Frequency-domain analysis of cerebral autoregulation from spontaneous fluctuations in arterial blood pressure

  • R. B. Panerai
  • J. M. Rennie
  • A. W. R. Kelsall
  • D. H. Evans
Article

Abstract

The dynamic relationship between spontaneous fluctuations of arterial blood pressure (ABP) and corresponding changes in crebral blood flow velocity (CBFV) is studied in a population of 83 neonates. Static and dynamic methods are used to identify two subgroups showing either normal (group A, n=23) or impaired (group B, n=21) cerebral autoregulation. An FFT algorithm is used to estimate the coherence and transfer function between CBFV and ABP. The significance of the linear dependence between these two variables in demonstrated by mean values of squared coherence >0.50 for both groups in the frequency range 0.02–0.50 Hz. However, group A has significanlty smaller coherences than group B in the frequency ranges 0.02–0.10 Hz and 0.33–0.49 Hz. The phase response of group A is also significantly more positive than that of group B, with slopes of 9.3±1.05 and 1.80±1.2 rad Hz−1, respectively. The amplitude frequency response is also significantly smaller for group A in relation to group B for the frequency range 0.25–0.43 Hz. These results suggest that transfer function analysis may be able to identify different components of cerebral autoregulation and also provide a deeper understanding of recent findings by other investigators.

Keywords

Cerebral haemodynamics Cerebral blood flow Pressure-velocity relationship Spectral analysis Phase frequency response 

List of symbols

ν(n)

time-domain sequence of CBFV values

p(n)

time-domain sequence of ABP values

V0

mean value of CBFV

P0

mean value of ABP

R0

mean value of resistance-area product

V(f)

Fourier transform ofv(n)

P(f)

Fourier transform ofp(n)

Gpv(f)

cross-spectrum betweenV(f) andP(f)

Gxx(f)

power spectrum of CBFV or ABP

γ2(f)

coherence function

H(f)

transfer function

HR(f)

real part ofH(f)

|H(f)|

frequency response of transfer function (amplitude)

ϕ(f)

phase of frequency response

hpv(n)

impulse response ofv(n) with inputp(n)

