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J Appl Physiol 103: 369-375, 2007. First published April 26, 2007; doi:10.1152/japplphysiol.00271.2007
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INNOVATIVE METHODOLOGY

Influence of noninvasive peripheral arterial blood pressure measurements on assessment of dynamic cerebral autoregulation

Emily L. Sammons,1,2 Nilesh J. Samani,1 Stephen M. Smith,1 Wendy E. Rathbone,1 Steve Bentley,3 John F. Potter,4 and Ronney B. Panerai1

1Department of Cardiovascular Sciences, 2Faculty of Medicine, University of Leicester; 3Department of Medical Physics, University Hospitals of Leicester, NHS Trust, Leicester; and 4School of Medicine, University of East Anglia, Norwich, United Kingdom

Submitted 8 March 2007 ; accepted in final form 25 April 2007


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
Assessment of dynamic cerebral autoregulation (CA) requires continuous recording of arterial blood pressure (ABP). In humans, noninvasive ABP recordings with the Finapres device have often been used for this purpose. We compared estimates of dynamic CA derived from Finapres with those from invasive recordings in the aorta. Measurements of finger noninvasive ABP (Finapres), intra-aortic ABP (Millar catheter), surface ECG, transcutaneous CO2, and bilateral cerebral blood flow velocity (CBFV) in the middle cerebral arteries were simultaneously and continuously recorded in 27 patients scheduled for percutaneous coronary interventions. Phase, gain, coherence, and CBFV step response from both the Finapres and intra-arterial catheter were estimated by transfer function analysis. A dynamic autoregulation index (ARI) was also calculated. For both hemispheres, the ARI index and the CBFV step response recovery at 4 s were significantly greater for the Finapres-derived estimates than for the values obtained from aortic pressure. The transfer function gain for frequencies <0.1 Hz was significantly smaller for the Finapres estimates. The phase frequency response was significantly greater for the Finapres estimates at frequencies >0.1 Hz, but not at lower frequencies. The Finapres gives higher values for the efficiency of dynamic CA compared with values derived from aortic pressure measurements, as indicated by biases in the ARI index, CBFV step response, gain, and phase. Despite the significance of these biases, their relatively small amplitude indicates a good level of agreement between indexes of CA derived from the Finapres compared with corresponding estimates obtained from invasive measurements of aortic ABP.

cerebral blood flow velocity; central arterial pressure

CEREBRAL AUTOREGULATION (CA) describes the intrinsic ability of cerebral blood vessels to maintain cerebral blood flow (CBF) relatively constant despite large changes in arterial blood pressure (ABP) (25). CA remains unaltered with ageing and hypertension (3, 30), and there is controversy whether it remains intact during orthostatic stress or not (4, 9, 16, 28, 35). On the other hand, CA has been shown to change under physiological and pathological conditions, such as exercise (17), hypercapnia (7), temperature (6), stroke (5, 13), carotid artery disease (32), and Alzheimer disease (8).

Two technological developments have contributed to a growing interest in the noninvasive assessment of CA. First, the excellent temporal resolution of transcranial Doppler ultrasound has allowed the analysis of transient CBF velocity (CBFV) responses to induced or spontaneous changes in ABP (20). This approach has been termed dynamic CA in contrast to static CA, which relies on steady-state values of CBF and ABP (1, 31). Second, the introduction of devices that can measure ABP continuously by noninvasive means has allowed the study of dynamic CA in populations whose invasive ABP measurement would not be appropriate for ethical, logistic, or safety reasons. Most of these noninvasive devices, like the Finapres, Portapres, or Finometer, use the principle of arterial volume clamping to record ABP in the digital artery (26).

As methods for assessing dynamic cerebral autoregulation move from the research laboratory to clinical practice, it becomes increasingly important to establish any differences in results that could be ascribed to the techniques adopted to record continuous ABP. Noninvasive finger ABP (ABPfin) has been the object of many validation studies, mainly compared with intravascular ABP measurements in the brachial or radial arteries (12). To our knowledge, none of these studies have looked into the influence of ABPfin on estimates of dynamic CA. Since central, rather than peripheral, ABP provides a better approximation to ABP in the large cerebral vessels, we compared estimates of dynamic CA recorded with the Finapres against corresponding values derived from aortic ABP (ABPao) in patients scheduled for routine elective percutaneous coronary interventions.


