Continuous Response of Optic Nerve Head Blood Flow to Increase of Arterial Blood Pressure in Humans

Abstract

Purpose.: This study investigates the effect of increased ocular perfusion pressure (OPP) on optic nerve head (ONH) hemodynamics.

Methods.: In 21 healthy subjects, the increase in arterial blood pressure (BP), measured continuously using a pneumatic transcutaneous sensor, was produced by isometric exercise consisting of 2 minutes of hand-gripping. ONH blood flow parameters—namely the velocity (Vel), number (Vol), and flux (F) of red blood cells—were measured using the laser Doppler flowmeter (LDF).

Results.: In those 14 healthy subjects who exhibited a similar increase in BP to handgrip superior to 30% of baseline BP, group average increases of BP and OPP amounted to 34% ± 3% (SEM) and 43% ± 3%, respectively. The increase in F of 19% ± 8%, resulting from an increase in Vel (17% ± 7%) and Vol (6% ± 7%), was significantly less than predicted for a passive autoregulatory response, as revealed also by the increase in vascular resistance (R = OPP/F). Spearman test of linear correlations between F and time during handgrip led to the identification of one group of eight subjects (with a stable F) and one group of six subjects (with an increase in F). A closed-loop gain (G) of the regulatory process, defined as G = 1 − {(F − F_bl )/F_bl }/{(OPP − OPP_bl )/OPP_bl }, was found to be rather independent from the OPP, with an average value 0.7 ± 0.07. G was 0.83 ± 0.06 for the group of eight subjects with stable F and 0.3 ± 0.15 for the group of six subjects with F increasing with the OPP.

Conclusions.: The continuous recording of both BP and LDFs represents a novel and more precise approach to the characterization of ONH hemodynamics during isometric exercise, especially useful in the future for patients with ocular diseases. The efficiency of the ONH blood flow autoregulation appears to vary significantly between healthy subjects. (ClinicalTrials.gov number, NCT00874913.)

Introduction

A number of studies have investigated the effect of changes of the mean ocular perfusion pressure (OPP = mean blood pressure in the ophthalmic artery minus the intraocular pressure [IOP]) on blood flow in the different tissues of the human eye. ^1–7 Decreases of the OPP were induced by increasing the IOP, keeping the systemic arterial blood pressure (BP) constant. Increases of OPP were obtained by decreasing the IOP, ⁸ keeping the BP constant, or by increasing BP by means of either dynamic or static exercises, such as isometrics. 

In the human eye, studies of the process of blood flow autoregulation in response to increases in OPP induced by isometric exercises have concentrated primarily on the retinal ^4,5,9,10 and choroidal ^1,6,11–15 vascular systems. In the optic nerve head (ONH), the vessels have no neural innervations. ¹⁶ Therefore, reported regulatory hemodynamic changes in the ONH induced by exercise ^2,3 were interpreted as resulting from a local mechanism (autoregulation in the strict sense). ¹⁷ In these studies, BP was measured by sphygmomanometry at discrete time intervals. Therefore, the relationship between the changes of blood flow and OPP was based on a small number of discrete data. The advent of new devices enabling the continuous measurement of arterial BP ¹⁸ should permit a more precise characterization of this relationship and, consequently, of the blood flow autoregulation process. 

The purpose of this work was to determine in healthy subjects the responses of the OPP, ONH hemodynamics, and vascular resistance (R) to increases in BP by handgrip based on simultaneous and continuous measurements of both blood flow and BP. 

Materials and Methods

Study Population

Included in the study were 21 healthy nonsmoker subjects, aged 18 to 40 years. The subjects underwent a full ophthalmological examination (visual acuity and refraction, slit lamp examination, IOP, funduscopy, and pachymetry), a general examination with supine and standing BP measurements, and an electrocardiogram. We selected healthy subjects with refractive errors varying between −1 and +1 diopters (D) and normal optic disc. The exclusion criteria included local or general medication, ocular or systemic disease, pregnancy, and reduced motility. The study was conducted in accordance with the Declaration of Helsinki for research involving human subjects and adhered to good clinical practice guidelines. Informed consent was obtained from the subjects after explanation of the study. The study protocol was approved by the local institutional review board (IRB #6705) and was registered on ClinicalTrials.gov (NCT00874913). 

