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1 Department of Plastic and Reconstructive Surgery, Malmö University Hospital, S-205 02 Malmö, Sweden; and 2 Group of Nonlinear Dynamics and Synergetics, Faculty of Electrical Engineering, University of Ljubljana, 1000 Ljubljana, Slovenia
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ABSTRACT |
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 TOP
 ABSTRACT
 INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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We have used the wavelet transform to evaluate the time-frequency content of laser-Doppler flowmetry (LDF) signals measured simultaneously on the surfaces of free microvascular flaps deprived of sympathetic nerve activity (SNA), and on adjacent intact skin, in humans. It was thereby possible to determine the frequency interval within which SNA manifests itself in peripheral blood flow oscillations. The frequency interval from 0.0095 to 2 Hz was examined and was divided into five subintervals: I, ~0.01 Hz; II, ~0.04 Hz; III, ~0.1 Hz; IV, ~0.3 Hz; and V, ~1 Hz. The average value of the LDF signal in the time domain as well as the mean amplitude and total power in the interval from 0.0095 to 2 Hz and amplitude and power within each of the five subintervals were significantly lower for signals measured on the free flap (P < 0.002). The normalized spectral amplitude and power in the free flap were significantly lower in only two intervals: I, from 0.0095 to 0.021 Hz; and II, from 0.021 to 0.052 Hz (P < 0.05); thus indicating that SNA is manifested in at least one of these frequency intervals. Because interval I has recently been shown to be the result of vascular endothelial activity, we conclude that we have identified SNA as influencing blood flow oscillations in normal tissues with repetition times of 20-50 s or frequencies of 0.02-0.05 Hz.
blood flow variability; time-frequency analysis; wavelet transform; autoregulation; microvascular free flaps
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INTRODUCTION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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SYMPATHETIC NERVOUS SYSTEM activity provides one of the fundamental mechanisms for the control of blood flow and pressure. In contrast to somatic nerve activity, sympathetic nerves (SN) are continuously active. They rhythmically discharge so that all innervated blood vessels are under some degree of continuous contraction and relaxation. Their control of the blood distribution to the end cells or organs is exerted in several frequency bands, including rhythms related to the cardiac and respiratory cycles. Whereas the rhythmical discharge of SN at higher frequencies does not appear directly to induce oscillations in innervated vasculature, slower frequencies appear to be directly responsible for oscillations in the blood flow (30).
However, it is still unclear which frequency band(s) manifest the effect of sympathetic innervation on the blood flow oscillation in humans. One of the reasons is certainly connected with difficulties in obtaining good low-frequency resolution. Moreover, not one, but several oscillatory components were observed in the blood flow signal spanning from the cardiac frequency (~1 Hz in healthy humans) down to endothelium-related oscillations with frequencies ~0.01 Hz (25, 47). Like the cardiac frequencies, the others are also nonconstant, but rather vary in time. That is why, in studying various oscillatory components in the blood flow signal, a method for time-frequency analysis with logarithmic frequency resolution is required. With the use of Morlet's mother wavelet (17, 34), the wavelet transform was shown to meet these requirements (8, 46, 47).
In this study, clinical cases of microvascular free flaps were used to study the role of sympathetic oscillations in the peripheral blood flow. The flaps were transferred from a suitable donor site to the defected site. During surgery, the free flap is completely detached from its donor site, and the blood perfusion of the flap is restored by means of microvascular anastomoses. Normally, one supplying artery and one draining vein were used. Because all SN fibers are cut in this type of operation, there is no residual sympathetic control of the blood flow to the flap. The aim of the present study was to analyze the frequency content of blood flow signals simultaneously recorded on the free flap and on the intact skin. Any differences may thus be taken as an indication of the characteristic frequency of blood flow oscillations where sympathetic control is manifested.
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METHODS |
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ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Patients
The investigation was conducted according to the Helsinki Declaration of 1975 (Revised 1983). Eight patients, all female, with transferred musculocutaneous flaps were included in the study (median age 50.6 yr, range 45-57 yr).Measurements
A laser-Doppler flowmeter (model PeriFlux PF-3, Perimed; Järfälla, Sweden) was used for the measurements of the skin blood perfusion. The method is noninvasive and allows for continuous recordings (38). The speed of blood cells moving within the measured volume is estimated from the frequency shift between the emitted and scattered light, with some chosen time constant. A time constant of 0.03 s was selected. Each blood perfusion signal was sampled at a frequency of 32 Hz and stored in a personal computer. Although the signal cannot be expressed in other than arbitrary units (AU) (26), in what follows we will refer to it either as blood perfusion or blood flow, because our main interest is cantered on its dynamical properties where only the relative changes are relevant.The signals were recorded after free-flap surgery. The recordings started 2-10 h after reperfusion and continued overnight at the intensive care unit. Two probes functioning simultaneously were used. The first probe collected the signal from the revascularized free flap, whereas the second probe collected the signal from intact skin in the immediate vicinity of the free flap.
