Waldemar Kolodziej | PubMed Health

PubMed2007

Noninvasive measurement of intracranial pressure: is it possible?

BACKGROUND: Some publications suggest a strong correlation between the intracranial pressure and the intraocular pressure. Other studies claim no correlation between these two physiologic variables. Our aim was to study whether the tonometry could be a useful method to evaluate intracranial pressure in patients with suspected intracranial abnormality. METHODS: We evaluated the correlation between the intracranial pressure and the intraocular pressure, the intracranial pressure and the mean arterial pressure, and the intraocular pressure and the mean arterial pressure in 22 patients, initially comatose, who were admitted to our hospital. All patients required the intracranial pressure monitoring on clinical grounds. Simultaneous measurements were performed and recorded. RESULTS: We calculated both the linear correlation coefficient and the Spearman rank-order correlation coefficient. We found significant correlation between the intraocular pressure and the mean arterial pressure in 12 patients; however, significant correlation between the intraocular pressure and the intracranial pressure was found in only 2 patients. CONCLUSION: Tonometry is not an appropriate method for the assessment of intracranial pressure increases.

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PubMed2005

Phase dynamics in cerebral autoregulation.

Complex continuous wavelet transforms are used to study the dynamics of instantaneous phase difference delta phi between the fluctuations of arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) in a middle cerebral artery. For healthy individuals, this phase difference changes slowly over time and has an almost uniform distribution for the very low-frequency (0.02-0.07 Hz) part of the spectrum. We quantify phase dynamics with the help of the synchronization index gamma = (sin delta phi)2 + (cos delta phi)2 that may vary between 0 (uniform distribution of phase differences, so the time series are statistically independent of one another) and 1 (phase locking of ABP and CBFV, so the former drives the latter). For healthy individuals, the group-averaged index gamma has two distinct peaks, one at 0.11 Hz [gamma = 0.59 +/- 0.09] and another at 0.33 Hz (gamma = 0.55 +/- 0.17). In the very low-frequency range (0.02-0.07 Hz), phase difference variability is an inherent property of an intact autoregulation system. Consequently, the average value of the synchronization parameter in this part of the spectrum is equal to 0.13 +/- 0.03. The phase difference variability sheds new light on the nature of cerebral hemodynamics, which so far has been predominantly characterized with the help of the high-pass filter model. In this intrinsically stationary approach, based on the transfer function formalism, the efficient autoregulation is associated with the positive phase shift between oscillations of CBFV and ABP. However, the method is applicable only in the part of the spectrum (0.1-0.3 Hz) where the coherence of these signals is high. We point out that synchrony analysis through the use of wavelet transforms is more general and allows us to study nonstationary aspects of cerebral hemodynamics in the very low-frequency range where the physiological significance of autoregulation is most strongly pronounced.

Adult↗