Elsevier journal article on blood velocity in human eye microvessels
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When blood flow is not pulsating (venules) a limited sequence of
images without vessel movement would be sufficient for the
measurement of velocity. However, for velocity pulse quantification
(arterioles) successive images must be registered (aligned) in a time
extend of at least one cardiac cycle because of microvessel motion
caused by the normal eye micro movements. This is not required in
animal preparations (Rosenblum, 1969; Κοutsiaris and Pogiatzi, 2004)
where the anaesthetized animal stands completely still after a minor
surgery. In addition, more powerful microscope objective lenses can be
used in animal preparations because the lens is permitted to come
closer to the animal tissue in comparison to the human eye and
because of the optical limitations of the slit lamp system.
Recently, a fully automated pixel intensity registration method
(Wu et al., 2009) was used on images from the finger mail-fold and a
semi-automated area based registration technique (Shahidi et al.,
2010) was used on images from the human conjunctiva. Here the
microvessel images were registered manually, following a geometri-
cal feature based procedure described in the following section.
Materials and methods
Experimental arrangement
The experimental set up (Fig. 1) comprised a PC (Pentium 4, 3 GHz)
and a high-speed ultra compact CCD camera (12 bit, PCO Computer
Optics GmbH, Germany) connected to a zoom photo slit lamp (Nikon
FS-3 V) via an appropriate adaptor. The camera produced 12 bit digital
images of 320×240 pixels at a frame rate of 96 fps (frames per
second). The images were then transferred to the main memory of the
computer with the aid of a frame grabber by direct memory access.
Then it was possible for the operator to display the images on the PC
monitor and store them on the hard disk at 8 bit greyscale.
A special objective lens (10×/0.21) placed in front of the slit lamp
raised the maximum magnification through the ocular lenses to 242×
and enhanced the conversion factor to 1.257±0.004 μm/pixel. The
conversion factor (or digital resolution) was measured by using an
object micrometer in front of the objective lens. According to the
Rayleigh criterion, the objective lens had an optical resolution of
1.51 μm for a light wavelength equal to 520 nm (Chris James & Co.
LTD. lighting filters, No 323).
Human subjects
The age of the human volunteers ranged between 24 and 38 years
with an average of 32 years. Images were taken from the bulbar
conjunctiva (temporal side) of the right eyes of 15 normal human
volunteers (9 men and 6 women) with an average body mass index
(BMI, defined as the number of body kilograms over the square of the
height) of 23±3 kg/m2
. The individuals had no smoking or alcohol
habit, no ocular or systemic disease and were not under any
medication.
In case of more than 20% change in either of the initial systolic or
diastolic arterial blood pressure, recordings were not taken into account.
On surplus, subjects with diastolic blood pressure greater than 90 mm
Hg were excluded from the study as hypertensive. No volunteer
contributed by more than two microvessels to the total sample.
In order to avoid any vascular dilations or constrictions associated
with the menstrual cycle, image data from female subjects were acquired
after their menstruation and before the premenstrual period of 8 days.
Due to dependence of microcirculation on temperature (Park et al.,
2008) all measurements were performed in a room temperature
between 22 and 24 ° C after waiting for at least 40 min for temperature
adaptation of the subjects. Also, the filter selection lever of the slit lamp
was set to the heat absorption position to prevent heating of the
conjunctival tissue. The project was approved by the research ethics
committee of the university hospital of Larissa and informed consent
was obtained from all participants in the study.
Image registration
Registration of the image sequences was accomplished employing
a manual approach and using a graphical user interface programme
developed in MATLAB software platform.
One of the images in the sequence was tagged as “reference” and
the remaining “mobile” images were all registered to the reference.
Two white cross-hair tools forming a simple grid of 9 rectangular
quadrilaterals were provided to mark characteristic regions visible in
Fig. 1. The experimental set-up.
203A.G. Koutsiaris et al. / Microvascular Research 80 (2010) 202–208
4. Author's personal copy
every image of the sequence and hence aid in the selection of the
appropriate translation values.