The exposed part of the flap was a free-flap skin (musculocutaneous flaps). Its size varied from ~10×15 cm up to ~20 × 30 cm. The flap probe was placed in the exposed center of the flap. The comparison probe, which collected signals from adjacent skin, was placed close to the flap, but out of range from the operation field to ensure that nondenervated skin was monitored, thereby avoiding undermined or compromised skin, and on scar-free skin supported by intact subcutaneous tissue. A common distance to the probe was ~10 cm from the wound and the border of the free flap.
The recordings were motivated clinically as well as experimentally.
Namely, early detection of any disturbances of the flap perfusion is of
paramount importance because a reoperation can usually save the flap if
undertaken without delay. Therefore, the level of blood perfusion was
continuously monitored for immediate detection of possible
complications. At the same time, data were stored for later spectral
analysis. However, movement artifacts are unavoidable in recordings
taken over several hours. Consequently, only the segments without
artifacts were extracted from each recording. A time interval
of 20 min was chosen to achieve the weak stationarity of the signals
necessary for calculation of the wavelet transform. This time interval
allows for reliable estimation of the spectrum in the broad frequency
interval where we expect sympathetic activity to be manifested, namely
from 0.0095 to 2.0 Hz. The same time interval was selected for both
signals (Fig. 1) and the spectral characteristics of signals measured on free flaps were compared with
those of signals measured on intact skin.
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Time-Frequency Analysis
Methods of frequency and time-frequency analysis are based on the theory of Fourier transform (12), a mathematical tool that connects representation of a signal in time and frequency domain. However, the Fourier analysis is inappropriate for dealing with signals that contain time-variable frequency content. Moreover, any abrupt change in time is spread out over the whole observed frequency interval. To obtain localization in time, a short-time Fourier transform was proposed (14). By using this method, a window w(u) of fixed length is shifted along the signal to obtain information about the time and a standard Fourier transform is performed within this window to extract the current frequency content. However, when both low and high frequencies with different time spans are to be detected simultaneously in a signal, the short-time Fourier transform fails either to follow the time evolution of quick events or to estimate the frequency content within the low-frequency band. The method of wavelet analysis offers a solution to this problem. In the wavelet transform, at a particular time instant, each frequency is estimated for a corresponding window. The window,
(u), is called the mother wavelet and is scaled (dilated and constricted) in time, thus allowing for frequency localization. In
this way, a family of generally nonorthogonal basis functions
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(1) |
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(2) |
By choosing a mother wavelet well concentrated in both time and
frequency, we can precisely detect the frequency content within a given
time interval. Here we are only restricted by the uncertainty principle. Namely, to detect a frequency, the signal must be observed over at least one period of this frequency. Hence, we cannot say exactly at which instant in time the signal had this frequency. The
best time-frequency localization, within the limits given by the
uncertainty principle, can be obtained by using the Morlet wavelet. It
is a Gaussian function modulated by sine wave. The wavelet
transformation of a signal (Fig.
2A) yields a three-dimensional plot (Fig. 2B), which can then be projected in two
dimensions, averaging over either time (Fig. 2C) or
amplitude (Fig. 2D). Before calculation of the wavelet
transform, the average value of each signal was subtracted, normalizing
its mean value to zero. The frequency content <0.0095 Hz, which
manifests as a trend, was also removed by use of a moving average.
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Quantitative measures.
An oscillatory component in a signal can be characterized by its
instantaneous frequency and corresponding amplitude or power. To
compare many signals, quantitative measures were introduced (8). The frequency interval is divided into several
intervals (Fig. 3), and the power and
average amplitude within each interval are used to characterize the
spectral components. In the blood flow signal, five oscillatory
components were demonstrated to exist in the interval between 0.0095 and 2.0 Hz. In resting subjects, their frequencies are centered at
~0.01, 0.04, 0.1, 0.3, and 1 Hz. The outer limits for each
characteristic frequency were determined and are presented in Table
1. Time-averaged wavelet transforms obtained from signals measured on the free flap and on intact skin are
presented in Fig. 3, A and B, respectively. The
frequency intervals for each oscillatory component are indicated.