Blood Flow Measurements in the ONH

ONH blood flow changes in response to increases in BP were assessed by continuous laser Doppler flowmetry (LDF), a technique which has been described previously in detail. ¹⁹ In our implementation of LDF for the ONH, ²⁰ we use a new instrument that delivers a coherent near-infrared probing beam (wavelength of 785 nm). This beam is focused at the optic disk (nominal diameter ≈12 μm at the disk; however, due to its scattering in the tissue, its effective size is in fact markedly larger) by having the subject's eye fixate a target consisting of a point-like light from a red diode laser. This target is moved in a plane conjugated with the retina to bring the laser at the desired location at the disk. On the light-collecting side, an annular diaphragm blocks specular reflection in the center while the scattered light passes through the annulus. ²¹  

The power of the laser at the cornea of 90 μW is in conformity to the American National Standards Institute (ANSI) standard Z 136.1 for laser safety. The instrument also enables collecting the light backscattered by a discrete volume of illuminated tissue (area of approximately 130 μm in diameter, excluding the center of approximately 20 μm diameter, depth of approximately 300 μm ²² ). This scattered light is focused onto an avalanche photodiode, the output photocurrent of which is sampled at a frequency of 240 kHz with a 16-bit resolution and processed with development environment software (Labview; National Instruments, Austin, TX) to determine the LDF parameters (the LDFs) in real time at a rate of 17 Hz, using an algorithm based on tissue photon diffusion and probabilistic theory. ²³ The LDFs are: velocity, Vel (kHz); volume, Vol (AU), and relative flux, F = Vel × Vol (AU) of the red blood cells within the sampled tissue volume. They represent mean values obtained by integration over the heart cycle. F is proportional to blood flow if the hematocrit remains constant during the experiment. 

A camera was mounted on the instrument to monitor the location of the probing beam at the pupil. Location of the beam at the ONH disk was monitored by a second camera. During a recording, the operator attempted to keep these locations as constant as possible. When this was not possible, the recording was disregarded and the experiment was restarted. In order to obtain a stable location, the subjects were selected for their capability to maintain a steady fixation. 

The software automatically rejects signals for which: the light intensity reaching the detector (DC, direct current) is not within ±10% of its most frequent value; the volume shows sudden spikes, due to—for example—micro saccades; and the power of the Doppler spectrum is too close to the noise spectrum (values at Doppler shift frequencies around 0.5 kHz should be at least three time larger than the noise evaluated around 15 kHz). Two or more continuous 30-second recordings of the LDFs were obtained for a baseline measurement and a minimum of 12 seconds of valid measurement in each eye was required for determining the LDFs. During handgrip, the LDFs were recorded continuously for 120 seconds. 

Study Protocol

Subjects were asked to abstain from alcohol and caffeine for at least 12 hours before undergoing measurements. LDF was performed after dilation of the pupil with one drop of tropicamide (0.5%; Théa, Clermont-Ferrand, France). A monitor with a pneumatic transcutaneous sensor (Nexfin; Bmeye, Amsterdam, The Netherlands) allowed continuous recording of systolic, diastolic and mean BP. ¹⁸ Since the measurement of the IOP by contact in itself alters the quality of the LDFs, an additional handgrip experiment, which however did not include LDF, was performed to record the time course of the IOP (one measurement every 30 seconds during 2 minutes). This measurement was made with a tonometer (Tono-Pen XL; Oculab, Glendale, CA) after the instillation of oxybuprocaine (Novartis Pharma, Rueil-Malmaison, France). Three to six successive IOPs were done to reach a mean value with a coefficient of variation of less than 5%. 

