Skip to main content

Advertisement

SpringerLink
Log in

Animal Models in Cardiovascular MRI Research: Value and Limitations

  • Cardiac Magnetic Resonance (E Nagel, Section Editor)
  • Published:
Current Cardiovascular Imaging Reports Aims and scope Submit manuscript

Abstract

This review will explore the interface between MRI, cardiovascular research, and animal models, with particular attention to values, limitations, and best practices. This includes the question of whether an animal model may be necessary or appropriate. Factors influencing the selection of small versus large animal models will be considered, including the features that distinguish mice from other animal models. MRI has proven extremely useful in studies of basic cardiovascular physiology, but its true utility lies in the acquisition of end points relevant to cardiovascular disease in preclinical and clinical investigations. Brief summaries will be presented of the many anatomic and functional parameters that can be assessed by cardiovascular MRI, along with its role in translational medicine. Finally, the predictive value and clinical relevance of animal models of cardiovascular disease will be explored, including steps that are recommended to maximize the predictive value of animal models in translational medicine.

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

Similar content being viewed by others

References

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

  1. Rogers Jr WJ, Shapiro EP, Weiss JL, Buchalter MB, Rademakers FE, Weisfeldt ML, et al. Quantification of and correction for left ventricular systolic long-axis shortening by magnetic resonance tissue tagging and slice isolation. Circulation. 1991;84(2):721–31.

    PubMed  Google Scholar 

  2. Mostbeck GH, Caputo GR, Higgins CB. MR measurement of blood flow in the cardiovascular system. AJR Am J Roentgenol. 1992;159(3):453–61.

    PubMed  CAS  Google Scholar 

  3. Bennett KM, Shapiro EM, Sotak CH, Koretsky AP. Controlled aggregation of ferritin to modulate MRI relaxivity. Biophys J. 2008;95(1):342–51.

    Article  PubMed  CAS  Google Scholar 

  4. Harrison GJ, Cerniway RJ, Peart J, Berr SS, Ashton K, Regan S, et al. Effects of A(3) adenosine receptor activation and gene knock-out in ischemic-reperfused mouse heart. Cardiovasc Res. 2002;53(1):147–55.

    Article  PubMed  CAS  Google Scholar 

  5. Schuster A, Grunwald I, Chiribiri A, Southworth R, Ishida M, Hay G, et al. An isolated perfused pig heart model for the development, validation and translation of novel cardiovascular magnetic resonance techniques. J Cardiovasc Magn Reson. 2010;12:53.

    Article  PubMed  Google Scholar 

  6. Goldberg AM, Zurlo J, Rudacille D. The three Rs and biomedical research. Science. 1996;272(5267):1403.

    Article  PubMed  CAS  Google Scholar 

  7. Carmeliet P, Collen D. Transgenic mouse models in angiogenesis and cardiovascular disease. J Pathol. 2000;190(3):387–405.

    Article  PubMed  CAS  Google Scholar 

  8. Epstein FH. MR in mouse models of cardiac disease. NMR Biomed. 2007;20(3):238–55.

    Article  PubMed  Google Scholar 

  9. Skarnes WC, Rosen B, West AP, Koutsourakis M, Bushell W, Iyer V, et al. A conditional knockout resource for the genome-wide study of mouse gene function. Nature. 2011;474(7351):337–42.

    Article  PubMed  CAS  Google Scholar 

  10. Initial sequencing and comparative analysis of the mouse genome. Nature. 2002;420(6915):520–62.

  11. Bockamp E, Sprengel R, Eshkind L, Lehmann T, Braun JM, Emmrich F, et al. Conditional transgenic mouse models: from the basics to genome-wide sets of knockouts and current studies of tissue regeneration. Regen Med. 2008;3(2):217–35.

    Article  PubMed  CAS  Google Scholar 

  12. Huang G, Ashton C, Kumbhani DS, Ying Q-L. Genetic manipulations in the rat: progress and prospects. Curr Opin Nephrol Hypertens. 2011;20(4):391–9.

    Article  PubMed  Google Scholar 

  13. Hasenfuss G. Animal models of human cardiovascular disease, heart failure and hypertrophy. Cardiovasc Res. 1998;39(1):60–76.

    Article  PubMed  CAS  Google Scholar 

  14. Decking UKM, Pai VM, Bennett E, Taylor JL, Fingas CD, Zanger K, et al. High-resolution imaging reveals a limit in spatial resolution of blood flow measurements by microspheres. Am J Physiol Heart Circ Physiol. 2004;287(3):H1132–40.