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Power of spectral components.
In a given frequency interval, the average power can be determined as
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(3) |
i is the total power with the
ith frequency interval and ds and
dt are the derivatives of scale and time, respectively. The frequencies
fi1 and
fi2 are the lower and upper bounds
of the ith frequency interval. The power is averaged over the time tw, for which the wavelet transform was calculated.
To obtain the relative contribution of a particular spectral
component, the normalized power was also introduced
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(4) |
total is the total
power of the signal in the entire frequency range of interest, i.e.,
between 0.0095 and 2.0 Hz in our case.
The average amplitude of a spectral component in a given
frequency interval can be determined as
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(5) |
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(6) |
Statistical Analysis
Data are presented either as group medians within the total range or as box plots. The five horizontal lines at the boxes are the 10%, 25%, 50%, 75%, and 90%. Values below or above the 10% and 90% level are presented as data points. The Mann-Whitney test with two-sided critical values was applied. Statistically significant differences are defined as P < 0.05.| |
RESULTS |
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ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Average Values of Blood Flow Signal
For each 20-min signal, an average value was calculated. Data for both groups of signals, measured simultaneously on the flap (n = 8) and on intact skin in the immediate vicinity (n = 8), are presented as box plots in Fig. 4A. The median of average values of the blood perfusion signals from free flaps is 4.3 (1.4-10.6) AU and 36.9 (6.8-60.3) AU for signals collected from intact skin, thus demonstrating a significantly lower level of blood flow in the flaps (P < 0.0003).
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Average Spectral Amplitude
The mean values of the average spectral amplitude in the frequency range from 0.0095 to 2.0 Hz for signals obtained from free flaps is 0.30 (0.12-0.70) and 4.00 (0.42-6.84) on intact skin. The differences are significant (P < 0.0003). Box plots for both groups are presented in Fig. 4B.Total Spectral Power
The total power in the entire frequency range, i.e., from 0.0095 to 2.0 Hz, was calculated for each signal. The box plots for groups of signals are presented in Fig. 4C. The mean value for signals obtained on flaps is 0.35 (0.04-1.45), and it is 74.92 (0.54-152.30) for signals obtained on intact skin. Again, the differences are significant (P < 0.0003), hence demonstrating that not only the level of flow but also the power of its oscillations is lower on free flaps.Spectral Amplitude Within Each Frequency Interval
Median values and total ranges of spectral amplitude in each frequency interval are summarized in Table 2.
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The amplitude of each oscillatory component is significantly smaller
for signals measured on free flaps. To resolve whether the decrease in
amplitude in any of the frequency intervals is relatively more
pronounced we also present normalized amplitudes. Box plots for both
groups of signals are presented in Fig.
5A. The normalized amplitude
is significantly decreased in intervals I and II.
The median value of normalized amplitude contributed by interval
I for signals obtained on flaps is 1.46 (0.99-2.06) and for
signals obtained on intact skin 3.16 (1.17-6.01), with P < 0.04. The median value of normalized amplitude
within interval II is 1.38 (1.13-2.14) for flaps and
2.54 (1.10-5.18) for intact skin, with P < 0.05.
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Spectral Power Within Each Frequency Interval
Median values and the total range of spectral power in each frequency interval are summarized in Table 3.
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The power of each oscillation is significantly smaller for signals measured on free flaps. Again, to see whether the spectral power in some of the intervals is changed more than in others, we also present the normalized power contributed by each frequency interval to the total power. Box plots for both groups of signals are presented in Fig. 5B. Here, we see that a great decrease in spectral power with respect to the total power occurs for flaps in frequency intervals I (0.0095-0.021 Hz) and II (0.021-0.052 Hz). The median value of normalized power contributed by interval I is 0.012 (0.005-0.025) for flaps and 0.048 (0.006-0.128) for intact skin, with P < 0.03. The median value of normalized power within interval II is 0.026 (0.015-0.058) for flaps and 0.083 (0.015-0.229) for intact skin, with P < 0.05.