Scrolling through the sequence, each of the “mobile” images was
translated manually so that its characteristic regions were aligned with
the ‘reference’ image. The possible geometrical transformations included
translation along the x and y axes (two-dimensional registration).
An example of the registration procedure for only one mobile
image of a given sequence is shown in Fig. 2.
After the alignment, the velocity measurement can be carried out in
any vessel of theimage sequence choosing the most clearly depicted part.
Internal diameter (D) and axial RBC velocity (V) measurement
The coordinates of the intersection points A (xa, ya) and B (xb, yb)
between a vertical line to the vessel axis and the outer limits of the
erythrocyte column, were used for the calculation of the internal
Fig. 2. An example of using the multi-window 2D manual registration software employed to register each sequence of the acquired conjunctival images: (a) the reference window
(reference 2D dataset) includes animage selectedby the user as reference and two white cross-hair tools were superimposed to facilitate the choice of the translation parameters. The cross
hair tool white lines delineate nine rectangular quadrilaterals. The coordinates of the white lines define the size of the quadrilaterals and can be adjusted in a desired way in order to mark
characteristic regions or sites. The central quadrilateral was adjusted here to include a microvessel section as shown. (b) One of the “mobile” images (here the 140th) of the sequence to be
registered, is displayed in the registration window (registered 2D dataset). It can be noticed that image 140 moved down and to the left probably due to involuntary eye movement. (c) The
mobile image was manuallytranslated in the properdirections (up and to the right) so that the two microvessels have the same positionrelative to the white quadrilaterals. The translation
of the mobile image is also shown by the black margins in the window. (d) The mobile image number (140), the total number of images in the sequence (200), and the coordinates of the
two cross-hair tools [(x1, y1)=(221, 20) and (x2, y2)=(187, 61)] are shown on the left (light gray) side of another window called “Image slice slider—2D transformation parameters”. The
manually set values of the translation parameters x and y (X-translation=10 and Y-translation=−22) are shown on the right (dark gray) side of the window. The z-rotation parameter
was not used. The coordinates and the translation parameters X and Y are in pixels. The same procedure was followed for all the mobile images of the sequence.
204 A.G. Koutsiaris et al. / Microvascular Research 80 (2010) 202–208
5. Author's personal copy
diameter (D), as the distance between these 2 points, according to the
Pythagoras's theorem. Arterioles were identified from the direction of
blood flow (divergent). The final diameter value was estimated from
the average of 3 or 4 different measurements.
Axial erythrocyte velocity was measured from images of the bulbar
conjunctiva by quantifying the axial distance travelled by a RBC or a
plasma gap, over a fixed time interval Δt:
V = DC = Δt ð1Þ
Where, DC stands for the displacement of a RBC or a plasma gap,
after a short time interval Δt known from the frame rate of the camera
as equal to 10.04 ms. The DC was calculated in the same way as the
internal diameter D. Displacement measurements, in pixels, were
converted to mm, using the conversion factor mentioned in
Experimental arrangement.
The total relative error in the axial velocity measurements REV is a
combination of the time interval measurement error and the flow
displacement measurement error. In this work, the REV was
approximately 12.6%. More details on the velocity relative error can
be found elsewhere (Koutsiaris et al., 2007).
Velocity pulse quantification
Every pulsating waveform is characterized by a maximum and a
minimum value. Here, the amplitude of pulsation corresponding to a
microvessel velocity pulse was quantified using the resistive index RI
(Pourcelot, 1975):
RI ¼ ðPSV À EDVÞ=PSV ð2Þ
where PSV stands for peak systolic velocity (maximum) and EDV
stands for end diastolic velocity (minimum). The RI is a positive
dimensionless parameter that takes its minimum value (zero) in the
case of a completely flat waveform (PSV=EDV).
Since the velocity waveform in the microcirculation is relatively
smooth, it was decided to use one velocity value (VV) for every 10
successive images (Fig. 3) corresponding to a time interval approxi-
mately 1/10 of a second (104 ms exactly). So, in Fig. 3 each column
represents one VV. This velocity value was usually the average of 2 or 3
velocity (V) measurements with a coefficient of variation less than
20%.
