Cardiovascular Engineering and Technology

, Volume 3, Issue 2, pp 179–193 | Cite as

Underestimation of Murine Cardiac Hemodynamics Using Invasive Catheters: Errors, Limitations, and Remedies

  • Christakis Constantinides
  • S. Angeli
  • F. Kossivas
  • P. Ktorides


This study confirms the existence and quantifies the magnitude of a compound bias error in the estimation of hemodynamic indices of global cardiac function from the use of invasive, miniature, commercially available catheters in mice. Correspondingly, a new catheter design alternative is proposed that minimizes underestimation errors of such indices, according to simulations using end-diastolic (ED) and end-systolic (ES) computational myocardial models. Computational surface and finite element ED and ES mouse cardiac left ventricular (LV) models were constructed from MR images from five C57BL/6J mice. A commercially available miniature catheter and a modified improve design were also developed and imported in XFdtd for simulation of the electric field excitation pattern in composite catheter-LV blood and myocardium models. Straight (ED) and bent (ES) catheter orientations were tested and global functional indices of hemodynamics were estimated. Comparison of ED and ES estimates from catheter simulations, and direct MRI quantification, shows mean underestimation errors from five C57BL/6J mice that range between −8.3 ± 52.9 and −68.9 ± 10.4%. Propagation of such errors for estimating stroke volume, cardiac output, and ejection fraction, yields compound errors (for the commercially available catheter), of the order of 85.4 ± 29.1, 182.3 ± 117.4, 132.9 ± 171.1%, respectively, assuming a catheter electric field threshold sensitivity of 5%. Elicited response improvements (peak amplitude and spatial extent) in the generated ED and ES electric fields are quantified to be 405% and 52% (3.8 vs. 2.5 mm at 1% electric field fall-off) in ED, and 934 and 80% in ES, for the new catheter, compared to the commercially available design. Significant reductions in absolute hemodynamic error estimates were computed (of the order of 4.8–60.8%) for the new catheter design based on the computational models of one of the studied C57BL/6J mice. Overall, implementation of the newly proposed design can be realized at a reduced cost, with manufacturing processes that do not deviate from the currently employed methods, thereby leading to significantly improved accuracies in the estimation of hemodynamic indices of cardiac function.


Mouse Cardiac catheterizations Hemodynamics Miniature catheters MRI Error bias 



Particular thanks are deserved to Dr. D. Perperidis for his help with the co-registration of the various mouse cardiac surface models, and to the Center for In Vivo Microscopy at Duke University Medical Center, USA for providing us with the MRI data. The work was partly funded by the Hellenic Bank grant “HEART” and by the Research Promotion Foundation grants on International collaboration STOXOS 0308/02 and TECHNOLOGY/0609(BE)/05.

