Blood pulse wave velocity (PWV) is an important physiological parameter that characterizes vascular stiffness. In this letter, we present electrocardiogram-synchronized, photoacoustic microscopy for noninvasive quantification of the PWV in the peripheral vessels of living mice. Interestingly, blood pulse wave-induced fluctuations in blood flow speed were clearly observed in arteries and arterioles, but not in veins or venules. Simultaneously recorded electrocardiograms served as references to measure the travel time of the pulse wave between two cross sections of a chosen vessel and vessel segmentation analysis enabled accurate quantification of the travel distance. PWVs were quantified in ten vessel segments from two mice. Statistical analysis shows a linear correlation between the PWV and the vessel diameter which agrees with known physiology

Hu, Song

Maslov, Konstantin

Wang, Lihong V.

Yeh, Chenghung

Caltech Authors - Main

Photoacoustic microscopy of blood pulse
wave
Chenghung Yeh
Song Hu
Konstantin Maslov
Lihong V. Wang
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Photoacoustic microscopy
of blood pulse wave
Chenghung Yeh,* Song Hu,* Konstantin Maslov, and
Lihong V. Wang
Washington University in St. Louis, Optical Imaging Laboratory,
Department of Biomedical Engineering, One Brookings Drive, St. Louis,
Missouri 63130-4899
Abstract. Blood pulse wave velocity (PWV) is an impor-
tant physiological parameter that characterizes vascular
stiffness. In this letter, we present electrocardiogram-
synchronized, photoacoustic microscopy for noninvasive
quantification of the PWV in the peripheral vessels of living
mice. Interestingly, blood pulse wave-induced fluctuations
in blood flow speed were clearly observed in arteries and
arterioles, but not in veins or venules. Simultaneously
recorded electrocardiograms served as references to mea-
sure the travel time of the pulse wave between two cross
sections of a chosen vessel and vessel segmentation analysis
enabled accurate quantification of the travel distance.
PWVs were quantified in ten vessel segments from two
mice. Statistical analysis shows a linear correlation between
the PWV and the vessel diameter which agrees with known
physiology. © 2012 Society of Photo-Optical Instrumentation Engineers
(SPIE). [DOI: 10.1117/1.JBO.17.7.070504]
Keywords: optical-resolution photoacoustic microscopy; electrocardio-
graphy; pulse wave velocity.
Paper 12248L received Apr. 20, 2012; revised manuscript received
May 22, 2012; accepted for publication May 22, 2012; published
online Jun. 28, 2012.
Cardiovascular diseases, particularly hypertension and athero-
sclerosis, often induce pathological changes to arterial compli-
ance and resistance.1,2 Consequent pathological change in local
blood pulse wave velocity (PWV) has been widely adopted as a
robust disease indicator.2,3 Traditional Doppler ultrasound has
been used for PWV measurements, however, it is limited to
large trunk vessels.1,4,5
Photoacoustic microscopy (PAM) is capable of high sensitiv-
ity, high resolution, and noninvasive vascular imaging in vivo,6
extending PWV measurements to small peripheral vessels. In
this letter, by simultaneously monitoring blood flow speed
and cardiac pulsation using a combined PAM-electrocardiogra-
phy (ECG) system, we demonstrated the first in vivo photoa-
coustic measurement of the PWV in the mouse peripheral
vasculature.
The dual-modal system consists of a second-generation opti-
cal-resolution PAM (OR-PAM) system7 and a home-made ECG
recorder, as seen in Fig. 1. In OR-PAM, the outputs of a solid-
state laser (SPOT, Elforlight) and a wavelength-tunable laser
system (pump laser: INNOSLAB, Edgewave; dye laser:
CBR-D, Sirah) were combined using a beam splitter to provide
pulse-to-pulse wavelength switching for the measurement of
hemoglobin oxygen saturation (SO2). The combined laser
beam was spatially filtered by an iris (ID25SS, Thorlabs; aper-
ture size: 2 mm), focused by a condenser lens (LA1131, Thor-
labs) through a 50-μm-diameter pinhole (P50C, Thorlabs), and
then coupled into a single-mode fiber (PA-460A-FC-2, Thor-
labs). A tunable neutral density filter (NDC-50C-2M, Thorlabs)
was placed before the fiber coupler to regulate the intensity of
the incident beam. The fiber output was collimated by a micro-
