1. Pulsatility Index quantification in the human precapillary arterioles of
the eye
Aristotle G. Koutsiaris ⁎
Department of Medical Laboratories, School of Health Sciences, Technological Educational Institute (TEI) of Thessaly, Larissa, Greece
a b s t r a c ta r t i c l e i n f o
Article history:
Received 2 February 2016
Revised 14 March 2016
Accepted 17 March 2016
Available online 19 March 2016
The Pulsatility Index (PI) was quantified for the first time in the human conjunctival pre-capillary arterioles
in vivo. In 30 arterioles with diameters ranging between 6 and 12 μm, from 15 healthy humans, peak to peak
velocity ranged from 0.2 up to 4.8 mm/s with a mean value equal to 1.4 ± 0.2 (SE) mm/s. The PI ranged from
0.4 to 1.5 and the overall mean value was 0.8 ± 0.1 (SE). The linear correlation between PI and diameter was
practically zero (Spearman's correlation coefficient, rs ≈ 0) for the range of arteriolar diameters examined
here. In this work a first step was made towards the complete PI mapping of the human carotid arterial tree.
© 2016 Elsevier Inc. All rights reserved.
Keywords:
Human
Eye
Microcirculation
Arterioles
Blood flow
Pulsatility Index
Introduction
Popular ways of quantifying the blood flow pulsation in the cardiovas-
cular system are the Resistive Index (RI) (Pourcelot, 1975) and the
Pulsatility Index (PI) (Gosling and King, 1974). Even though physiological
and pathological values of these indices have been studied extensively in
large vessels, the normal range of RI and PI values is still unknown
throughout the vascular tree in most areas of the human body.
The RI was quantified recently at the lowest diameter pre-capillary
arterioles of the human conjunctiva (Koutsiaris et al., 2010) using high
magnification slit lamp video microscopy. The average RI value of 53%
(with a standard error of the mean: ±2%) was very close to the reported
values from the rabbit mesentery (Koutsiaris and Pogiatzi, 2004). Later,
it was proposed that the RI can be expressed as a Neperian logarithmic
function of the vessel diameter (D) in the human eye arterial tree
(Koutsiaris, 2013).
Most of the ultrasound instruments used in clinical practice for the
measurement of the blood velocity waveform, estimate automatically
the value of the PI instead of the RI. Furthermore, the PI cannot be estimat-
ed from RI. Therefore, the purpose of this work was the PI quantification
in the smallest diameter arterioles of the human conjunctiva in vivo. In
the estimating procedure of the PI the average time velocity is required
and consequently all the velocity values over a complete cardiac cycle
must be taken into account. In contrast, RI estimation requires only 2
extreme values from the cycle: the maximum systolic and the minimum
diastolic velocities.
Methods
The experimental set up, human subjects, image registration, diam-
eter and velocity quantification, were reported in detail previously
(Koutsiaris et al., 2010) so, a very brief description follows.
Experimental set up
The experimental set up comprised a PC, a photo slit lamp (Nikon
FS-3V) with a special objective lens and a high-speed CCD camera
(PCO Computer Optics GmbH, Germany) producing 320 × 240 pixel
digital images at a frame rate of 96 fps (frames per second) (Fig. 1).
The conversion factor was 1.26 μm/pixel.
Human subjects
The group of the human normal volunteers consisted of 9 men and 6
women with an average age of 32 years (24 to 38 years old) and an
average body mass index of 23 ± 3 Kg/m2
. They were not under any med-
ication and their diastolic blood pressure was less than 90 mm Hg. Images
were taken from the bulbar conjunctiva (temporal side) of the right eyes
in a room temperature between 22 and 24 °C. Images from females were
taken after their menstruation and before the premenstrual period of
8 days. Not more than 2 microvessels were selected from the same per-
son. The project was approved by the Research Ethics Committee of the
Microvascular Research 106 (2016) 36–38
⁎ 9 Miauli St, Larissa 41223, Greece.
E-mail addresses: ariskout@otenet.gr, ariskout@teilar.gr.
http://dx.doi.org/10.1016/j.mvr.2016.03.008
0026-2862/© 2016 Elsevier Inc. All rights reserved.
Contents lists available at ScienceDirect
Microvascular Research
journal homepage: www.elsevier.com/locate/ymvre

2. University Hospital of Larissa and informed consent was obtained from all
participants in the study.
Image registration
Image sequences were registered manually using a graphical user
interface developed in MATLAB software platform. One of the images
of each sequence was selected as ‘reference’ and the remaining ‘mobile’
images were all registered (translated) to the reference. After image
registration, the most clearly depicted part of each vessel was used to
measure vessel diameter and blood velocity.
Diameter, velocity and PI quantification
Diameter was measured by drawing a line vertically to the
microvessel axis. Axial erythrocyte velocity was estimated from the
axial distance traveled by a red blood cell or a plasma gap, over a
fixed time interval. The blood flow pulsation corresponding to each
arteriole was quantified using the PI definition (Gosling and King,
1974):
PI ¼ Vpp=AVV
where Vpp stands for peak to peak axial velocity (maximum minus
minimum velocity) and AVV stands for the average velocity throughout
the cardiac cycle. The Vpp is shown graphically in Fig. 2(a).