Conflict of interest



  1. 1.
    Baan, J., E. T. van der velde, H. G. de Bruin, G. J. Smeenk, J. Koops, A. D. van Duk, D. Temmerman, J. Senden, and B. Buts. Continuous measurement of left ventricular volume in animals and humans by conductance catheter. Circulation 70(5):812–823, 1984.CrossRefGoogle Scholar
  2. 2.
    Bauer, R., G. A. MacGowan, A. Blain, K. Bushby, and V. Straub. Steroid treatment causes deterioration of myocardial function in the δ-sarcoglycan-deficient mouse model for dilated cardiomyopathy. Cardiovasc. Res. 79:652–661, 2008.CrossRefGoogle Scholar
  3. 3.
    Bucholz, E., K. Ghaghada, Y. Qi, S. Mukundan, and G. A. Johnson. Four-dimensional MR microscopy of the mouse heart using radial acquisition and liposomal gadolinium contrast agent. Magn. Reson. Med. 60:111–118, 2008.CrossRefGoogle Scholar
  4. 4.
    Bucholz, E., K. Ghaghada, Y. Qi, S. Mukundan, H. A. Rockman, and G. A. Johnson. Cardiovascular phenotyping of the mouse heart using a 4D radial acquisition and liposomal Gd-DTPA-BMA. Magn. Reson. Med. 63:979–987, 2010.CrossRefGoogle Scholar
  5. 5.
    Burger, H. C., and R. van Dongen. Specific electrical resistance of body tissues. Phys. Med. Biol. 5:431–437, 1961.CrossRefGoogle Scholar
  6. 6.
    Burkhoff, D., E. van der Velde, D. Kass, J. Baan, W. L. Maughan, and K. Sagawa. Accuracy of volume measurement by conductance catheter in isolated, ejecting canine hearts. Circulation 72(2):440–447, 1985.CrossRefGoogle Scholar
  7. 7.
    Constantinides, C., S. Angeli, and R. Mean. Murine cardiac hemodynamics following manganese administration under isoflurane anesthesia. Ann. Biomed. Eng. 39(11):2706–2720, 2011. doi: 10.1007/s10439-011-0367-5,2011.CrossRefGoogle Scholar
  8. 8.
    Constantinides, C., A. Angeli, and R. Mean. Murine cardiac catheterizations and hemodynamics: on the issue of parallel conductance. IEEE Trans. Biomed. Eng. 58(11):3260–3268, 2011.CrossRefGoogle Scholar
  9. 9.
    Constantinides, C., A. Aristocleous, A. Johnson, and D. Perperidis. Static and dynamic cardiac modeling: initial strides and results towards a quantitatively accurate mechanical heart model. Proceedings of the IEEE Society on Biomedical Imaging (SBI), Rotterdam, Netherlands, February 2009.Google Scholar
  10. 10.
    Epstein, F. H., Z. Yang, W. D. Gilson, S. S. Berr, C. M. Kramer, and B. A. French. MR tagging early after myocardial infarction in mice demonstrates contractile dysfunction in adjacent and remote regions. Magn. Reson. Med. 48(2):399–403, 2002.CrossRefGoogle Scholar
  11. 11.
    Feldman, M. D., Y. Mao, J. W. Valvano, J. A. Pearce, and G. L. Freeman. Development of a multifrequency conductance catheter-based system to determine LV function in mice. Am. J. Physiol. Heart Circ. Physiol. 279:H1411–H1420, 2000.Google Scholar
  12. 12.
    Frydrychowicz, A., M. Spindler, E. Rommel, G. Ertl, A. Haase, S. Neubauer, and F. Wiesmann. Functional assessment of isolated right heart failure by high resolution in vivo cardiovascular magnetic resonance in mice. J. Cardiovasc. Magn. Reson. 9:623–627, 2007.CrossRefGoogle Scholar
  13. 13.
    Gabriel, S., R. W. Lau, and C. Gabriel. The dielectric properties of biological tissues: II. Measurements in the frequency range 10 Hz to 20 GHz. Phys. Med. Biol. 41(11):2251–2269, 1996.CrossRefGoogle Scholar
  14. 14.
    Gabriel, S., R. W. Lau, and S. Gabriel. The dielectric properties of biological tissues: III. Parametric models for the dielectric spectrum of tissues. Phys. Med. Biol. 41(11):2271–2293, 1996.CrossRefGoogle Scholar
  15. 15.
    Georgakopoulos, D., and D. A. Kass. Estimation of parallel conductance by dual-frequency conductance catheter in mice. Am. J. Physiol. Heart Circ. Physiol. 279:H443–H450, 2000.Google Scholar