OPP was calculated as OPP = (0.74 × BP_m ) − IOP, ²⁴ where BP_m , the mean BP in the brachial artery, was calculated as: BP_m = BP_diastolic + 1/3 (BP_systolic − BP_diastolic ). So defined, the OPP represents the mean value of the perfusion pressure during the cardiac cycle. The mean vascular resistance (R) was calculated as R = OPP/F. 

Before the start of the measurements, subjects were seated for at least 20 minutes to establish stable baseline conditions. Handgrip consisted of static contraction of the finger flexors to 30% of maximum contraction force using a hand dynamometer (Model SH5001; Saehan Corporation, Masan, South Korea). 

Normalization of the LDFs.

Because LDF provides only relative values, the LDFs and R were normalized at baseline (average over 10 seconds of measurement prehandgrip) to a value equal to 100% in each subject. This normalization was also used for the OPP. Following this procedure, the OPP, LDFs, and R were plotted as a function of time with a resolution of 1 second. The results plotted each second corresponded to a value of BP and an average of 14 values of LDFs. 

Gain of the Regulatory Process.

From the F versus OPP plot, a closed-loop gain (G) of the regulatory process was defined as follows: G = 1 − {(F − F_bl )/F_bl }/{(OPP − OPP_bl )/OPP_bl }, where F_bl and OPP_bl were both set to a value of 100%. From this definition, it follows that G = 1 for a system that fully regulates its blood flow and G = 0 in the absence of such a regulation. The G values obtained in this study were also compared to the values which were calculated from F versus OPP graphs published by previous investigators. ^2,15  

Statistical Analysis

Group mean (±SEM) normalized OPP, LDFs, and R were determined. Baseline- and end-of-handgrip values represent the average of the values obtained during 10 seconds prior to isometric exercise and the last 10 seconds of the handgrip, respectively. To estimate the correlations between the LDFs and time and/or OPP, generalized estimating equations (GEE) were used to properly adjust for nonindependent contribution (SAS procedure, procedure genmod, available in the public domain at http://support.sas.com/onlinedoc/913) since subjects provided multiple data within each intervals of OPP or time. Given the non-normality of the data (as assessed by the Shapiro-Wilk test), log-transformation was performed. Validity of large sample with GEE does not require normality of the response. ²⁵ Spearman test was used to test the correlation between F and time for each subject. 

Results

The data of 14 subjects (7 males and 7 females, mean age of 27 ± 5 years) were considered after exclusion of 7 subjects from an initial series of 21 healthy subjects. Six subjects were excluded based on the fact that during the 2 minutes of handgrip, arterial BP increased by less than 30% from the baseline BP. One subject was also removed from the statistical analysis since F varied by as much as 250% during handgrip due to unstable target fixation. Group mean baseline BP and IOP values were 97 ± 11 mm Hg and 14 ± 3 mm Hg, respectively. In 10 subjects, the LDFs were measured at a superior temporal location and in four subjects, at an inferior temporal location of the disk. Rejection of data (as described in the Methods section) led to an average analysis duration of 84 ± 13 seconds (70% of the 2 minutes of handgrip). The subjects showed an average increase of BP at the end of handgrip of 39% ± 3% above baseline BP, a value based on a linear regression of BP versus time. Figure 1A shows the group average OPP versus time. A linear regression of OPP versus time during handgrip was significant (P < 0.0001). During the last 10 seconds of handgrip, this OPP shows an average increase of 43% ± 3% above baseline. Figure 1B illustrates the time course of the LDFs in response to the increase of the OPPs. The increase of F above its baseline value reached 19% ± 8% at the end of the exercise due to an increase in both Vel (17% ± 7%) and Vol (6% ± 7%). A linear regression of each F and Vel versus time was significant (P = 0.01 and 0.02, respectively). There was a tendency for Vol to increase with time (P = 0.18). The linear regression of R versus time (Fig. 1C) was significant (P = 0.008), showing an increase of 33% ± 9% at the end of handgrip. 

