Epub 2017 Mar 18.

  54. •• Paz Y, Morgenstern R, Weinberg R, Chiles M, Bhatti N, Ali Z, et al. Relation of coronary flow reserve to other findings on positron emission tomography myocardial perfusion imaging and left heart catheterization in patients with end-stage renal disease being evaluated for kidney transplant. Am J Cardiol. 2017;120:1909–12 This prospective study demonstrated for the first time that abnormal coronary flow reserve as assessed by positron emission tomography myocardial perfusion imaging is frequently present in patients with end-stage renal disease and is independent of perfusion defects or obstructive coronary artery disease.

    Article  PubMed  Google Scholar 

  55. Fukushima K, Javadi MS, Higuchi T, Bravo PE, Chien D, Lautamäki R, et al. Impaired global myocardial flow dynamics despite normal left ventricular function and regional perfusion in chronic kidney disease: a quantitative analysis of clinical 82Rb PET/CT studies. J Nucl Med. 2012;53:887–8893.

    Article  PubMed  Google Scholar 

  56. Lodge MA, Braess H, Mahmood F, Suh JD, Englar N, Bacharach SL, et al. Developments in nuclear cardiology: transition from single photon emission computed tomography to positron emission tomography-computed tomography. J Invasive Cardiol. 2005;17:491–6.

    PubMed  Google Scholar 

  57. Dilsizian V, Taillefer R. Journey in evolution of nuclear cardiology: will there be another quantum leap with the F-18 labeled myocardial perfusion tracers? JACC Cardiovasc Imaging. 2012;5:1269–84.

    Article  PubMed  Google Scholar 

  58. Dilsizian V. Metabolic adaptation to myocardial ischemia: the role of fatty acid imaging. J Nucl Cardiol. 2007;14(Suppl 3):S97–9.

    Article  PubMed  Google Scholar 

  59. Tillisch J, Brunken R, Marshall R, Schwaiger M, Mandelkern M, Phelps M, et al. Reversibility of cardiac wall-motion abnormalities predicted by positron tomography. N Engl J Med. 1986;314:884–8.

    Article  CAS  PubMed  Google Scholar 

  60. Dilsizian V, Arrighi JA, Diodati JG, Quyyumi AA, Bacharach SL, Alavi K, et al. Myocardial viability in patients with chronic coronary artery disease: comparison of 99mTc-sestamibi with thallium reinjection and 18F-fluorodeoxyglucose. Circulation. 1994;89:578–87.

    Article  CAS  PubMed  Google Scholar 

  61. Srinivasan G, Kitsiou AN, Bacharach SL, Bartlett ML, Miller-Davis C, Dilsizian V. 18F-fluorodeoxyglucose single photon emission computed tomography: can it replace PET and thallium SPECT for the assessment of myocardial viability? Circulation. 1998;97:843–50.

    Article  CAS  PubMed  Google Scholar 

  62. Kitsiou AN, Bacharach SL, Bartlett ML, Srinivasan G, Summers RM, Quyyumi AA, et al. 13N-ammonia myocardial blood flow and uptake: relation to functional outcome of asynergic regions after revascularization. J Am Coll Cardiol. 1999;33:678–86.

    Article  CAS  PubMed  Google Scholar 

  63. Osterholt M, Sen S, Dilsizian V, Taegtmeyer H. Targeted metabolic imaging to improve the management of heart disease. JACC Cardiovasc Imaging. 2012;5:214–26.

    Article  PubMed  PubMed Central  Google Scholar 

  64. •• Sengupta PP, Kramer CM, Narula J, Dilsizian V. The potential of clinical phenotyping of heart failure with imaging biomarkers for guiding therapies: a focused update. JACC Cardiovasc Imaging. 2017;10:1056–71 This review presents potential application of advanced cardiac imaging in assessment of heart failure phenotype and as a guide to selecting specific and evidence-based treatment.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Gewirtz H, Dilsizian V. Myocardial viability: survival mechanisms and molecular imaging targets in acute and chronic ischemia. Circ Res. 2017;120:1197–212.