scope objective (RMS4X, Thorlabs), reflected by a mirror, and
re-focused by a second identical objective to achieve nearly dif-
fraction-limited optical focusing (focal diameter: 2.6 μm). A
home-made acoustic-optical beam combiner, containing an
oil-filled interface, was placed beneath the objective to align
the optical excitation and ultrasound detection coaxially and
confocally. The generated photoacoustic wave was focused
by an acoustic lens, detected by an unfocused ultrasonic trans-
ducer (V214-BB-RM, Olympus-NDT), and amplified by two
24-dB cascaded electrical amplifiers (ZFL 500LN, Mini-Cir-
cuits). Electrocardiograms were simultaneously recorded with
three electrodes, one connected to the ground, one to a front
leg, and one to a hind leg of a mouse. The ECG signals
were then amplified by a high-gain differential amplifier
(Model 3000, A-M systems). The acquired photoacoustic and
ECG signals were digitized by a dual-channel high-resolution
digitizer (NI PCI 5124, National Instruments Corporation)
and stored in a computer for offline data processing.
To study the differential responses of arteries and veins to the
cardiac pulsation, we identified the major arteries and veins, in a
5 × 2.5 mm2 region of interest in a mouse ear, using a dual-
wavelength OR-PAM measurement (532 nm from the SPOT
laser and 563 nm from the Sirah laser), as seen in Fig. 2(a).
Then, two cross sections, one from an artery and one from a
vein and depicted by arrows in Fig. 2(a), were selected for a
30-second OR-PAM monitoring of the blood flowduring
which an electrocardiogram was simultaneously recorded. Fig-
ure 2(b) and 2(c) showed representative one-second segments of
the recorded blood flow and ECG patterns in the artery and vein,
respectively. Fourier analysis of the entire 30-second blood flow
pattern and electrocardiogram showed a strong pulsation-
induced oscillation tone in the arterial blood flow, as seen in
Fig. 3(d), but not the venous flow, as shown in Fig. 3(e),
which is consistent with previously reported observations.4 Phy-
siologically speaking,8 arterial blood is actively transported by
the beating of the heart. In contrast, the transportation of venous
blood is passively regulated by valves and driven by the skeletal-
muscle neither have a correlation with heart beat. Therefore, we
focused on PWV measurements in peripheral arteries and
arterioles.
By definition, PWV is the distance traveled, Δl, by the blood
pulse wave divided by the corresponding travel time,Δt. Ideally,
to measure Δt, the blood flow patterns at both the starting and
ending points of the travel path should be recorded simulta-
neously. However, our current OR-PAM system is based on
focused scanning, which allows flow patterns to be monitored
at only one location at a time.
To solve this problem, we simultaneously recorded ECG sig-
nals as references, a technique previously adopted for ultra-
sound-based PWV measurements.9 As shown in Fig. 3(a),
*Authors contributed equally to this work.
Address all correspondence to: Lihong V. Wang, Optical Imaging Laboratory,
Department of Biomedical Engineering, Washington University in St. Louis,
One Brookings Drive, St. Louis, Missouri 63130-4899. Tel: +1 (314) 935-
6152; Fax: +1 (314) 935-7448; E-mail: lhwang@wustl.edu 0091-3286/2012/$25.00 © 2012 SPIE
Journal of Biomedical Optics 070504-1 July 2012 • Vol. 17(7)
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the ECG and blood flow patterns were divided into single-period
segments according to the R-spike of the ECG signal in each
cardiac cycle. Then, all the single-period segments of the
flow patterns, indicated by the thin blue curves in Fig. 3(b),
were aligned according to their corresponding ECG R-spikes
to compute an average, which is depicted by the thick black
curve in Fig. 3(b). For more accurate quantification of Δt,
the average was correlated with the raw flow pattern in each
period and those with poor cross-covariance, cross-covariance
coefficient <0, were discarded, as indicated by the thin blue
curves in Fig. 3(c). The remaining raw single-period flow pat-
terns were re-averaged over all periods. The average flow pat-
terns acquired at the starting, shown by the red solid curve in
Fig. 3(d), and ending, indicated by the black dashed curve in
Fig. 3(d), points of the travel path were compared to compute