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DISCUSSION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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We have presented an analysis of blood flow measured on free flaps and on intact skin within first 24 h after transplantation. Only flaps with no disturbances in perfusion were included in the study. Therefore, two main differences between the intact skin and the free flap were to be expected: 1) the absence of sympathetic control of the vessels in the flap, and 2) reduced endothelium-mediated metabolic activity in the flap.
The blood flow level in free flaps was significantly lower than in intact skin. In addition, the power and amplitude of oscillations in the frequency range from 0.0095 to 2.0 Hz were dramatically lowered. However, the most pronounced decreases, as manifested in normalized values of power and amplitude, were observed in two frequency intervals: interval I, from 0.0095 to 0.021 Hz; and interval II, from 0.021 to 0.052 Hz. These results imply that the sympathetic and endothelium-mediated metabolic activity manifest in either or both of these two frequency intervals.
Oscillations in Blood Flow
The oscillations recorded in the blood flow reflect both vasomotion and flow motion. The vasomotion is usually defined as rhythmic changes in the diameter of the small blood vessels, produced by contraction and relaxation of the muscular components in their walls. The flow motion results from the motion of the blood cells and their interaction with the vessel walls.The cardiac frequency (~1 Hz in a resting, healthy subject) and the respiratory frequency (~0.3 Hz) have been reported in the peripheral blood flow signal, measured by laser-Doppler flowmetry (8, 18, 25, 42, 46). They were also demonstrated in simultaneous measurements of ECG, respiration, and peripheral blood flow recorded at different sites of human skin (7, 46). The essential source of the blood flow, also in the peripheral vessels, is therefore the pressure difference generated by the heart and lung pumps. For example, ~50% of the normalized spectral power in the blood flow is contributed by the heart, both in the intact skin and the free flap (see Fig. 5B). However, there are also peripheral mechanisms that contribute to the oscillations observed in the blood flow.
Endothelium-mediated oscillations. The layer of endothelial cells that lines the entire vascular system acts not only as a passive barrier keeping cells and proteins from escaping freely into the tissue, but also as a source of several vasoactive substances. After Furchgott and Zawadzki (13) showed that the rabbit aorta dilates in response to the application of ACh only in the presence of intact endothelium, several studies were initiated to identify the vasoactive substances and their involvement in metabolic, immune, and cytotoxic activity (33). The application of iontophoretically an endothelium-dependent (ACh) and an endothelium-independent (sodium nitroprusside) vasodilator recently demonstrated that endothelial involvement in blood flow oscillations is manifested in the frequency interval from 0.0095 to 0.021 Hz (25, 47).
Oscillations with a period of ~1 min are significantly reduced in flaps. This may be taken as evidence that the contribution of endothelium-mediated metabolic activity to the blood flow oscillations of the flap is lower than to those of the intact skin. This may be on account of the smaller number of vessels, and hence the smaller area of endothelium involved in the perfusion, during the early stage after transplantation. The release of mediators from ischemic areas in the transplanted flap, such as oxygen-free radicals or nitric oxide, and the exposure of other metabolites after ischemia-reperfusion injury, may well contribute to decreased endothelial activity.Sympathetic regulation of peripheral blood flow oscillations. Apart from frequency interval I, from 0.0095 to 0.021 Hz, the only significant difference between the normalized power and amplitude of oscillations in flaps and in intact skin was observed in the frequency interval II, from 0.021 to 0.052 Hz. Therefore, we may take the results of the present study as evidence that sympathetic control of the peripheral vasculature is involved in oscillations in this frequency interval.
The results obtained are in agreement with the findings of Kastrup et al. (23) and Golenhofen and Hildebrandt (15). With the use of a laser-Doppler flowmeter, Kastrup et al. (23) have identified rhythmical variations in the blood flow of the human skin with median frequencies of 6.8 min
1 (0.11 Hz) and 1.5 min1 (0.025 Hz).
They named these 
-oscillations and 
-oscillations, respectively.
The -oscillations correspond to our interval II, whereas
-oscillations correspond to interval III. They showed that the -oscillations disappeared after local and ganglionic blockade or chronically sympathectomized tissue. Furthermore, they
suggested that -oscillations are a vascular reaction of pure
neurogenic origin.
By using the wavelet transform, which facilitates good low-frequency
resolution, we have confirmed the results of Kastrup et al.
(23), obtained by observing periodicities in the time domain. It is difficult, however, in the time domain to visualize more
than two oscillations. This could be the reason they concentrated only
on those two particular oscillations.