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References

  1. Aaslid, R. (1987): ‘Visually evoked dynamic blood flow response of the human cerebral circulation’,Stroke,18, pp. 771–775Google Scholar
  2. Aaslid, R., Lindegard, K. F., Sorteberg, W., andNornes, H. (1989): ‘Cerebral autoregulation dynamics in humans’,Stroke,20, pp. 45–52Google Scholar
  3. Bendat, J. S. andPiersol, A. G. (1986): ‘Random data analysis and measurement procedures (John Wiley & Sons, 2nd edn., New York)MATHGoogle Scholar
  4. Birch, A. A., Dirnhuber, M. J., Hartley-Davies, R., Iannotti, F., andNeilDwyer, G. (1995): ‘Assessment of autoregulation by means of periodic changes in blood pressure’,Stroke,26, pp 834–837Google Scholar
  5. Cohen, J. (1960): ‘A coefficient of agreement for nominal scales’,Educ. Psychol. Meas.,XX, pp. 37–46Google Scholar
  6. DeBoer, R. W., Karemaker, J. M., andStrackee, J. (1985): ‘Relationships between short-term blood-pressure fluctuations and heart-rate variability in resting subjects. I: a spectral analysis approach’,Med. Biol. Eng. Comput.,23, pp. 352–358CrossRefGoogle Scholar
  7. Dewey, R. C., Pieper, H. P., andHunt, W. E. (1974): ‘Experimental cerebral hemodynamics. Vasomotor tone, critical closing pressure, and vascular bed resistance’,J. Neurosurg.,41, pp. 597–606CrossRefGoogle Scholar
  8. Diehl, R. R., Linden, D., Lucke, D. andBerlit, P. (1995): ‘Phase relationship between crebral blood flow velocity and blood pressure. A clinical test of autoreguation’,Stroke,26, pp. 1801–1804.Google Scholar
  9. DiRienzo, M., Castiglioni, P., Parati, G., Mancia, G., andPedotti, A. (1996): ‘Effects of sino-aortic denervation on spectral characteristics of blood pressure and pulse interval variability: a wide-band approach’,Med. Biol. Eng. Comput.,34, pp. 133–141CrossRefGoogle Scholar
  10. Evans, D. H., Levene, M. I., Shortland, D. B. andArcher, L. N. (1988): ‘Resistance index, blood flow velocity, and resistance area product in the cerebral arteries of very low birth weight infants during the first week of life’,Ultrasound Med. Biol.,14, pp. 103–110CrossRefGoogle Scholar
  11. Evans, D. H., Schlindwein, F. S., andLevene, M. I. (1989): ‘An automatic system for capturing and processing ultrasonic Doppler signals and blood pressure signals’,Clin. Phys. Physiol. Meas.,10, pp. 241–251CrossRefGoogle Scholar
  12. Fisher, R. A. (1948): ‘Combining independent tests of significance’,Am. Statistician,2, p. 30CrossRefGoogle Scholar
  13. Giller, C. A. (1990): ‘The frequency-dependent behavior of cerebral autoregulation’,Neurosurgery,27, pp. 362–368CrossRefGoogle Scholar
  14. Jorch, G. andJorch, N. (1987): ‘Failure of autoregulation of cerebral blood flow in neonates studies by pulsed Doppler ultrasound of the internal carotid artery’,Eur. J. Pediatr.,146, pp. 468–472CrossRefGoogle Scholar
  15. Newell, D. W., Aaslid, R., Lam, A., Mayberg, T. S. andWinn, H. R. (1994): ‘Comparison of flow and velocity during dynamic autoregulation testing in humans’,Stroke,25, pp. 793–797Google Scholar
  16. Panerai, R. B., Coughtrey, H., Rennie, J. M. andEvans, D. H. (1993): ‘A model of the instantaneous pressure-velocity relationships of the neonatal cerebral circulation’,Physiol. Meas.,14, pp. 411–418CrossRefGoogle Scholar
  17. Panerai, R. B., Kelsall, A. W. R., Rennie, J. M. andEvans, D. H. (1995): ‘Cerebral autoregulation dynamics in premature newboms’,Stroke,26, pp. 74–80Google Scholar
  18. Panerai, R. B., Kelsall, A. W. R., Rennie, J. M. andEvans, D. H. (1996): ‘Analysis of cerebral blood flow autoregulation in neonates’,IEEE Trans.,BME-43, pp. 779–788Google Scholar
  19. Paulson, O. B., Strandgaard, S. andEdvinson, L. (1990): ‘Cerebral autoregulation’,Cerebrovasc. Brain Metab. Rev.,2, pp. 161–192Google Scholar
  20. Reynolds, K. J., Panerai, R. B., Kelsall, A. W. R., Rennie, J. M. andEvans, D. H. (1997): ‘Spectral pattern of neonatal cerebral flow velocity: comparison with spectra from blood pressure and heart rate’,Pediatric Res.,41, pp. 276–284Google Scholar
  21. Schlindewin, F. S., Smith, M. J. andEvans, D. H. (1988): ‘Spectral analysis of Doppler signals and computation of the normalized first moment in real time using a digital signal processor’,Med. Biol. Eng. Comput.,26, pp. 228–232CrossRefGoogle Scholar
  22. Sitzer, M., Knorr, U. andSeitz, R. J. (1994): ‘Cerebral hemodynamics during sensorimotor activation in humans’,J. Appl. Physiol.,77, pp. 2804–2811Google Scholar
  23. Steiger, H. J., Aaslid, R., Stoos, R. andSeiler, R. W. (1994): ‘Transcranial Doppler monitoring in head injury: relations between type of injury, flow velocities, vasoreactivity, and outcome’,Neurosurgery,34, pp. 79–86Google Scholar
  24. Symon, L., Held, K. andDorsch, N. W. S. (1973): ‘A study of regional autoregulation in the cerebral circulation to increased perfusion pressure in normocapnia and hypercapnia’,Stroke,4, pp. 139–147Google Scholar
  25. Tieks, F. P., Lam, A. M., Aaslid, R. andNewell, D. W. (1995a): ‘Comparison of static and dynamic cerebral autoregulation measurements’,Stroke,26, pp. 1014–1019Google Scholar
  26. Tiecks, F. P., Lam, A. M., Matta B. F., Strebel, S., Douville, C. andNewell, D. W. (1995b): ‘Effects of the Valsalva maneuver on cerebral circulation in health adults. A transcranial Dopplelr study’,Stroke,26, pp. 1386–1392Google Scholar
  27. Zernikow, B., Michel, E., Kohlmann, G., Steck, J., Schmitt, R. M. andJorch, G. (1984): ‘Cerebral autoregulation of preterm neonates— a non-linear control system?’Arch. Dis. Child.,70, pp. F166-F173Google Scholar

Copyright information

© IFMBE 1998

Authors and Affiliations

  • R. B. Panerai
    • 1
  • J. M. Rennie
    • 2
  • A. W. R. Kelsall
    • 2
  • D. H. Evans
    • 1
  1. 1.Division of Medical Physics, Faculty of Medicine, Univeristy of LeicesterLeicester Royal InfirmaryLeicesterUK
  2. 2.Neonatal Intensive Care UnitRosie Maternity HospitalCambridgeUK

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