   METHODS
TOP
 ABSTRACT
 METHODS
RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
Subjects and measurements.   Recruited subjects were scheduled for routine elective percutaneous coronary interventions. Exclusion criteria included conditions potentially affecting the blood flow to the hands such as Raynaud's phenomenon. Patients were screened in advance of their elective procedure with the Finapres device, to exclude those who displayed a difference >5% between the systolic and diastolic ABP values of their right and left hands. Patients were not excluded on the basis of their individual pathologies or medications, since each would act as his/her own control. The local ethics committee approved the study, and all patients were provided with detailed written information regarding the intent and procedures of the study.

All measurements were conducted in the morning after a fasting period of 6 h, during which time patients were asked to refrain from alcohol and nicotine. Left heart catheterization was performed by the femoral artery percutaneous Seldinger technique. After the elective procedure, a catheter-tip pressure transducer (Mikro-Tip SPC-454E; Millar Instruments, Houston, TX), balanced to zero atmospheric pressure, was advanced over a 0.028-inch guide wire, under fluoroscopic guidance to the ascending aorta (2–3 cm above the aortic cusps), and measurements were performed with subjects in a supine position. Bilateral middle cerebral artery (MCA) velocity measurements were obtained via acoustic windows using transcranial Doppler ultrasound (TCD, 2 MHz; Scimed QVL 842X, Bristol, UK), probes being immobilized by an adjustable head frame set. Depth of insonation was between 45 and 55 mm.

ABPfin was measured by the Finapres device (Finapres 2300; Ohmeda, Englewood, CO), attached to the middle finger. The arm was rested at the patient's side at atrial level with the hand kept warm by a blanket. The Finapres cuff was repositioned until a stable waveform was achieved with the servo-adjust on, waveforms being considered stable when the period between servo-adjusts was >30 beats duration (11). Once this had been achieved, the servo-adjust was switched off, to avoid unwanted artifact, and calibration signals from the Finapres and Millar catheter were recorded before each measurement. Three standard chest leads were used to record the ECG. Transcutaneous CO2 levels were measured (TINA; Radiometer, Copenhagen, Denmark).

Simultaneous and continuous measurements of ECG, TINA, ABPfin, TCD, and ABPao data were recorded on digital audiotape (DAT Sony PC-208AX), for 10 min. The Finapres servo was switched back on, the system was allowed to restabilize, and then the servo was switched off again. This was followed by another calibration of the Finapres and intra-arterial catheter and a second 10-min recording.

Data analysis.   Signals recorded on DAT tapes were transferred to a computer for offline editing and analysis. The maximum cerebral blood flow velocity was calculated every 5 ms using the fast Fourier transform (FFT) algorithm. All other analog signals were also digitized at 200 samples/s. The editing process first involved calibration of both ABP signals, followed by visual inspection and removal of artifacts. The two Doppler signals were then median filtered with a window width of 5 samples, and all signals were low-pass filtered by a zero-phase Butterworth filter, with a cut-off frequency of 20 Hz, to prevent aliasing, while preserving their most significant harmonics. The beginning and end of each cardiac cycle were automatically marked from the ECG to allow beat-to-beat estimates of mean, systolic, and diastolic CBFV and ABP.

The beat-to-beat mean CBFV and ABP time series were spline interpolated and then resampled at 5 Hz to create a uniform time base. Transfer function analysis of ABP (input) and CBFV (output) was performed with standard techniques (19, 21, 34). In brief, spectral estimates were obtained with an FFT algorithm, and the Welch method was used to estimate the coherence function, gain, and phase frequency responses from 8 segments of data, 512 samples each, allowing for 40% superposition. The coherence function varies between 0 and 1 and reflects the fraction of output power (i.e., CBFV) that can be linearly explained by the input power at each frequency. The CBFV step response to a hypothetical sudden change in ABP can also be estimated in the time domain from the inverse FFT of gain and phase (21, 22, 24, 34). This function allows direct visualization of the rate of return of CBFV to its original level following a sudden change in ABP, resembling the typical responses obtained by the thigh cuff maneuver (1, 20, 31). The step response recovery to baseline ({Delta}STEP) was expressed as a percentage of the peak value 4 s after the peak.

As proposed by Tiecks et al. (31), the rate of CBFV return can be quantified by an autoregulation index (ARI), varying between 0 (absent autoregulation) and 9 (best autoregulation), by least-squares fitting the best of 10 possible CBFV template response curves to the first 10 s of the step response (23, 31). Mean values of systolic, diastolic, and mean ABP were calculated for the Finapres and aortic pressure for the entire duration of each recording. Mean values of coherence function, gain, and phase of the ABP-CBFV transfer function were calculated for three separate frequency intervals, corresponding to low frequency (LF, 0.0–0.1 Hz), mid-frequency (MF, 0.1–0.25 Hz), and high frequency (HF, 0.25–0.4 Hz).