    Article  PubMed  CAS  Google Scholar 

  15. Lawton J, Cupps B, Knutsen A, Ma N, Brady B, Reynolds L, et al. Magnetic resonance imaging detects significant sex differences in human myocardial strain. Biomed Eng Online. 2011;10(76):1–11.

    Google Scholar 

  16. Spence AL, Naylor LH, Carter HH, Buck CL, Dembo L, Murray CP et al. A prospective randomised longitudinal MRI study of left ventricular adaptation to endurance and resistance exercise training in humans. J Physiol. 2011; Published online before print.

  17. Hockings P. Magnetic resonance imaging in pharmaceutical safety assessment. In: Vogel HG, editor. Drug discovery and evaluation: safety and pharmacokinetic assays. Berlin: Springer-Verlag; 2006. p. 385–408.

    Google Scholar 

  18. Franco F, Thomas GD, Giroir B, Bryant D, Bullock MC, Chwialkowski MC, et al. Magnetic resonance imaging and invasive evaluation of development of heart failure in transgenic mice with myocardial expression of tumor necrosis factor alpha. Circulation. 1999;99(3):448–54.

    PubMed  CAS  Google Scholar 

  19. Goetschalckx K, Rademakers F, Bogaert J. Right ventricular function by MRI. Curr Opin Cardiol. 2010;25(5):451–5.

    Article  PubMed  Google Scholar 

  20. Kuppahally SS, Akoum N, Burgon NS, Badger TJ, Kholmovski EG, Vijayakumar S, et al. Left atrial strain and strain rate in patients with paroxysmal and persistent atrial fibrillation / Clinical Perspective. Circ Cardiovasc Imaging. 2010;3(3):231–9.

    Article  PubMed  Google Scholar 

  21. Makowski M, Jansen C, Webb I, Chiribiri A, Nagel E, Botnar R, et al. First-pass contrast-enhanced myocardial perfusion MRI in mice on a 3-T clinical MR scanner. Magn Reson Med. 2010;64(6):1592–8.

    Article  PubMed  Google Scholar 

  22. Zun Z, Wong EC, Nayak KS. Assessment of myocardial blood flow (MBF) in humans using arterial spin labeling (ASL): Feasibility and noise analysis. Magn Reson Med. 2009;62(4):975–83.

    Article  PubMed  Google Scholar 

  23. Matheijssen NA, Baur LH, Reiber JH, van der Velde EA, van Dijkman PR, van der Geest RJ, et al. Assessment of left ventricular volume and mass by cine magnetic resonance imaging in patients with anterior myocardial infarction intra-observer and inter-observer variability on contour detection. Int J Card Imaging. 1996;12(1):11–9.

    Article  PubMed  CAS  Google Scholar 

  24. Bottini PB, Carr AA, Prisant LM, Flickinger FW, Allison JD, Gottdiener JS. Magnetic resonance imaging compared to echocardiography to assess left ventricular mass in the hypertensive patient. Am J Hypertens. 1995;8(3):221–8.

    Article  PubMed  CAS  Google Scholar 

  25. Bellenger NG, Davies LC, Francis JM, Coats AJ, Pennell DJ. Reduction in sample size for studies of remodeling in heart failure by the use of cardiovascular magnetic resonance. J Cardiovasc Magn Reson. 2000;2(4):271–8.

    Article  PubMed  CAS  Google Scholar 

  26. Pfeffer JM, Pfeffer MA, Braunwald E. Influence of chronic captopril therapy on the infarcted left ventricle of the rat. Circ Res. 1985;57(1):84–95.

    PubMed  CAS  Google Scholar 

  27. Pfeffer MA, Lamas GA, Vaughan DE, Parisi AF, Braunwald E. Effect of captopril on progressive ventricular dilatation after anterior myocardial infarction. New Engl J Med. 1988;319(2):80–6.

    Article  PubMed  CAS  Google Scholar 

  28. Pfeffer MA, Braunwald E, Moya LA, Basta L, Brown EJ, Cuddy TE, et al. Effect of captopril on mortality and morbidity in patients with left ventricular dysfunction after myocardial infarction. N Eng J Med. 1992;327(10):669–77.

    Article  CAS  Google Scholar 

  29. Kloner RA, Forman MB, Gibbons RJ, Ross AM, Alexander RW, Stone GW. Impact of time to therapy and reperfusion modality on the efficacy of adenosine in acute myocardial infarction: the AMISTAD-2 trial. Eur Heart J. 2006;27(20):2400–5.