Tyml and Groom (1980) proved that the velocity pulse period in the
capillaries of the frog sartorius muscle is practically identical to the heart
beat period, measuring independently the two kinds of period in a care-
fully designed study. Lee et al. (1994) reached at the same conclusion
for the muscle capillaries of a big mammal (goat) and Sugii et al. (2002)
and Nakano et al. (2003) did the same for the mesenteric arterioles of a
small mammal (rat). Therefore, in this work there was no heart rate
monitoring.
The PI is a dimensionless index which is equal to zero in the case of a
completely flat waveform (Vpp = 0) and equal to one when the peak to
peak ripple matches AVV.
Statistical analysis
The professional edition of Microsoft Office EXCEL 2003 and the
version 1.4 of the SOFA (Paton-Simpson & Associates Ltd.) software
was used for statistical analysis. Linear correlation was estimated with
Spearman's rank correlation coefficient (rs). The level of significance
was set at p b 0.05.
Results
Axial velocity was measured at 30 different precapillary arterioles
with diameters ranging from 6 up to 12 μm. A sum of 150 to 170 images
was acquired from each arteriole and a total of more than 5000 images
were registered to allow the subsequent off-line velocity waveform
measurements. All measured velocities ranged between 0.40 and
5.84 mm/s. The average velocity throughout the cardiac cycle (AVV)
ranged between 0.52 and 3.26 mm/s and peak to peak velocity (Vpp)
values ranged between 0.2 and 4.8 mm/s.
Using the estimated Vpp and AVV values, the Pulsatility Indices (PIs)
were estimated for each diameter (Fig. 2b). Each black dot in Fig. 2(b) is
the PI result from a column diagram similar to the one shown in
Fig. 2(a). The linear correlation between PI and diameter was practically
zero (rs ≈ 0) for the range of arteriolar diameters examined here. The
PIs ranged from 0.4 to 1.5 and their overall mean value was 0.8 ± 0.1
(SE).
Discussion
Axial blood velocity can be used for the estimation of indices such as
the RI and the PI and other hemodynamic parameters such as volume
flow Q and wall shear stress (WSS). WSS is a very important mechanical
stimulus for the endothelium and must be taken into account in the
design of in vitro models (Palmioti et al., 2014; Koutsiaris, 2015).
Some hemodynamic parameters (Q, WSS) depend heavily on
precapillary arteriolar diameter and a change of some micrometers
Fig. 1. A high speed digital camera attached to a slit lamp.
Fig. 2. (a) The velocity variation during the cardiac cycle is shown in columns. Each column is
the average of 2 or 3 velocity measurements from about 10 successive images. 96 successive
images correspond to 1 s. Peak to peak axial velocity is shown diagrammatically.
(b) Pulsatility Index (PI) values in the human eye pre-capillary arterioles are shown
as black dots. Each dot is the PI result from a column diagram similar to the one
shown in part (a). The correlation of PI to arteriolar diameter D was practically
zero. The mean PI (bPIN) was 0.8 ± 0.1 (SE).
37A.G. Koutsiaris / Microvascular Research 106 (2016) 36–38

3. in diameter can make a difference. For example, for a change of D from 6
to 12 μm the average WSS throughout the cardiac cycle decreases fivefold
from 10.5 down to 2.1 N/m2
(Koutsiaris et al., 2010). Nevertheless, other
parameters such as RI present a kind of “immunity” in diameter changes
since they vary little over a wide span of diameters (Koutsiaris, 2013).
From the results presented here, the correlation between PI and
diameter was found close to zero (rs ≈ 0) meaning that the PI for
D = 12 μm was practically the same as the PI for half the vessel diameter
(D = 6 μm).
For the majority (95%) of healthy male human population the heart
rate is between 53 and 89 bpm (beats per minute) (Milnor, 1990) and
the heart rate is higher in females than in males (Gillum, 1988). Consid-
ering the heart rate of 50 bpm as the lower physiological limit translates
to a cardiac cycle period of 1.2 s or to 115 consecutive image frames for
the CCD camera of this study. Therefore, the minimum number of 150
frames per arteriole was adequate for recording more than one cardiac
cycle.
In order to estimate the repeatability of the PI measurements, blood
velocity should be measured in the same arteriole for more than 5
consecutive cardiac cycles. This would require the acquisition of more
than 480 consecutive images from each arteriole and would also require
the use of automatic image registration and velocity measurement
techniques which were not available in this work.
The mean precapillary PI value was found to be 0.8. It would be
interesting to see how this changes in pathological conditions such as
carotid stenosis, sickle cell disease (Kord Valeshabad et al., 2015a,
2015c), unilateral ischemic stroke (Kord Valeshabad et al., 2015b) or
in other situations such as contact lens wearing (Jiang et al., 2014).
New automated axial velocity measurement techniques (Jiang et al.,
2014; Khansari et al., 2015; Landa et al., 2012) could provide help to-
wards this direction. In this work, a first step was made towards the PI
mapping of the human carotid arterial tree.
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