Statistical analysis.   Only subjects with good-quality CBFV signal recordings for both MCAs were accepted for analysis. Separate analyses were performed for the right and left MCA to compare the consistency of estimates derived from each side. Agreement between estimates of dynamic CA obtained from the Finapres, with corresponding values derived from ABPao, was assessed with Bland-Altman plots and calculation of correlation coefficients. The bias and precision of parameters were obtained from the mean and SD of differences between the Finapres and aorta-derived parameters. The dynamic relationship between the two ABP sources was also quantified by the coherence function between beat-to-beat values of mean ABPao and mean ABPfin. A paired Student's t-test was used to assess the significance of differences, assuming a critical value of P = 0.05. Multiple comparisons were corrected by the Bonferroni procedure. The influence of age on the differences between parameters derived from the Finapres and aortic pressure was tested by linear regression.


   RESULTS
TOP
 ABSTRACT
 METHODS
 RESULTS
DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
Forty-five patients were recruited, but good quality Doppler recordings for both MCAs were only obtained in 27 subjects who were used in the analysis. The main reason for rejection was the absence of a suitable acoustic window in one or both sides. The demographic, clinical profile, and baseline characteristics of the population studied are given in Table 1.


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  		Table 1. Demographics, clinical profile, and baseline characteristics of the study population

 
The bias and SD of differences for ABPfin-ABPao for the systolic, diastolic, and mean ABP were 4.3 ± 18.0 (P = 0.22), 3.2 ± 7.0 (P = 0.027), and –2.5 ± 8.4 mmHg (P = 0.14), respectively. The total mean ABP power was not significantly different between ABPfin and ABPao, but the Finapres power was significantly higher for the LF range (11.75 ± 10.40 vs. 9.74 ± 9.50 mmHg2, P = 0.014) and significantly lower for the MF range (1.48 ± 1.59 vs. 2.63 ± 3.94 mmHg2, P = 0.020).

As shown in Fig. 1, there was a high coherence between mean ABPao and mean ABPfin, but with a sharp reduction for frequencies <0.05 Hz. The mean ± SD coherences for the low, middle, and high frequency ranges were 0.87 ± 0.08, 0.87 ± 0.12, and 0.84 ± 0.18, respectively.


Figure 1
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  		Fig. 1. Population average coherence function between mean aortic arterial blood pressure (ABPao) and mean finger arterial blood pressure (ABPfin) (solid line) and SD (dashed line).

 
Figure 2 illustrates the differences in step response pattern and ARI values that can be obtained using either ABPao or ABPfin as the input pressure, for the same CBFV output signal. For the population as a whole, significant differences were obtained for most parameters from transfer function analysis and the ARI index, for both MCAs, as shown in Table 2. The exceptions were LF coherence and LF phase, for both MCAs, and HF phase for the left MCA (Table 2). The correlation coefficients between transfer-function analysis and time-domain estimates of dynamic CA obtained with the Finapres and from ABPao are given in Table 3.


Figure 2
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  		Fig. 2. Extreme difference in cerebral blood flow velocity (CBFV) step response patterns and extracted values of autoregulation index (ARI) for a 81-yr-old male subject. A: segment of ABPfin, ABPao, and left middle cerebral artery (MCA) CBFV waveforms. B: CBFV step response for ABPfin input (solid line) and fitted Tiecks model (dashed line). C: CBFV step response for ABPao input (solid line) and fitted Tiecks model (dashed line).

 

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  		Table 2. Transfer function analysis parameters for ABPfin or ABPao as input variables and right and left MCA CBFV as ouput

 

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  		Table 3. Correlation coefficients between estimates of dynamic cerebral autoregulation obtained with the Finapres and corresponding values derived from intra-aortic ABP measurements

 
The differences observed for the ARI and {Delta}STEP indicate that ABPfin results in higher values for calculated dynamic CA response, and this is confirmed by the plots in Fig. 3, showing a lower LF gain, higher MF phase, but mainly an average step response that drops significantly more than the response obtained with ABPao.


Figure 3
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  		Fig. 3. Population average coherence function (A), gain (B), phase frequency response (C), and CBFV step response (D) between mean ABP and CBFV (right MCA) for pressure measurements in the aorta (solid line) or Finapres (dashed line). The error bars represent the largest ± 1 SE. Almost identical results were obtained for the left MCA.

 
Figure 4 shows the Bland-Altman plots of gain, phase, ARI, and step response recovery for the right MCA. The only plot which showed a significant trend was the LF gain, with differences becoming more negative as the gain increased (P = 0.008), but this trend became nonsignificant when the negative outlier was removed. Similar results were obtained for the left MCA, but the differences observed were smaller, and no trends were observed in any plots. The two subjects who showed outlier differences in LF phase (Fig. 4B) also displayed outliers in the step response recovery (Fig. 4D), and one of them also contributed to the ARI result outlier (Fig. 4C).