The conclusion that the SN activity (SNA) influences skin blood flow in
the frequency band of 0.02-0.05 Hz contrasts with the results of
the study by Stauss et al. (43). In their investigations, the SN fibers were electrically stimulated at different frequencies and
the responses in skin blood flow were recorded with the laser-Doppler method. In that study, sympathetic modulation of human skin blood flow
was found to be most effective in the frequency range of 0.075-0.1
Hz. However, in the present study, we have collected signals from
reliably denervated postischemic tissue and made comparative
studies with intact tissue in its physiological state in the same
individual without stimulation of any frequency. One possible
explanation for the differences in the results obtained is that, as
observed in the oscillations of the blood flow, the basic activity of
the sympathetic nervous system differs from that induced by electrical
stimulation via major peripheral nerves. Furthermore, the two studies
differ with respect to the methods used for spectral estimation. We
have used continuous wavelet transform, which allows for logarithmic
frequency resolution (which is of particular importance for the
low-frequency content), whereas in the study by Stauss et al.
(43) spectra were estimated using the fast Fourier transform.
There are several studies indicating that the oscillations at 0.1 Hz
are due to resonance in the baroreceptor pathway (4). However, in our study, no difference was observed in the normalized spectral power at 0.1 Hz. Bernardi et al. (5) have argued
that SNA to the skin displays an oscillation at 0.1 Hz, which directly induces an oscillation in the vasculature. However, what they failed to
appreciate was that if blood pressure also displayed an oscillation at
0.1 Hz, then it would be apparent in the blood flow via a simple
pressure to flow relationship. It was shown that the major parts of
skin nerve activity controlling skin temperature are composed of
baroreceptor-independent components (35). This, besides
the improved low-frequency resolution compared with the previous
studies, may be a possible explanation why in our study the skin SNA
was not found to be dominantly influencing the 0.1-Hz oscillation. Yet
it remains to be clarified whether or not the frequency of mechanical
oscillations in the blood flow is synchronized with the discharge
frequency of SNs. It might be that SNA only allows for the skin
vascular oscillations to exist through the production of generalized
tone, and the resultant frequency of oscillation could well be lower
than that of the SN discharge. In fact, the clear-cut divergences in
both setups and the results between Stauss et al. (43) and
our study do indicate that this assumption may be correct.
Recently, Macefield and Wallin (28) demonstrated that the
discharge of human cutaneous sympathetic neurons is modulated by the
respiratory and cardiac frequencies. This might be taken as evidence
that in its control of the stiffness of the peripheral vessels,
sympathetic activity is also governed by the state of the cardiac and
respiratory rhythms. However, the basic frequency of its autonomous
discharge will only be established by analysis of the low-frequency
content of the spontaneous sympathetic neural activity.
The differences between free flaps and intact skin may also be due to
the different skin temperature. It was shown that skin temperature
contains several oscillatory components in the frequency interval of
<0.05 Hz (41), with the dominant frequency components lying <0.01 Hz (27). Because cutaneous nerve activity
also controls skin temperature, a decrease in the temperature
oscillations of the flaps could be expected as a consequence rather
than a cause of the observed differences. However, the interplay
between skin temperature oscillations, blood flow oscillations and
adjacent SNA remains to be established by detailed analysis of all
three simultaneously recorded signals.
Oscillations of local origin.
Interval III, from 0.051 to 0.145 Hz, corresponds to
-oscillations as defined by Kastrup et al. (23).
Rhythmical variations with the frequency ~0.1 Hz were reported
already in the early studies of oscillations in the laser-Doppler
signal of the blood flow (39).
-oscillations
were unchanged during local and ganglionic nerve blockade and preserved in chronically sympathectomized tissue, and they suggested their local
nonneurogenic origin. Johansson and Bohr (21) demonstrated that isolated small subcutaneous vessels show rhythmic contraction. Furthermore, they proposed that this rhythmic behavior must be due to
synchronization of contraction of many smooth muscle cells, indicating
that the separate cells are able to communicate with each other. The
passive local regulation of the blood flow is often named the myogenic
response (11, 22, 40). It is a response to intravascular
pressure elevation mainly mediated by stretch-sensitive ion channels in
the smooth muscle cells. The oscillations with frequency ~0.1 Hz were
shown to be preserved in free flaps immediately after transplantation
(42). The results of the present study might be taken as a
further evidence for the frequency interval at which the myogenic
activity manifests in human cutaneous blood flow. Namely, the
normalized spectral power and amplitude in the frequency interval
~0.1 Hz did not differ in flaps compared with intact skin, thus
illustrating that the underlying mechanism of these oscillations is
probably of local myogenic origin.