Figure 1

 

Group continuous average time course of normalized OPP (A); Vel, Vol, F (B); and R (C) during 2 minutes of handgrip for the population of 14 subjects (moving average based on 11 consecutive data points). Normalization consisted of setting the baseline (prehandgrip) values in each subject equal to 100%. Error bars represent SEM and only the upper part of the error bars was plotted for clarity. The straight lines represent calculated linear regressions.

Figure 2A shows a plot of F versus OPP, with the dashed line representing the theoretical curve if F were to increase proportionally to the OPP. A linear regression of R versus OPP (calculated for a range of OPPs from 100%–150%) was significant (P = 0.00013). A median increase of 50% in OPP above baseline resulted in a median increase of F of 14% and R of 32%. During the last 10 seconds of exercise, R was 33% ± 9% above its baseline value. 

Figure 2

 

Relationship of F versus change in OPP during 2 minutes of handgrip (A) in 14 healthy subjects, (B) in 6 healthy subjects with increased F, and (C) in 8 healthy subjects with stable F. The fact that some of the LDFs and OPP do not start at 100% at starting time is due to the moving average based on 200 consecutive normalized data points. Error bars represent SEM. The line represents the theoretical response of F if F increases proportionally to OPP.

Spearman test of linear correlations between F and time led to the identification of two subgroups of subjects (Table; Fig. 3): one made up of eight subjects, each showing a stable F as defined by a nonsignificant correlation coefficient (P > 0.05) and the other consisting of six subjects, each demonstrating an increase in F as defined by a significant positive (P < 0.001) correlation coefficient. 

Figure 3

 

Group average time course of Vel, Vol, F, and R changes during 2 minutes of handgrip for one subject (linear regression curve of F, r = 0.09, P = 0.3) and the population of eight subjects with a stable blood flow (A), one subject (r = 0.43, P < 0.0001) and the population of six subjects with an increased blood flow (B). Error bars represent SEM. The regression line of F and Resistance (R) values is drawn. The fact that some of the LDF and OPP changes do not start at a value of zero at starting time is due to the moving average based on 11 consecutive data points.

Table

 

Regression Analysis of OPP, F, and R Across Time

	Regression Coefficient	CI 95%	P Value
Group of stable F, n = 8
OPP	0.0013	0.001/0.0015	<0.001
R	0.0013	0.0008/0.0018	<0.001
F	−0.0001	−0.0004/0.002	0.69
Group of increased F, n = 6
OPP	0.0013	0.0011/0.0015	<0.001
R	−0.0001	−0.0006/0.0004	0.6
F	0.0014	0.0009/0.002	<0.001
Overall population, n = 14
OPP	0.0013	0.0011/0.0014	<0.001
R	0.0007	0.0002/0.0012	0.0083
F	0.0006	0.0001/0.0011	0.0181

 Regression: log Y (normalized data). Statistics were performed using normalized data. CI, confidence interval; F, flow; OPP, ocular perfusion pressure; R, resistance.

Figures 2B and 2C represent plots of the LDFs versus OPP for the groups of six subjects with F increasing significantly with the OPP and eight subjects with stable F, respectively. Stable F was due to nonsignificant changes in both Vol and Vel (P = 0.5), whereas the increase of F was due to significant increases of both Vol and Vel (P = 0.0005 and 0.001, respectively). 

The gain, G, of the autoregulation was calculated from the measurements in Figure 2 for the three groups and is shown in Figure 4. G was found to be rather independent from the OPP (between 118% and 155%), as revealed by nonsignificant coefficient of regression with an average value of 0.7 ± 0.07. For the groups of eight and six subjects, G was 0.83 ± 0.06 (OPP from 115%–155%) and 0.3 ± 0.15 (OPP 120%–150%), respectively. For the group of six subjects, there was no statistically detectable change in F below an OPP of 119%. 

