Assessment of spatial resolution of pace mapping when using body surface potentials

  • R. Hren
  • B. B. PunskeEmail author
  • G. Stroink


Using computer simulations and statistical methods, the resolution of pace mapping when used in combination with body surface potentials was systematically investigated. In an anatomical model of the human ventricular myocardium, pre-excitation sequences were initiated at 69 sites positioned along the atrioventricular (AV) ring and corresponding body surface potential maps (BSPMs) were calculated at 32 leads placed on the anterior torso. For each time after the onset of pre-excitation (every 4ms to 40ms) and each root-mean-square (RMS) noise level (5, 10, 20 and 50μV), BSPMs were cross-correlated and the spatial resolution defined as the largest pacing site separation at which the differences in correlation coefficients were not statistically significant (level p≥0.05). The findings indicate that when random RMS noise of 5μV was added to the simulated BSPMs, average spatial resolution over all 69 sites was at 20ms after the onset of pre-excitation within 3.5±0.9mm. The results provide theoretical evidence that statistical analysis of BSPMs obtained during pace mapping can offer improved means for subcentimetre identification of accessory pathways located along the AV ring.


Body surface potential mapping Spatial resolution Pace mapping Pre-excitation syndrome Computer model 


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  1. Dubuc, M., Nadeau, R., Tremblay, G., Kus, T., Molin, F., andSavard, P. (1993): ‘Pace mapping using body surface potential maps to guide catheter ablation of accessory pathways in patients with Wolff-Parkinson-White syndrome’,Circulation,87, pp. 135–143Google Scholar
  2. Green, L. S., Lux, R. L., Ershler, P. R., Freedman, R. A., Marcus, F. I., andGear, K. (1994): ‘Resolution of pace mapping stimulus site separation using body surface potentials’,Circulation,90, pp. 462–468Google Scholar
  3. Grogin, H. R., Stanley, M. L., Eisenberg, S. J., Horáček, B. M., andLesh, M. D. (1992): ‘Body surface mapping for localization of accessory pathways in WPW syndrome’,in Murray, A., andArzbaecher, R. (Eds). ‘Computers in Cardiology’ (IEEE Computer Society Press, Los Alamitos, CA), pp. 255–258CrossRefGoogle Scholar
  4. Horáček, B. M. (1974): ‘Numerical model of an inhomogeneous human torso’,Adv. Cardiol.,10, pp. 51–57Google Scholar
  5. Hren, R. (1998): ‘Value of epicardial potential maps in localizing pre-excitation sites for radiofrequency ablation: a simulation study’,Phys. Med. Biol.,43, pp. 1449–1468CrossRefGoogle Scholar
  6. Hren, R., andHoráček, B. M. (1997): ‘Value of simulated body surface potential maps as templates in localizing sites of ectopic activation for radiofrequency ablation’,Physiol. Meas.,18, pp. 373–400CrossRefGoogle Scholar
  7. Hren, R., Stroink, G., andHoráček, B. M. (1998a): ‘Spatial resolution of body surface potential maps and magnetic field maps: a simulation study applied to the identification of ventricular pre-excitation sites’,Med. Biol. Eng. Comput.,36, pp. 145–157CrossRefGoogle Scholar
  8. Hren, R., Nenonen, J., andHoráček, B. M. (1998b): ‘Simulated epicardial potential maps during paced activation reflect myocardial fibrous structure’,Ann. Biomed. Eng.,26, pp. 1022–1035CrossRefGoogle Scholar
  9. Leon, L. J., andHoráček, B. M. (1991): ‘Computer model of excitation and recovery in the anisotropic myocardium. I. Rectangular and cubic arrays of excitable element’,J. Electrocardiol.,24, pp. 1–15CrossRefGoogle Scholar
  10. Lux, R. L., Smith, C. R., Wyatt, R. F., andAbildskov, J. A. (1978): ‘Limited lead selection for estimation of body surface potential maps in electrocardiography’,IEEE Trans. Biomed. Eng.,BME-25, pp. 270–276CrossRefGoogle Scholar
  11. Lux, R. L. (1993): ‘Electrocardiographic mapping: noninvasive electrophysiological cardiac imaging’,Circulation,87, pp. 1040–1042Google Scholar
  12. Molin, F., Savard, P., Dubuc, M., Kus, T., Tremblay, K., andNadeau, R. (1997): ‘Spatial resolution and role of pacemapping during ablation of accessory pathway’,Pacing Clin. Electrophysiol.,20, pp. 683–694CrossRefGoogle Scholar
  13. Nenonen, J., Edens, J. A., Leon, L. J., andHoráček, B. M. (1991): ‘Computer model of propagated excitation in the anisotropic human heart. I. Implementation and algorithms’,in Murray, A., andArzbaecher, R. (Eds.) ‘Computers in cardiology’ (IEEE Computer Society Press, Los Alamitos, CA), pp. 545–548Google Scholar
  14. Simmers, T. A., Wittkampf, F. H. M., Hauer, R. N. W., andRobles De Medina E. O. (1994): ‘In vivo ventricular lesion growth in radiofrequency catheter ablation’,Pacing Clin. Electrophysiol.,17, pp. 525–531Google Scholar
  15. Singer, I. (1997): ‘Interventional electrophysiology’ (Williams and Wilkins, Baltimore)Google Scholar
  16. Sippensgroenewegen, A., Spekhorst, H., van Hemel, N. M., Kingma, J. H., Hauer, R. N. W., De Bakker, J. M. T., Grimbergen, C. A., Janse, M. J., andDunning, A. J. (1993): ‘Localization of the site of origin of postinfarction ventricular tachycardia by endocardial pace mapping: body surface mapping compared with the 12-lead electrocardiogram’,Circulation,88, pp. 2290–2306Google Scholar

Copyright information

© IFMBE 1999

Authors and Affiliations

  1. 1.Institute of Mathematics, Physics, and MechanicsUniversity of LjobljanaLjubljanaSlovenia
  2. 2.Nova Eccles Harrison Cardiovascular Research and Training InstituteUniversity of UtahSalt Lake CityUSA
  3. 3.Department of PhysicsDalhousie UniversityHalifaxCanada

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