Some times it was not possible to perform a VV measurement
because of experimental difficulties such as a temporal loss of focus or
an eyelid closure. In these cases, a linear interpolation was performed
using the two neighbor velocity values. An example of an interpolated
VV is shown by a gray column is Fig. 3.
The velocity pulse period (VPP) was defined as the time interval
between two successive VV peaks (Fig. 3). The average value of all the
VVs during a VPP was named as AVV (average velocity value).
The heart rate (HR) in beats per minute (bpm) for each individual
was estimated from the VPP by the following formula:
HR ¼ ð1=VPPÞÃ60 ð3Þ
Where, the VPP is measured in seconds.
From the aforementioned data it is logically deduced that the
higher the VPP the lower the HR and vice versa. A normal HR of 75 bps
corresponds to a VPP of 0.8 s or an image sequence of approximately
77 images. Therefore it was assumed that an image sequence of at least
150 images would cover more than one physiological velocity pulse
period.
Statistical analysis
SPSS for windows version 11.5 was used for statistical analysis.
Correlations were estimated with Pearson's correlation coefficient.
Results were considered significant at pb0.05.
Results
Velocity pulse measurements were taken from 30 different
precapillary arterioles ranging in diameter between 6 and 12 μm.
From each microvessel at least 150 images were recorded and a total
of more than 5000 images were recorded and registered to allow the
subsequent off-line velocity measurements. From the 15 volunteers
no one contributed by more than 2 microvessels in order to avoid bias
from the same person.
The PSVs, AVVs and EDVs of all microvessels are shown in Fig. 4a, b
and c respectively. PSVs ranged between 0.62 and 5.84 mm/s, AVVs
ranged between 0.52 and 3.26 mm/s and EDVs between 0.40 and
1.80 mm/s. The mean values bEDVN, bAVVN and bPSVN and their 95%
confidence intervals (± 1.96 SE) for all microvessels were 1.05±0.13,
1.66±0.22 and 2.45±0.43 mm/s respectively (Fig. 5).
Using the measured PSV (Fig. 4a) and EDV (Fig. 4c) values of each
microvessel in equation 2, the resistive indices RIs were estimated for
each diameter and their values are shown as black dots in Fig. 6. The
very weak positive correlation between RI and diameter (r=0.047)
was statistically not significant (p=0.4). The RI ranged between 35.5%
and 81.8% and its mean value for all microvessels was 53.1±2.2% (SE).
The mean value of all VPPs was equal to 0.84 s±0.02 (SE)
corresponding to a mean heart beat rate of 72 bpm±1.5 (SE).
Discussion
The pre-capillary arteriolar velocity pulse has been quantified in
the past, only in animals, such as mice (Rosenblum, 1969) and rabbits
(Κοutsiaris and Pogiatzi, 2004).
The mean RI estimated from the peak systolic and the end diastolic
velocities measured in 8 mouse pial arterioles (Rosenblum, 1969) was
45.3±3.7% (SE) i.e. 14.7% less than the mean of 53.1±2.2% in the
present work. This could be attributed to the low peripheral resistance
of the brain vascular network. Αs the name of the resistive index
implies, it is considered as a marker of the vascular network flow
resistance downstream the site of measurement.
A mean value of 62.7±2.1% was reported from 14 pre-capillary
arterioles between 6 and 12 μm in the rabbit mesentery (Κοutsiaris
and Pogiatzi, 2004). The mesenteric mean RI is 18.1% higher than the
conjunctival mean of 53.1±2.2% reported here, but again this could
be attributed to the different hemodynamic resistances exhibited by
the different tissues.
The mean value of the RI in a particular tissue, aside from an
indication of the peripheral blood flow resistance, can be useful for
two more reasons described below.
Fig. 3. Velocity pulse quantification in a female conjunctival arteriole with an internal
diameter of 6.9 μm. The velocity value (VV) represented by each column is the average
of 2 or 3 velocity measurements from 10 successive images. An interpolated VV is
shown in gray. Also, the velocity pulse period (VPP) is shown between 2 successive VV
peaks. In this example, VPP=0.94 s and the resistive index RI=44%.