Δt using cross-covariance. Furthermore, the travel distance, Δl,
was measured along the vessel axis using vessel segmentation
analysis.10 With experimentally measured Δl and Δt, the PWV
was computed by taking the ratio.
Given the limited temporal resolution of 0.65 ms in our cur-
rent measurement of blood flow, a Δl of ∼1 mm was preferred
to ensure that a PWVof up to 160 cm∕s can be measured. How-
ever, Δl should never exceed the vascular length between two
adjacent bifurcation points because vascular bifurcation might
induce abrupt changes to the phase of the pulse wave. Increasing
Δl can further extend the maximum measurable PWV, at the
expense of localizability. Alternatively, higher repetition-rate
pulsed lasers can improve the temporal resolution, thereby,
enhancing the measurability of a large PWV without sacrificing
the localizability. The minimum measurable PWV is determined
by the minimum Δl and maximum Δt. The minimum Δl is
2.6 μm, the lateral resolution of our OR-PAM system. To
avoid phase ambiguity, the maximum measurable Δt is
167 ms, the average time duration between two adjacent cardiac
pulses. Thus, a PWV as low as 1.6 × 10−3 cm∕s can be
measured.
According to known physiology, the PWVis roughly linearly
proportional to the vessel diameter in normal physiological con-
ditions.5,11 As a validation, we measured the PWVs in ten arter-
ial/arteriolar vessel segments, with various diameters, from two
nude mice (Hsd:Athymic Nude-FoxnlNU, Harlan) of the same
Fig. 1 Schematic of the ECG-synchronized OR-PAM system for PWV
measurement. λ, wavelength; BS, beam splitter; ConL, condenser
lens; ND, neutral density; FC, fiber collimator; SMF, single-mode
fiber; CorL, correction lens; RAP, right-angle prism; SO, silicone oil;
RhP, rhomboid prism; US, ultrasonic transducer; FL, foreleg; HL,
hind leg; PC, personal computer.
Fig. 2 Differential responses of artery and vein to cardiac pulsation.
(a) Dual-wavelength (532 nm and 563 nm) OR-PAM of SO2 in a
nude mouse ear. A, a cross section in the artery; V , a cross section
in the vein. (b) Simultaneous measurements of the arterial flow
speed at cross section; A (top) and ECG (bottom). (c) Simultaneous mea-
surements of the venous flow speed at cross section V (top) and ECG
(bottom). (d) Normalized power spectra of the arterial flow speed (top)
and ECG (bottom) signals shown in (b). (e) Normalized power spectra of
the venous flow speed (top) and ECG (bottom) signals shown in (c).
Fig. 3 Four-step procedure for PWV quantification. (a) Simultaneously
recorded blood flow patterns and ECG are divided into single-period
segments according to the R-spike of the ECG signal in each cardiac
cycle. (b) The single-period raw flow segments are aligned according
to the ECG R-spikes and then averaged. (c) The average flow pattern
is correlated with the raw flow pattern in each period, and the outliers
with negative correlations are discarded. (d) The average flow patterns
acquired at the starting and ending points of the travel path are aligned
according to their ECG counterparts, and the travel time of the pulse
wave is computed using cross-covariance.
Journal of Biomedical Optics 070504-2 July 2012 • Vol. 17(7)
JBO Letters
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batch. Figure 4 shows the experimentally measured PWV versus
the vessel diameter. A linear correlation between the PWV and
the vessel diameter was observed, with an r-value of 0.999 and a
p-value of 0.012. The slope of the linear regression was 2.77,
which agreed with the values reported in the literature.5,11 For
vessels larger than 80 μm in diameter, our present method failed
to give a reasonable estimation of the PWV. The error is likely
caused by the inadequate temporal resolution in resolving the
short travel time due to a high PWV. Also, fluctuation in the
ECG frequency, when measuring at the starting and ending
points of the chosen travel path, contributes to inaccuracy.
In conclusion, we have demonstrated, for the first time, an
ECG-synchronized photoacoustic method for noninvasive mea-
surements of the PWV in mouse peripheral microvessels. Strong
correlations between the simultaneously recorded ECG and the
blood flow patterns were observed in arteries and arterioles, but
not in veins and venules. Furthermore, a linear relationship