Figure 4

 

Illustration of G of the autoregulation. (A) In 14 healthy subjects (r = −0.2, P = 0.7). (B) In six healthy subjects with increased F (r = −0.5, P = 0.19). (C) In eight healthy subjects with stable F (r = 0.11, P = 0.7).

Visual inspection of the individual LDFs recordings showed oscillations of these parameters during the handgrip exercise in 10 out of 14 subjects, as exemplified by the LDFs recordings in Figure 5. Frequencies of the oscillations were between 3 and 3.6 cycles/min. In 80% of the subjects, we found phase shifts of approximately 180° between Vol and Vel. 

Figure 5

 

Time course of F, Vel, and Vol in one of the subjects (no. 5) during handgrip illustrating rhythmic fluctuations of LDF parameters.

Discussion

The continuous and simultaneous noninvasive measurements of brachial blood pressure and LDFs during isometrics allow a more detailed quantitative description of the relationship between ONH F and OPP than previously possible. Indeed, in past investigations, this relationship was derived based on a small number of discrete OPP data obtained during a few minutes of isometric exercise. Furthermore, our investigation aimed at obtaining a homogeneous group of healthy volunteers with regard to the magnitude of the BP response magnitude as well as the time course of this response to handgrip. This led us to the inclusion of 14 subjects who demonstrated an increase of BP of more than 30% of baseline BP during approximately 2 minutes of handgrip. Our study thus differs from a recent investigation performed in 24 young volunteers, ¹⁵ which allowed a wide interindividual variability of OPP increases and time course of these increases. 

In humans, BP can be increased noninvasively by isometric ^6,26 or dynamic exercise. ²⁶ In this study, we selected handgrip since it causes a greater increase in BP than dynamic exercise, ²⁶ principally by stimulating the sympathetic nervous system. ²⁷ This is a reproducible and noninvasive test of sympathetic function with a well-defined reflex pathway, ²⁸ leading to an increase of muscle sympathetic nerve activity and plasma catecholamines. Isometrics also increase heart rate, cardiac output, left ventricular contractility, and systemic vascular resistance. ^29–32 The cardiovascular effect depends mainly on the intensity of the isometric contraction and the duration of the isometric exercise, ³³ irrespective of muscle mass. ³⁴  

The data in our 14 volunteers demonstrate that the increase of F in response to the increase of the OPP during handgrip is significantly less than predicted for a passive vascular system, indicating the presence of blood flow autoregulation in the ONH of young, healthy subjects, thus confirming previous reports by others. ^2,3,7,15  

As an index of the efficiency of the autoregulation process, we calculated a closed-loop gain, G at a number of discrete values of the OPP. For the 14 subjects, a mean value of G was found to be 0.7 ± 0.07, which represents an efficient autoregulation, since a value of G = 1 corresponds to a process in which F remains constant and equal to the baseline flow in spite of a change in the OPP and a G = 0 corresponds to proportional increases of F and OPP (passive system—i.e., no change in R). As a matter of comparison with previous studies, the gain was also determined from the ONH F versus OPP relationship established by other investigations in response to isometric exercise. Thus from Figure 5 of Movaffaghy et al., ² an average G of 0.67 ± 0.24 (OPP in the range, 105%–178%) was obtained; and from Figure 4 of Schmidl et al., ¹⁵ we obtained an average G of 0.76 ± 0.13 (OPP in the range, 105%–154%) for an OPP in the range, 105% to 154%. These studies demonstrated similar F responses as those reported in our series, as well as similar G values. 