    Article  CAS  PubMed  Google Scholar 

  66. •• Fink JC, Lodge MA, Smith MF, Hinduja A, Brown J, Dinits-Pensy MY, et al. Pre-clinical myocardial metabolic alterations in chronic kidney disease. Cardiology. 2010;116:160–7 This original prospective study showed for the first time that a significant inverse correlation existed between myocardial glucose utilization and severity of kidney dysfunction that could not be explained by demographic factors or cardiac workload.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Amann K, Breitbach M, Ritz E, Mall G. Myocyte/capillary mismatch in the heart of uremic patients. J Am Soc Nephrol. 1998;9:1018–22.

    CAS  PubMed  Google Scholar 

  68. McIntyre CW, Burton JO, Selby NM, Leccisotti L, Korsheed S, Baker CS, et al. Hemodialysis-induced cardiac dysfunction is associated with an acute reduction in global and segmental myocardial blood flow. Clin J Am Soc Nephrol. 2008;3:19–26.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Dasselaar JJ, Slart RH, Knip M, Pruim J, Tio RA, McIntyre CW, et al. Haemodialysis is associated with a pronounced fall in myocardial perfusion. Nephrol Dial Transplant. 2009;24:604–10.

    Article  PubMed  Google Scholar 

  70. Assa S, Hummel YM, Voors AA, Kuipers J, Westerhuis R, de Jong PE, et al. Hemodialysis-induced regional left ventricular systolic dysfunction: prevalence, patient and dialysis treatment-related factors, and prognostic significance. Clin J Am Soc Nephrol. 2012;7:1615–23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Breidthardt T, Burton JO, Odudu A, Eldehni MT, Jefferies HJ, McIntyre CW. Troponin T for the detection of dialysis-induced myocardial stunning in hemodialysis patients. Clin J Am Soc Nephrol. 2012;7:1285–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Burton JO, Jefferies HJ, Selby NM, McIntyre CW. Hemodialysis-induced cardiac injury: determinants and associated outcomes. Clin J Am Soc Nephrol. 2009;4:914–20.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Dilsizian V, Bateman TM, Bergmann SR, Des Prez R, Magram M, Goodbody AE, et al. Metabolic imaging with β-methyl-ρ-[123I]-iodophenyl-pentadecanoic acid (BMIPP) identifies ischemic memory following demand ischemia. Circulation. 2005;112(14):2169–74.

    Article  PubMed  Google Scholar 

  74. Taegtmeyer H, Dilsizian V. Imaging myocardial metabolism and ischemic memory. Nat Clin Pract Card. 2008;5:S42–8.

    Article  CAS  Google Scholar 

  75. Dilsizian V. FDG uptake as a surrogate marker for antecedent ischemia. J Nucl Med. 2008;49:1909–11.

    Article  PubMed  Google Scholar 

  76. Dilsizian V, Fink JC. Deleterious effect of altered myocardial fatty acid metabolism in kidney disease. J Am Coll Cardiol. 2008;51:146–8.

    Article  CAS  PubMed  Google Scholar 

  77. Nishimura M, Hashimoto T, Kobayashi H, Fukuda T, Okino K, Yamamoto N, et al. Myocardial scintigraphy using a fatty acid analogue detects coronary artery disease in hemodialysis patients. Kidney Int. 2004;66:811–9.

    Article  PubMed  Google Scholar 

  78. Nishimura M, Murase M, Hashimoto T, Kobayashi H, Yamazaki S, Imai R, et al. Insulin resistance and impaired myocardial fatty acid metabolism in dialysis patients with normal coronary arteries. Kidney Int. 2006;69:553–9.

    Article  CAS  PubMed  Google Scholar 

  79. Nishimura M, Tsukamoto K, Hasebe N, Tamaki N, Kikuchi K, Ono T. Prediction of cardiac death in hemodialysis patients by myocardial fatty acid imaging. J Am Coll Cardiol. 2008;51:139–45.

    Article  CAS  PubMed  Google Scholar 

  80. Nishimura M, Tokoro T, Nishida M, Hashimoto T, Kobayashi H, Yamazaki S, et al. Myocardial fatty acid imaging identifies a group of hemodialysis patients at high risk for cardiac death after coronary revascularization. Kidney Int. 2008;74:513–20.