between PWV and vessel diameter was observed experimen-
tally, which is in good agreement with the data in the lit-
erature.5,11
Complementary to ultrasonic measurements of PWV in the
aorta, OR-PAM is capable of measuring the PWV in peripheral
microvessels. According to the Moens–Korteweg equation,2
PWV is closely associated with vascular stiffness, vessel wall
thickness, and blood density. This innovation holds the potential
to study a broad range of peripheral cardiovascular diseases,
including diabetes and hypertension, by providing a metric of
local vascular stiffness and blood pressure.2 Extending this
method to intravascular photoacoustic endoscopy12 can
potentially enable early diagnosis of arteriosclerosis.13 Further-
more, combining PWV with previously quantified vascular
anatomy, SO2, blood flow, and the metabolic rate of oxygen,
14
can provide a comprehensive characterization of cardiovascular
diseases.
Acknowledgments
The authors appreciate the close reading of the manuscript by
Professors. James Ballard, Seema Dahlheimer, and Lynnea
Brumbaugh. Thanks to Amy Winkler and Brian Soetikno for
helpful discussions. Thanks to Di Lang for experimental assis-
tance. This work was sponsored by National Institutes of Health
Grants R01 EB000712, R01 EB008085, R01 CA134539, U54
CA136398, R01 CA157277, and R01 CA159959. L.V.W. has
financial interests in Microphotoacoustics, Inc. and Endra,
Inc., which, however, did not support this work. K. Maslov
has a financial interest in Microphotoacoustics, Inc.
References
1. A. K. Reddy et al., “Multichannel pulsed Doppler signal processing
for vascular measurements in mice,” Ultrasound Med. Biol. 35(12),
2042–2054 (2009).
2. W. W. Nichols, M. F. O’Rourke, and C. Vlachopoulos, McDonald’s
Blood Flow in Arteries: Theoretical, Experimental and Clinical Prin-
ciples, Oxford University Press, Oxford, UK (2011).
3. E. G. Lakatta et al., “Human aging: changes in structure and function,”
J. Am. Coll. Cardiol. 10(2, Suppl. 1), 42A–47A (1987).
4. E. Okada et al., “Spectrum analysis of fluctuations of RBC velocity in
microvessels by using microscopic laser Doppler velocimetry,” in Proc.
Ann. Int. IEEE EMBS, Seattle, WA, USA, pp. 1741–1743 (1989).
5. J. Seki, “Flow pulsation and network structure in mesenteric microvas-
culature of rats,” Am. J. Physiol. 266(2), H811–H821 (1994).
6. J. Yao et al., “In vivo photoacoustic imaging of transverse blood flow by
using Doppler broadening of bandwidth,” Opt. Lett. 35(9), 1419–1421
(2010).
7. S. Hu, K. Maslov, and L. V. Wang, “Second-generation optical-resolu-
tion photoacoustic microscopy with improved sensitivity and speed,”
Opt. Lett. 36(7), 1134–1136 (2011).
8. R. E. Klabunde, Cardiovascular Physiology Concepts, Lippincott Wil-
liams & Wilkins, Philadelphia, USA (2011).
9. C. J. Hartley et al., “Noninvasive determination of pulse-wave velocity
in mice,” Am. J. Physiol. 273(1), H494–H500 (1997).
10. S. Oladipupo et al., “VEGF is essential for hypoxia-inducible factor-
mediated neovascularization but dispensable for endothelial sprouting,”
Proc. Natl. Acad. Sci. USA 108(32), 13264–13269 (2011).
11. E. Okada et al., “Application of microscopic laser Doppler velocimeter
for analysis of arterial pulse wave in microcirculation,” in Proc. Ann.
Int. IEEE EMBS, Orlando, FL, USA, pp. 564–566 (1990).
12. J.-M. Yang et al., “Simultaneous functional photoacoustic and ultraso-
nic endoscopy of internal organs in vivo,” Nat. Med. (in press).
13. N. Chubachi et al., “Measurement of local pulse wave velocity in arter-
iosclerosis by ultrasonic Doppler method,” in Proc. IEEE Ultrason.
Symp., Cannes, France, Vol. 3, pp. 1747–1750 (1994).
14. L. V. Wang and S. Hu, “Photoacoustic tomography: in vivo imaging
from organelles to organs,” Science 335(6075), 1458–1462 (2012).
Fig. 4 Pulse wave velocity versus vessel diameter, measured in ten ves-
sel segments from two mice. The measurements were divided into four
categories: 26–38 μm, 38–50 μm, 50–62 μm, and > 62 μm. The PWV
and vessel diameter averaged within each of the first three categories
show a linear relationship with an r-value of 0.999 and a p-value of
0.012.
Journal of Biomedical Optics 070504-3 July 2012 • Vol. 17(7)
JBO Letters
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Photoacoustic microscopy of blood pulse wave

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