Figure 4
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  		Fig. 4. Bland-Altman plots of low frequency (LF) gain (A), LF phase (B), ARI (C), and step response recovery (D) for the right MCA. The bias is represented by the continuous line, and the dashed lines delimit the approximate 95% confidence interval. The corresponding plots for the left MCA show smaller differences.

 
Linear regressions of differences in ARI or {Delta}STEP (Finapres-aortic) against age (range 41–81 yr old) were not significant.


   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
The accuracy and precision of the Finapres device have been assessed in a variety of physiological and pathological conditions (12), but we are not aware of any previous studies dealing with its influence on estimates of dynamic CA. Other characteristics of our study are also unique, for example regarding the usual method of comparing standard ABP parameters between the Finapres and intra-arterial ABP recordings at rest. Most of these studies recorded intra-arterial pressure in the brachial or radial arteries. Of the few studies that measured ABP in the aorta, two used fluid-filled catheters with an external transducer, which can lead to distortions, mainly in systolic pressure values (9, 26). Hope et al. (11) used high-fidelity solid-state catheter-tip transducers, as in this study, but compared aortic pressure against a radial tonometer, rather than the Finapres. These methodological differences need to be considered when comparing the values of bias and precision that we obtained with the wide range of corresponding values reported in the literature (12). In our case, significant differences were only observed for diastolic pressure, with a small bias of 3.2 mmHg, thus showing a very good agreement between the two pressure sources.

The coherence function between the two pressure sources showed that mean beat-to-beat values of ABPfin were significantly coupled to corresponding values of mean ABPao for the entire frequency range <0.5 Hz. Notably, the highest population average coherence occurred ~0.05 Hz and decreased quite sharply for lower frequencies (Fig. 1). The drop in coherence in the LF range was probably associated with the significantly greater variability of the mean ABPfin in this frequency range, in relation to mean ABPao, which could have been caused by vasomotion under the finger cuff. Overall, the average coherence function between the ABPao and ABPfin compares well with population curves previously reported (15, 18).

From the reduced bias in ABP parameters and the elevated values of coherence, we should expect a good agreement between estimates of dynamic CA derived from the two different pressure sources. On one hand this expectation was confirmed by the average population values shown in Fig. 3 and the relatively small differences observed in the parameters (Table 2 and Fig. 4). In particular, Fig. 4 shows satisfactory agreement for gain, phase, ARI, and {Delta}STEP, except for two subjects who contributed with outlier values. On the other hand, the directional consistency of those differences, and their relatively small scatter, led to statistically significant differences for several parameters that characterize dynamic CA in the frequency and time domain (Table 2). Frequency-domain parameters were averaged for three different spectral bands, but special consideration should be given to the LF range where we can expect dynamic CA to be more active. For frequencies <0.1 Hz, only the gain was significant, for both hemispheres, although the P values for coherence and phase were close to reaching significance (Table 2). Conversely, the two time-domain parameters showed highly significant differences, which could be explained by their reflecting the simultaneous contributions of gain and phase for the entire spectrum. Again, these differences in gain, ARI, and {Delta}STEP are likely to be the consequence of the greater variability observed in mean ABPfin in the LF range compared with the corresponding power of ABPao in the same frequency band. For frequencies >0.1 Hz, the significantly superior coherences between CBFV and ABPao, in relation to the Finapres (Table 2 and Fig. 3A), confirmed the premise that aortic pressure provides a better approximation to MCA pressure than ABPfin.

Both the ARI and the step response indicate that ABPfin tends to give higher values for the efficiency of dynamic CA in relation to values derived from ABPao (Table 2 and Fig. 3D). This result is important bearing in mind when approaching the large body of literature that has accumulated in recent years on human dynamic CA studies, based on ABP measurements in the finger. The vast majority of those studies dealt with specific groups of subjects, and, given the small differences between group averaged parameters (Table 2), it is less likely that their conclusions would have been different if ABPao had been used instead. On the other hand, results could have been different in studies that analyzed individual patients or very small groups of subjects, mainly when there was reason to suspect of a beta-error. One such example is the failure to detect any effects of ageing on dynamic CA (3, 14, 30). For this reason, we have also tested the possible influence of ageing on our set of data but did not find any significant effects. Nevertheless, our youngest subject was 41 yr old, and different results could have been obtained with younger (and healthier) subjects.