    Article  PubMed  Google Scholar 

  81. Moroi M, Tamaki N, Nishimura M, Haze K, Nishimura T, Kusano E, et al. Association between abnormal myocardial fatty acid metabolism and cardiac-derived death among patients undergoing hemodialysis: results from a cohort study in Japan. Am J Kidney Dis. 2013;61:466–75.

    Article  CAS  PubMed  Google Scholar 

  82. Nishimura M, Hashimoto T, Tamaki N, Kobayashi H, Ono T. Focal impairment in myocardial fatty acid imaging in the left anterior descending artery area, a strong predictor for cardiac death in hemodialysis patients without obstructive coronary artery disease. Eur J Nucl Med Mol Imaging. 2015;42:1612–21.

    Article  PubMed  PubMed Central  Google Scholar 

  83. Eckelman WC, Dilsizian V. Chemistry and biology of radiotracers that target changes in sympathetic and parasympathetic nervous system in heart disease. J Nucl Med. 2015;56:7S–10S.

    Article  CAS  PubMed  Google Scholar 

  84. Schwartz PJ, De Ferrari GM. Sympathetic-parasympathetic interaction in health and disease: abnormalities and relevance in heart failure. Heart Fail Rev. 2011;16:101–7.

    Article  PubMed  Google Scholar 

  85. Kishi T. Heart failure as an autonomic nervous system dysfunction. J Cardiol. 2012;59:117–22.

    Article  PubMed  Google Scholar 

  86. •• Jacobson AF, Senior R, Cerqueira MD, Wong ND, Thomas GS, Lopez VA, et al. Myocardial iodine-123 meta-iodobenzylguanidine imaging and cardiac events in heart failure. Results of the prospective ADMIRE-HF (AdreView Myocardial Imaging for Risk Evaluation in Heart Failure) study. J Am Coll Cardiol. 2010;55:2212–21 This is a pivotal study that lead to Federal Drug Administration’s approval of meta-iodobenzylguanidine imaging for risk stratification of patients with heart failure and reduced systolic function.

    Article  PubMed  Google Scholar 

  87. Dilsizian V, Chandrashekhar Y, Narula J. Introduction of new tests: low are the mountains, high the expectations. JACC Cardiovasc Imaging. 2010;3:117–9.

    Article  PubMed  Google Scholar 

  88. • Badarin FJ, Wimmer AP, Kennedy KF, Jacobson AF, Bateman TM. The utility of ADMIRE-HF risk score in predicting serious arrhythmic events in heart failure patients: Incremental prognostic benefit of cardiac 123I-mIBG scintigraphy. J Nucl Cardiol. 2014;21:756–62 This was a post-hoc evaluation of data from ADMIRE-HF that showed the utility of meta-iodobenzylguanidine imaging in predicting serious arrhythmic events in patients with heart failure and reduced systolic function.

    Article  PubMed  Google Scholar 

  89. Agostini D, Belin A, Amar MH, Darlas Y, Hamon M, Grollier G, et al. Improvement of cardiac neuronal function after carvedilol treatment in dilated cardiomyopathy: a 123I-MIBG scintigraphic study. J Nucl Med. 2000;41:845–51.

    CAS  PubMed  Google Scholar 

  90. Gerson MC, Craft LL, McGuire N, Suresh DP, Abraham WT, Wagoner LE. Carvedilol improves left ventricular function in heart failure patients with idiopathic dilated cardiomyopathy and a wide range of sympathetic nervous system function as measured by iodine 123 metaiodobenzylguanidine. J Nucl Cardiol. 2002;9:608–15.

    Article  PubMed  Google Scholar 

  91. Kasama S, Toyama T, Kumakura H, Takayama Y, Ichikawa S, Suzuki T, et al. Addition of valsartan to an angiotensin-converting enzyme inhibitor improves cardiac sympathetic nerve activity and left ventricular function in patients with congestive heart failure. J Nucl Med. 2003;44:884–90.

    CAS  PubMed  Google Scholar 

  92. Kasama S, Toyama T, Kumakura H, Takayama Y, Ichikawa S, Suzuki T, et al. Spironolactone improves cardiac sympathetic nerve activity and symptoms in patients with congestive heart failure. J Nucl Med. 2002;43:1279–85.