    Article  PubMed  CAS  Google Scholar 

  30. Maurer G. Adenosine as an adjunct to reperfusion in myocardial infarction. Eur Heart J. 2006;27(20):2376–7.

    Article  PubMed  Google Scholar 

  31. • Desmet W, Bogaert J, Dubois C, Sinnaeve P, Adriaenssens T, Pappas C, et al. High-dose intracoronary adenosine for myocardial salvage in patients with acute ST-segment elevation myocardial infarction. Eur Heart J. 2011;32(7):867–77. This report nicely illustrates the utility of combining T2-weighted and contrast-enhanced sequences to determine the myocardial salvage index for evaluating drug efficacy in the setting of acute MI.

    Article  PubMed  CAS  Google Scholar 

  32. • Danhof M, Alvan G, Dahl SG, Kuhlmann J, Paintaud G. Mechanism-based pharmacokinetic-pharmacodynamic modeling: a new classification of biomarkers. Pharmaceut Res. 2005;22(9):1432–7. This article proposes a new classification scheme for biomarkers and discusses their application in mechanism-based PK/PD analysis for drug discovery and development.

    Article  CAS  Google Scholar 

  33. Pitt B, Remme W, Zannad F, Neaton J, Martinez F, Roniker B, et al. Eplerenone, a selective aldosterone blocker, in patients with left ventricular dysfunction after myocardial infarction. N Eng J Med. 2003;348(14):1309–21.

    Article  CAS  Google Scholar 

  34. •• van der Worp HB, Howells DW, Sena ES, Porritt MJ, Rewell S, O’Collins V, et al. Can animal models of disease reliably inform human studies? PLoS Med. 2010;7(3):e1000245. This review addresses the controversy surrounding the value of animal models in predicting the effectiveness of novel therapies in human trials and proposes practical strategies to improve their predictive value.

    Article  PubMed  Google Scholar 

  35. Guerette B, Moisset PA, Huard C, Tardif F, Gravel C, Tremblay JP. Inflammatory damage following first-generation replication-defective adenovirus controlled by anti-LFA-1. J Leukoc Biol. 1997;61(4):533–8.

    PubMed  CAS  Google Scholar 

  36. Bodenheimer T. Uneasy alliance - clinical investigators and the pharmaceutical industry. N Eng J Med. 2000;342(20):1539–44.

    Article  CAS  Google Scholar 

  37. Horrobin DF. Innovation in the pharmaceutical industry. JRSM. 2000;93(7):341–5.

    CAS  Google Scholar 

  38. •• Paul SM, Mytelka DS, Dunwiddie CT, Persinger CC, Munos BH, Lindborg SR, et al. How to improve R&D productivity: the pharmaceutical industry’s grand challenge. Nat Rev Drug Discov. 2010;9(3):203–14. This review presents a detailed analysis of industry-wide data that characterizes the relative contributions of each step in the drug discovery/development pathway to overall productivity, then proposes specific strategies for improving that productivity.

    PubMed  CAS  Google Scholar 

  39. Kola I, Landis J. Can the pharmaceutical industry reduce attrition rates? Nat Rev Drug Discov. 2004;3(8):711–6.

    Article  PubMed  CAS  Google Scholar 

  40. Yang Y, Adelstein SJ, Kassis AI. Target discovery from data mining approaches. Drug Discov Today. 2009;14(3–4):147–54.

    Article  PubMed  Google Scholar 

  41. Rudy Y, Ackerman MJ, Bers DM, Clancy CE, Houser SR, London B, et al. Systems approach to understanding electromechanical activity in the human heart. Circulation. 2008;118(11):1202–11.

    Article  PubMed  Google Scholar 

  42. Phillips KA, Van Bebber S, Issa AM. Diagnostics and biomarker development: priming the pipeline. Nat Rev Drug Discov. 2006;5(6):463–9.

    Article  PubMed  CAS  Google Scholar 

Download references

Disclosure

The author acknowledges research support from the National Heart, Lung and Blood Institute of the NIH (R01 HL092305), the American Heart Association (09GRNT2261123) and AstraZeneca (AZ/UVA Strategic Alliance).

Author information

Authors and Affiliations

  1. Departments of Biomedical Engineering, Medicine, and Radiology, University of Virginia, Health Science Center, PO Box 800759, Charlottesville, VA, 22908, USA

    Brent A. French

Authors
  1. Brent A. French
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Brent A. French.

Rights and permissions

Reprints and permissions

About this article

Cite this article

French, B.A. Animal Models in Cardiovascular MRI Research: Value and Limitations. Curr Cardiovasc Imaging Rep 5, 99–108 (2012). https://doi.org/10.1007/s12410-012-9128-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12410-012-9128-6

Keywords

Search

Navigation