205A.G. Koutsiaris et al. / Microvascular Research 80 (2010) 202–208
6. Author's personal copy
First, a relatively high mean RI value for a particular tissue shows
that, for the correct estimation of velocity dependent hemodynamic
quantities, such as volume flow and shear stress, a single velocity
measurement during the cardiac cycle is not enough, since it can lead to
a serious underestimation or overestimation of the real average velocity
(AVV). According to the results of Fig. 5, a single velocity measurement
equal to the EDV leads to a mean velocity underestimation of 36.7% of
the AVV, whereas a single velocity measurement equal to the PSV leads
to a mean velocity overestimation of 32.2% of the AVV.
Second, the mean RI is useful to the design of hemodynamic
models, either experimental or mathematical, in order to simulate
better the natural state of real biological systems. For example, the
assessment of the validity of the least energy model proposed by
Murray (1926) necessitates the proper estimation of blood flow
throughout the cardiac cycle (Zamir et al., 1992; Koutsiaris, 2005).
Observing the reported RI data taken from larger human arteries
(Table 1) it is impressive to see the small reduction of the mean RI as
the velocity pulse travels through the successive ramifications of the
human carotid arterial tree. In the data of Table 1, the mean RI value of
78% in the common carotid artery (CCA) reduces to 53.1% (only 30%
lower) in the pre-capillary conjunctival arterioles with diameters
approximately 1000 times smaller than that of the CCA.
The low gradient of the RI reduction with diameter in Table 1, is
accordant with the very weak positive correlation (r=0.047) of the RI
with the precapillary arteriolar diameter observed in the present
work (Fig. 6).
Since many investigators have reported that age affects the RI in
the vessels of the head (Williamson et al., 1995; Baxter and
Williamson, 1995; Greenfield et al., 1995; Müller and Schimrigk,
1994), the data of Table 1 were chosen from normal individuals
between 19 and 50 years old.
It should be noticed that the mean RI of the internal carotid artery
(ICA) is lower than that of the ophthalmic artery (OA) presumably
due to the lower resistance of the brain vasculature in comparison to
the ophthalmic vasculature.
Asynchronous contraction and dilatation of arterioles (later called
vasomotion) was first demonstrated by Clark and Clark (1934) in the
vascular network of the rabbit ear. Intaglietta and Gross (1982)
reported vasomotion in only 40% of dorsal skin rat preparations and in
only 33% of the studied arterioles, meaning that vasomotion is not an
activity that can be observed systematically. The frequency, amplitudeFig. 4. (a) peak systolic velocities (PSVs), (b) average velocities values (AVVs) and (c) end
diastolic velocities (EDVs), for all microvessel diameters, are shown in triangles, circles and
black crosses respectively.
Fig. 6. The Resistive indices (RIs) of all microvessel diameters are shown in black dots.
Each dot corresponds to a separate velocity pulse quantification diagram, an example of
which is shown in Fig. 3. The correlation between RI and diameter is very low
(r=0.047) and statistically not significant (p=0.4). The mean RI of all the microvessels
was 53.1% with a standard error of the mean SE=2.2%.
Fig. 5. The mean values of the end diastolic velocities (bEDVN), average velocity values
(bAVVN) and peak systolic velocities (bPSVN) of all microvessels are shown in black
dots and the 95% confidence interval (CI) of the means is shown with bars (1.05±0.13,
1.66±0.22 and 2.45±0.43 respectively). The 95% CI of thebAVVNwas extended on
both sides with a black dashed line for comparison.
206 A.G. Koutsiaris et al. / Microvascular Research 80 (2010) 202–208
7. Author's personal copy
and appearance of vasomotion seem to vary between different
preparations (Ursino et al., 1998).