Oscillations Observed in Other Hemodynamic Parameters
It has long been recognized that the blood pressure is characterized by several spontaneous oscillations, or waves (32, 36). Besides the cardiac and respiratory waves, slower waves were also detected. Different terms are used in the literature to describe those waves. Traube, Hering, and Mayer, in separate studies, were the first to describe slow waves in blood pressure and the designation Traube-Hering-Mayer waves is often used for all waves slower than respiration. Attempts to identify and classify the waves also resulted in their ordering: cardiac, respiratory, and slow waves are also called waves of the first, second, and third order. After it was shown that the heart rate, cardiac contractility, and venous volume might fluctuate with the same rhythms, several studies (1, 9, 24, 36, 48) were initiated to distinguish these waves according to their origin. Many investigations (3, 16, 19, 20, 29, 31, 37, 44, 45, 49) have been performed to resolve the involvement of the vasomotor component and/or sympathetic control; however, the origin of third-order waves is unknown. Here, we show that oscillations with the same frequencies can also be observed in the peripheral blood flow signal. Moreover, applying the wavelet transform that allows for good low-frequency resolution, we were also able to show that waves slower than the third-order wave can be well distinguished in the blood flow fluctuations. However, their relation to the waves observed in blood pressure and heart rate still remains to be clarified as well as the question of whether waves with the same frequencies observed in other hemodynamic parameters share a common physiological origin.Physiological and Clinical Implications
Vascular endothelial dysfunction has become a key issue in cardiovascular biology, in particular with respect to its role in the pathogenesis of arteriosclerosis, essential hypertension, diabetes mellitus, and heart failure (2, 10). Recently, the spectral analysis of laser-Doppler signals from peripheral blood flow measurements was shown to enable an in vivo noninvasive evaluation of endothelial function (25, 46). Our present study indicates that vascular sympathetic activity may also be evaluated in a similar way. The role of SN influence on the spatial distribution and level of skin perfusion has been graphically demonstrated with the laser-Doppler imaging technique (8). This study, however, strongly indicates that the presence of vascular sympathetic activity in tissue, at any time point, can be evaluated by examining the low-frequency domain of collected laser-Doppler signals. This possibility is of great interest for several diagnostic and therapeutic purposes, the identification and distributive pattern of SN degeneration in patients with diabetes mellitus being only one example.In conclusion, in the absence of neurogenic control, but with a restored microcirculatory blood flow, the clinical free flap transfer was used as a model for studying the physiological origin of oscillations observed in the peripheral blood flow signal. The difference between spectral properties of blood perfusion signals measured on intact skin and free flap is manifested in the frequency interval <0.05 Hz. Besides oscillations in the frequency interval ~0.01 Hz, which were recently demonstrated to result from endothelial activity (25), it was shown that the main difference between the free flap and intact skin occurred in the frequency interval between 0.021 and 0.052 Hz. The compelling explanation is that the sympathetic control of blood flow oscillations are expressed with a repetition time between 20 and 50 s. Furthermore, our results feature a noninvasive technique for evaluation of sympathetic control of peripheral vascular activity, which may be important both for diagnostic and for therapeutic purposes.
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ACKNOWLEDGEMENTS |
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The measurements were performed at the Department of Plastic and Reconstructive Surgery, Malmö University Hospital, Malmö, Sweden, within the European Concerted Action "Laser-Doppler Flowmetry for Microcirculation Monitoring."
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FOOTNOTES |
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T. Söderström and H. Svensson were supported by grants from Lund University and The European Commission. A. Stefanovska and M. Veber were supported by a grant from the Slovenian Ministry of Education, Science, and Sport, and A. Stefanovska was also partially supported by the Royal Society of London.
Address for reprint requests and other correspondence: T. Söderström, Dept. of Plastic and Reconstructive Surgery, Malmö Univ. Hospital, S-205 02 Malmö, Sweden (E-mail: t{at}soderstrom.nu).
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
10.1152/ajpheart.00826.2000
Received 25 August 2000; accepted in final form 4 November 2002.
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
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