  16. 16.
    Georgakopoulos, D., and D. A. Kass. Minimal force-frequency modulation of inotropy and relaxation of in situ murine hearts. J. Physiol. 534(2):535–545, 2001.CrossRefGoogle Scholar
  17. 17.
    Georgakopoulos, D., W. Mitzner, C. H. Chen, B. J. Byrne, H. D. Millar, J. M. Hare, and D. A. Kass. In vivo murine left ventricular pressure-volume relations by miniaturized conductance micromanometry. Am. J. Physiol. Heart Circ. Physiol. 274(43):H1416–H1422, 1998.Google Scholar
  18. 18.
    Gopakumaran, B., J. H. Petre, B. Sturm, R. D. White, and P. A. Murray. Estimate of current leakage in left and right ventricular conductance volumetry using a dynamic finite element model. IEEE Trans. Biomed. Eng. 47(11):1476–1486, 2000.CrossRefGoogle Scholar
  19. 19.
    Guide for the Care and Use of Laboratory Animals. DHEW Publication No. (NIH) 85-23, Revised Office of Science and Health Reports, DRR/NIH, Bethesda, MD 20892, 1985.Google Scholar
  20. 20.
    Hoit, B. D. New Approaches to Phenotypic Analysis in Adult Mice. J. Mol. Cell. Cardiol. 33:27–35, 2001.CrossRefGoogle Scholar
  21. 21.
    Huges, I. G., and T. Hase. Measurements and Their Uncertainties: A Practical Guide to Modern Error Analysis. New York: Oxford University Press, pp. 43–44, 2010.Google Scholar
  22. 22.
    Joho, S., D. Ishizaka, R. Sievers, R. Foster, P. C. Simpson, and W. Grossman. Left ventricular pressure-volume relationship in conscious mice. Am. J. Physiol. Heart Circ. Physiol. 292:H369–H377, 2006.CrossRefGoogle Scholar
  23. 23.
    Oosterlinck, W., A. Vanderper, W. Flameng, and P. Herijgers. Glucose tolerance and left and ventricular pressure–volume relationships in frequently used mouse strains. J. Biomed. Biotechnol. 1–7:2011, 2011.Google Scholar
  24. 24.
    Pacher, P., T. Nagayama, P. Mukhopadhyay, S. Batkal, and D. A. Kass. Measurement of cardiac function using pressure–volume conductance catheter technique in mice and rats. Nat. Protoc. 3(9):1422–1434, 2008.CrossRefGoogle Scholar
  25. 25.
    Perperidis, D., E. Bucholz, G. A. Johnson, and C. Constantinides. Morphological studies of the murine heart based on probabilistic and statistical atlases. Comput. Med. Imaging Graphics 36:119–129, 2012.CrossRefGoogle Scholar
  26. 26.
    Porterfield, J. E., A. T. G. Kottam, K. Raghavan, D. Escobedo, J. T. Jenkins, E. R. Larson, R. J. Trevino, J. W. Valvano, J. A. Pearce, and M. D. Feldman. Dynamic correction for parallel conductance, Gp, and gain factor, α, in invasive murine left ventricular volume measurements. J. Appl. Physiol. 107:1693–1703, 2009.CrossRefGoogle Scholar
  27. 27.
    Raghavan, K., J. E. Porterfield, A. T. G. Kottam, M. D. Feldman, D. Escobedo, J. W. Valvano, and J. A. Pearce. Electrical conductivity and permittivity of murine myocardium. IEEE Trans. Biomed. Eng. 56(8):2044–2053, 2009.CrossRefGoogle Scholar
  28. 28.
    Reyes, M., G. L. Freeman, D. Escobedo, S. Lee, M. E. Steinhelper, and M. D. Feldman. Enhancement of contractility with sustained afterload in the intact murine heart. Circulation 107:2962–2968, 2003.CrossRefGoogle Scholar
  29. 29.
    Reyes, M., M. Steinhelper, J. Alvarez, D. Escobedo, J. A. Pearce, J. W. Valvano, B. Pollock, C. L. Wei, A. T. G. Kottam, D. Altman, S. Lee, S. Bailey, S. L. Thomsen, G. Freeman, and M. D. Feldman. Impact of physiologic variables and genetic background on myocardial frequency-resistivity relations in the intact beating murine heart. Am. J. Physiol. Heart Circ. Physiol. 291(4):H1659–H1669, 2006.CrossRefGoogle Scholar
  30. 30.
    Ross, A. J., Z. Yang, S. S. Berr, W. D. Gilson, W. C. Peterssen, J. N. Oshinski, and B. A. French. Serial MRI evaluation of cardiac structure and function in mice after reperfused myocardial infarction. Magn. Reson. Med. 47(6):1158–1168, 2002.CrossRefGoogle Scholar