    CAS  PubMed  Google Scholar 

  93. Cha YM, Oh J, Miyazaki C, Hayes DL, Rea RF, Shen WK, et al. Cardiac resynchronization therapy upregulates cardiac autonomic control. J Cardiovasc Electrophysiol. 2008;19:1045–52.

    Article  PubMed  PubMed Central  Google Scholar 

  94. Drakos SG, Athanasoulis T, Malliaras KG, Terrovitis JV, Diakos N, Koudoumas D, et al. Myocardial sympathetic innervation and long-term left ventricular mechanical unloading. JACC Cardiovasc Imaging. 2010;3:64–70.

    Article  PubMed  Google Scholar 

  95. Nishioka SA, Martinelli Filho M, Brandão SC, Giorgi MC, Vieira ML, Costa R, et al. Cardiac sympathetic activity pre and post resynchronization therapy evaluated by 123I-MIBG myocardial scintigraphy. J Nucl Cardiol. 2007;14:852–9.

    Article  PubMed  Google Scholar 

  96. Nakajima K, Verschure DO, Okuda K, Verberne HJ. Standardization of (123)I-meta-iodobenzylguanidine myocardial sympathetic activity imaging: phantom calibration and clinical applications. Clin Transl Imaging. 2017;5(3):255–63.

    Article  PubMed  PubMed Central  Google Scholar 

  97. Kurata C, Wakabayashi Y, Shouda S, Okayama K, Yamamoto T, Ishikawa A, et al. Enhanced cardiac clearance of iodine-123-MIBG in chronic renal failure. J Nucl Med. 1995;36:2037–43.

    CAS  PubMed  Google Scholar 

  98. Kurata C, Uehara A, Sugi T, Ishikawa A, Fujita K, Yonemura K, et al. Cardiac autonomic neuropathy in patients with chronic renal failure on hemodialysis. Nephron. 2000;84:312–9.

    Article  CAS  PubMed  Google Scholar 

  99. Chrapko BE, Jaroszyński AJ, Głowniak A, Bednarek-Skublewska A, Załuska W, Ksiażek A. Iodine-123 metaiodobenzylguanidine myocardial imaging in haemodialysed patients asymptomatic for coronary artery disease: a preliminary report. Nucl Med Commun. 2011;32:515–21.

    Article  CAS  PubMed  Google Scholar 

  100. Noordzij W, Özyilmaz A, Glaudemans AWJM, Tio RA, Goet ER, Franssen CFM, et al. Investigation into cardiac sympathetic innervation during the commencement of haemodialysis in patients with chronic kidney disease. Eur Radiol Exp. 2017;1:24.

    Article  PubMed  PubMed Central  Google Scholar 

  101. Furuhashi T, Moroi M. Importance of renal function on prognostic value of cardiac iodine-123 metaiodobenzylguanidine scintigraphy. Ann Nucl Med. 2007;21:57–63.

    Article  CAS  PubMed  Google Scholar 

  102. Verschure DO, Somsen GA, van Eck-Smit BL, Verberne HJ. Renal function in relation to cardiac (123)I-MIBG scintigraphy in patients with chronic heart failure. Int J Mol Imaging. 2012;2012:434790.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  103. Doi T, Nakata T, Hashimoto A, Yuda S, Wakabayashi T, Kouzu H, et al. Cardiac mortality assessment improved by evaluation of cardiac sympathetic nerve activity in combination with hemoglobin and kidney function in chronic heart failure patients. J Nucl Med. 2012;53:731–40.

    Article  PubMed  Google Scholar 

  104. Kouzu H, Doi T, Kawamukai M, Nishida J, Mochizuki A, Muranaka A, et al. Prognostic value of cardiac sympathetic imaging with metaiodobenzylguanidine for the prediction of mortality in patients with cardiorenal syndrome. Circulation. 2018;124:A9393.

    Google Scholar 

  105. Matsunari I, Aoki H, Nomura Y, Takeda N, Chen WP, Taki J, et al. Iodine-123 metaiodobenzylguanidine imaging and carbon-11 hydroxyephedrine positron emission tomography compared in patients with left ventricular dysfunction. Circ Cardiovasc Imaging. 2010;3:595–603.