In humans, vasomotion was observed mainly in the skin tissue,
indirectly, from the consequent flowmotion of blood (Salerud et al.,
1983), using laser Doppler flowmetry (LDF). They reported that
appearance (% of time) of flowmotion rhythmical variations of
amplitude greater than 25% was only 2.6% and occurred at only 20%
of the total number of subjects. Furthermore, the LDF technique is not
vessel specific and consequently it is still unknown which arteriolar
class in each tissue contributes the most.
Later, 5 flowmotion components with average periods of approx-
imately 1, 3, 10, 33 and 100 s were presented (Söderström et al., 2003)
from LDF measurements in the human skin. Recently, Leithäuser et al.
(2008) using nailfold capillary microscopy performed 10 measure-
ments per minute in order to even out the 10-s period vasomotion
fluctuation.
Using an invasive LDF technique, Kvernebo et al. (1990) did not
detect any vasomotion in the human anterior tibial muscle. Today,
there is no experimental evidence for the existence of vasomotion in
the smallest microvessels of the human conjunctival tissue.
In this work, probable flowmotion components with a period
higher than the heart rate period were not taken into account. Since
the heart rate period seems to be the smallest (Söderström et al.,
2003), and the measurements in this work were taken from 30
precapillary arterioles at random times, any influence from higher
period fluctuations is incorporated in the standard deviation of the RI
shown in Table 1 and also in the 95% confidence intervals of the mean
velocities shown in Fig. 5.
As this work is a first estimation of the RI range in the precapillary
arterioles of the human conjunctiva, it is evident that more work will
be required in the microvasculature, in the larger vessels and in
different tissues, before a clear picture is available.
In conclusion, the axial red blood cell velocity was measured over
the entire cardiac cycle, in the precapillary conjunctival arterioles of
15 normal humans between 24 and 38 years old. The mean resistive
index RI estimated from the quantified velocity pulse was 53.1%, a
value approximately 30% lower than that in the common carotid
artery.
Acknowledgments
A part of this work was financially supported from the Greek
Ministry of Education and the European Union (Program Archimedes).
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Table 1
Resistive indices (RI) in the human carotid arterial tree.
Vessel D (μm) RI (%) n (m) Technique Data source
CCA 6200±600 78.0±6.0 48 (48) CDI Yazici et al., 2005
ICA 4500±500 60.0±6.0 48 (48) CDI Yazici et al., 2005
OA —— 73.6±—— 13 (13) CDI Rojanapongpun and Drance, 1992
OA —— 75.0±—— 38 (38) CDI Williamson et al., 1995
OA —— 77.0±4.0 20 (40) CDI Kouvidis et al., 2000
OA 2020±460 —— 14 (14) CDI Orge et al., 2002
CRA —— 67.0±—— 38 (38) CDI Williamson et al., 1995
CRA 166±15 —— 210 (210) FC Taarnhøj et al., 2006
RA 108±13 62.0±9.0 13 (13) LDV Nagaoka and Yoshida, 2006
RA 101±13 63.0±9.0 13 (13) LDV Nagaoka and Yoshida, 2006
PCA 8.5±1.9 53.1±12.2 15 (30) HSM Present work
In the first column from the left, the vessel name is shown in abbreviated form (CCA: Common Carotid Artery, ICA: Internal Carotid Artery, OA: Ophthalmic Artery, CRA: Central
Retinal Artery, RA: Retinal Arterioles and PCA: PreCapillary Arterioles). In the second and third columns, the corresponding diameter D and RI are shown, respectively. All data were
ordered according to the mean vessel diameter D. In the forth column, the number of humans (n) and vessels (m) used for the measurements are shown and in the fifth column, the
RI measurement technique is shown in abbreviated form (CDI: Color Doppler Imaging, FC: Fundus Camera, LDV: Laser Doppler Velocimetry, HSM: High Speed
Microcinematography). All values are expressed as mean±SD (Standard deviation). The age of all humans was between 19 and 40 years, except for the works of Taarnhøj et al.
(2006) and Yazici et al. (2005) including humans up to 46 and 50 years old, respectively. In the work of Williamson et al. (1995) the RI was estimated from the age dependent fit lines
of PSV and EDV for the age of 30 years.
——: Data not available.
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