The capability of our method to measure continuously BP and F allows us to establish robust linear correlations between blood flow and perfusion pressure. Based on the P values of the correlation coefficients of the individual linear regressions of F versus time, the 14 subjects could be subdivided into 2 groups. In the group of eight subjects, the autoregulation was found to be highly efficient once the OPP has increased by approximately 15%. In the group of six subjects, the autoregulation was found to be less efficient, in particular at higher OPPs (above 40%), where G was found to drop to approximately half the average value calculated for OPPs below 40%. This clearly suggests that there are marked differences in the efficiency and OPP range of autoregulation among our normal subjects, a conclusion confirming recent findings of other investigators. ¹⁵  

One possibility to be considered for explaining a lower G in some subjects is whether the response of the vascular system is too slow for F to autoregulate during the increase of the OPP. This is most probably not the case since in Figure 1 of the paper by Movaffaghy et al., ² it can be seen that F remained unaffected by the change of the BP (MAP) from 111 to 138 mm Hg (corresponding to a change of OPP from 63–81 mm Hg—i.e., 29%), occurring within 2.5 minutes (i.e., ≈12%/min). In the present study, the rate of the F change was approximately 16%/min. It is doubtful that this difference in rate of change of the OPP would be the reason for the decrease in G in our group of six subjects. However, this remains to be further explored. It is also unlikely that the slower G is related to the location of the ONH measurement since in both groups of subjects, measurements were done at the inferior and the superior ONH location site (2/6 in the inferior temporal location in the increased by flow (BF) group and 2/8 in the stable BF group, P > 0.05). 

Calculation of the OPP using the BP_m, instead of the mean ophthalmic artery blood pressure (OABP), which was not measured, assumes implicitly that the factor 0.74, which expresses the drop of blood pressure between the brachial artery and the OA is not affected by the isometric exercise. The data of Robinson et al., ⁵ showed that this is the case by demonstrating a linear relationship between the OABP and BP_m during squatting. This relationship also indicates that the change in R during handgrip does not occur before the OA and must take place between the OA and the exit of the eye. 

In the ONH, only two recent human studies ^35,36 have explored the mediators potentially involved in the autoregulatory response during isometric exercise. Endothelin-A receptor has been implicated in the response of ONH blood flow in humans, ³⁶ similarly of that reported in the choroid ¹² and the retinal vessels. ⁹ During BQ-123 administration, ³⁶ the increase of ONH blood flow was significantly higher during OPP increase, suggesting that the vasoconstrictor effect of endothelin-1 counteracts the increase of the OPP. On the other hand, it appears that this response in the ONH does not involve nitric oxide ³⁵ in contrast to that found in the choroid. ¹¹  

In most of our subjects, we observed rhythmic changes in the LDFs during handgrip at a rate between 3 and 3.6 cycles/min and phase shifts between Vol and Vel of approximately 180°. These fluctuations were not correlated with those of the OPP. Similar fluctuations of the ONH LDFs were reported in a previous study in minipigs. ³⁷ Because these were not correlated with fluctuations of choroidal or retinal blood flow, it was suggested that they had a local origin. Fluctuations observed in our study must have been generated by the increase of the OPP since they were not present at baseline. 

In conclusion, simultaneous and continuous measurement of BP and ONH LDFs allows a more detailed characterization of the response of blood flow to an increase in BP by isometrics. Whereas healthy humans exhibit autoregulation at the ONH, the efficiency of this process appears to vary significantly between subjects with a G-ratio as high as a factor of 2.5 between good and poor regulators. The reason for this variability is not clear and more research is needed to elucidate the mechanisms mediating ONH autoregulation in response to increased blood pressure by isometrics. 

Acknowledgments

Preliminary results were presented in part at the meeting of the European Association for Vision and Eye Research and the French Society of Ophthalmology in 2011. 

Supported by grants from the Association for Research and Education in Ophthalmology; Innovation Hospitalière (Grenoble University Hospital); AGIRADOM Scientific Council; French Hospitals Federation; Ministry of Foreign Affairs (Egide, Germaine de Staël program); and the higher-education network in Western Switzerland (HES-SO). 

Disclosure: C. Chiquet, None; T. Lacharme, None; C. Riva, None; A. Almanjoumi, None; F. Aptel, None; H. Khayi, None; N. Arnol, None; J.-P. Romanet, None; M. Geiser, None