    Article  PubMed  Google Scholar 

  106. Dilsizian V, Eckelman WC. Myocardial blood flow and innervation measures from a single scan: an appealing concept but a challenging paradigm. J Nucl Med. 2015 Nov;56(11):1645–6.

    Article  PubMed  Google Scholar 

  107. Castano A, Haq M, Narotsky DL, Goldsmith J, Weinberg RL, Morgenstern R, et al. Multicenter study of planar technetium 99m pyrophosphate cardiac imaging: predicting survival for patients with ATTR cardiac amyloidosis. JAMA Cardiol. 2016;1:880–9.

    Article  PubMed  Google Scholar 

  108. Chen W, Dilsizian V. Molecular imaging of amyloidosis: will the heart be the next target after the brain? Curr Cardiol Rep. 2012;14(2):226–33.

    Article  PubMed  Google Scholar 

  109. Chen W, Ton VK, Dilsizian V. Clinical phenotyping of transthyretin cardiac amyloidosis with bone seeking radiotracers in heart failure with preserved ejection fraction. Curr Cardiol Rep. 2018;20(4):23.

    Article  PubMed  Google Scholar 

  110. Pilebro B, Arvidsson S, Lindqvist P, Sundström T, Westermark P, Antoni G, et al. Positron emission tomography (PET) utilizing Pittsburgh compound B (PIB) for detection of amyloid heart deposits in hereditary transthyretin amyloidosis (ATTR). J Nucl Cardiol. 2018;25:240–8.

    Article  PubMed  Google Scholar 

  111. Pilebro B, Arvidsson S, Lindqvist P, Sundström T, Westermark P, Antoni G, et al. (123)I-Labelled metaiodobenzylguanidine for the evaluation of cardiac sympathetic denervation in early stage amyloidosis. Eur J Nucl Med Mol Imaging. 2012;39:1609–17.

    Article  CAS  Google Scholar 

  112. Coutinho MC, Cortez-Dias N, Cantinho G, Conceição I, Oliveira A, Bordalo e Sá A, et al. Reduced myocardial 123-iodine metaiodobenzylguanidine uptake: a prognostic marker in familial amyloid polyneuropathy. Circ Cardiovasc Imaging. 2013;6(5):627–36.

    Article  PubMed  Google Scholar 

  113. Youssef G, Leung E, Mylonas I, Nery P, Williams K, Wisenberg G, et al. The use of 18F-FDG PET in the diagnosis of cardiac sarcoidosis: a systematic review and metaanalysis including the Ontario experience. J Nucl Med. 2012;53(2):241–8.

    Article  CAS  PubMed  Google Scholar 

  114. Blankstein R, Waller AH. Evaluation of known or suspected cardiac sarcoidosis. Circ Cardiovasc Imaging. 2016;9:e000867.

    Article  PubMed  Google Scholar 

  115. Tomberli B, Cecchi F, Sciagrà R, Berti V, Lisi F, Torricelli F, et al. Coronary microvascular dysfunction is an early feature of cardiac involvement in patients with Anderson-Fabry disease. Eur J Heart Fail. 2013;15:1363–73.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Cardiology, St. Luke’s University Health Network, Bethlehem, Ostrum Street, Bethlehem, PA, 18015, USA

    Jamshid Shirani & Srinidhi Meera

  2. Department of Diagnostic Radiology and Nuclear Medicine, The University of Maryland School of Medicine, Baltimore, MD, 21201, USA

    Vasken Dilsizian

Authors
  1. Jamshid Shirani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Srinidhi Meera
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Vasken Dilsizian
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jamshid Shirani.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection on Nuclear Cardiology

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shirani, J., Meera, S. & Dilsizian, V. The Cardiorenal Axis: Myocardial Perfusion, Metabolism, and Innervation. Curr Cardiol Rep 21, 60 (2019). https://doi.org/10.1007/s11886-019-1147-3

Download citation

  • Published:

  • DOI: https://doi.org/10.1007/s11886-019-1147-3

Keywords

Search

Navigation