  31. 31.
    Ruff, J., F. Wiesmann, K. H. Hiller, S. Voll, M. von Kienlin, W. R. Bauer, E. Rommel, S. Neubauer, and A. Haase. Magnetic resonance microimaging for noninvasive quantification of myocardial function and mass in the mouse. Magn. Reson. Med. 40:43–48, 1998.CrossRefGoogle Scholar
  32. 32.
    Segers, P., D. Georgakopoulos, M. Afanasyeva, H. C. Champion, D. P. Judge, H. D. Millar, P. Verdonck, D. A. Kass, N. Stergiopoulos, and N. Westerhof. Conductance catheter-based assessment of arterial input impedance, arterial function, and ventricular-vascular interaction in mice. Am. J. Physiol. Heart Circ. Physiol. 288:H1157–H1164, 2005.CrossRefGoogle Scholar
  33. 33.
    Shioura, K., D. L. Geenen, and P. H. Goldspink. Assessment of cardiac function with the pressure–volume conductance system following myocardial infarction in mice. Am. J. Physiol. Heart Circ. Physiol. 293:H2870–H2877, 2007.CrossRefGoogle Scholar
  34. 34.
    Shioura, K., D. L. Geenen, and P. H. Goldspink. Sex-related changes in cardiac function following myocardial infarction in mice. Am. J. Physiol. Regul. Integr. Comp. Physiol. 295:R528–R534, 2008.CrossRefGoogle Scholar
  35. 35.
    Staal, E. M., P. Steendijk, and J. Baan. The trans-cardiac conductance method for on-line measurement of left ventricular volume: assessment of parallel conductance offset volume. IEEE Trans. Biomed. Eng. 50(2):234–240, 2003.CrossRefGoogle Scholar
  36. 36.
    Tjon-A-Meeuw, L., O. M. Hess, H. Nonogi, E. S. Monrad, B. Leskosek, and H. P. Krayenbuehl. Left ventricular volume determination in dogs: a comparison between conductance technique and angiocardiography. Eur. Heart J. 9:1018–1026, 1988.Google Scholar
  37. 37.
    Wei, C., J. W. Valvano, M. D. Feldman, M. Nahrendorf, R. Peshock, and J. A. Pearce. Volume catheter parallel conductance varies between end-systole and end-diastole. IEEE Trans. Biomed. Eng. 54(8):1480–1489, 2007.CrossRefGoogle Scholar
  38. 38.
    White, P. A., C. I. O. Brookes, H. B. Ravn, E. E. Stenbog, T. D. Christensen, R. R. Chaturvedi, K. Sorensen, V. E. Hjortdal, and A. N. Redington. The effect of changing excitation frequency on parallel conductance in different sized hearts. Cardiovasc. Res. 28:668–675, 1998.CrossRefGoogle Scholar
  39. 39.
    Wiesmann, F., J. Ruff, S. Engelhardt, L. Hein, C. Dienesch, A. Leupold, R. Illinger, A. Frydrychowicz, K. H. Hiller, E. Rommel, A. Haase, M. J. Lohse, and S. Neubauer. Dobutamine-stress Magnetic Resonance Microimaging in mice: acute changes of cardiac geometry and function in normal and failing murine hearts. Circ. Res. 88(6):550–551, 2001.Google Scholar
  40. 40.
    Yang, B., D. F. Larson, and R. Watson. Age-related left ventricular function in the mouse: analysis based on in vivo pressure–volume relationships. Am. J. Physiol. Heart Circ. Physiol. 277(5):H1906–H1913, 1999.Google Scholar
  41. 41.
    Zhang, W., M. ten Hove, J. E. Schneider, D. J. Stuckey, L. Sebag-Montefiore, B. L. Bia, G. K. Radda, K. E. Davies, S. Neubauer, and K. Clarke. Abnormal cardiac morphology, function and energy metabolism in the dystrophic mdx mouse: an MRI and MRS study. J. Mol. Cell. Cardiol. 45(6):754–760, 2008.CrossRefGoogle Scholar

Copyright information

© Biomedical Engineering Society 2012

Authors and Affiliations

  • Christakis Constantinides
    • 1
  • S. Angeli
    • 1
  • F. Kossivas
    • 1
  • P. Ktorides
    • 1
  1. 1.Laboratory of Physiology and Biomedical Imaging, Department of Mechanical and Manufacturing Engineering, School of EngineeringUniversity of CyprusCyprusNicosia

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