The main limitation of this study is the impossibility of extrapolating its findings to healthy subjects and other patient groups. Similarly to other studies involving continuous recordings of aortic pressure, we performed measurements in patients undergoing catheterization of the coronary arteries (10, 11, 27). The fact that these patients might have an increased probability of having both extracranial and intracranial atherosclerotic disease does not invalidate our results since the same CBFV recording was used for the dynamic CA estimates obtained for both ABP sources. Furthermore, these patients are a representative group of individuals that could have been studied with the Finapres for assessment of dynamic CA for a number of different reasons. Our initial findings in this particular group of subjects should encourage further studies covering a wider spectrum of ages and clinical conditions. Seventy-six percent of the subjects included in the study used beta-adrenergic antagonists (beta-blockers) to treat their cardiovascular disease. Significantly, the recent CAFE (Conduit Artery Function Evaluation) study by Williams et al. (33), found that beta-blockers augment systolic ABPao by slowing the heart rate. This prolongs systolic ejection time and thereby allows time for reflected waves to summate the incident wave during its systolic phase. Therefore, we cannot exclude the possibility of altered hemodynamics in the ascending aorta influencing the discrepancies currently reported. Also, we did not measure aortic compliance, which is a known determinant of the preanacrotic phenomena. However, the study by Philippe et al. (27) found no significant correlation between compliance and factors affecting pulse-wave amplification, as well as the Finapres ABP bias.

Under ideal conditions, simultaneous recordings of invasive peripheral ABP would had been useful to identify the source of the differences in dynamic CA that were observed in parameters derived from the Finapres. For ethical reasons, it was not possible to insert an additional catheter in the radial artery in this study, and we cannot rule out the possibility that similar differences would had been observed in dynamic CA parameters extracted from invasive peripheral ABP measurements. Previous studies that relied on invasive peripheral ABP recordings to calculate dynamic CA parameters reported similar patterns for coherence function, gain, phase frequency response, and CBFV step response (23), but because the Finapres data showed relatively small differences in relation to the ABPao results in this study (Fig. 3), a dedicated investigation is necessary to determine how much of the differences observed can be apportioned to the measurement site, i.e., propagation and reflection effects, and how much could be due to limitations in the accuracy of the Finapres.

Previous studies of dynamic CA employed different maneuvers to induce changes in ABP, such as sudden thigh cuff deflation (1, 5, 19, 20, 31, 32, 34), to elicit large changes in CBFV and to reduce the duration of physiological recordings. On the other hand, these maneuvers could have accentuated differences between parameters derived from the Finapres, in relation to the aortic estimates. Birch and Morris (2) have shown that ABP measured by applanation tonometry in the wrist leads to a different time course in relation to the Finapres tracing during thigh-cuff maneuvers. On the other hand, the relatively small fluctuations in ABP observed during recordings at rest, as adopted in this study, could be seen as a more stringent test for the agreement between intra-aortic and noninvasive measurements, due to the relatively worse signal-to-noise ratio of this modality (35).

One common limitation of studies based on transcranial Doppler recordings is the assumption that changes in CBFV reflect changes in CBF, which is only valid if the cross-sectional area of the insonated vessel remains constant. The subjects we studied were at rest, without large changes in ABP or PaCO2, and hence less likely to exhibit changes in MCA diameter than other patient groups (29). In this study, the potential influence of MCA diameter changes was even less of a concern since the same CBFV recording was used for the two different estimates obtained from each ABP source.

In summary, we have shown that estimates of dynamic CA derived from intra-aortic ABP measurements show similar frequency-domain patterns for coherence function, gain, and phase frequency response, as well as similar time-domain CBFV step responses to these previously reported based on peripheral recordings of ABP obtained by invasive or noninvasive methods. Nevertheless, dynamic CA parameters obtained with the Finapres show small, but significant, differences from those extracted from intra-aortic recordings. Future research in this area should investigate the validity of our findings for healthy subjects or other patient groups. Whether similar results would be obtained for intra-arterial measurements in the brachial or radial arteries should also be the subject of further investigations.


   GRANTS
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
ACKNOWLEDGMENTS
 REFERENCES
 
This work was supported by UK Engineering and Physical Sciences Research Council Grant EP/C001656/1.


   ACKNOWLEDGMENTS
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
REFERENCES
 
We are grateful to Professor David Evans and Dr. Lingke Fan for development of the Doppler analyser software.


   FOOTNOTES
 

Address for reprint requests and other correspondence: R. B. Panerai, Dept. of Medical Physics, Leicester Royal Infirmary, Leicester LE1 5WW, UK (e-mail: rp9{at}le.ac.uk)

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.


   REFERENCES
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 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 

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