JBO-130677R 6..6 ++ - JBO_19_1

Label-free photoacoustic microscopy

of peripheral nerves

Thomas Paul Matthews

Chi Zhang

Da-Kang Yao

Konstantin Maslov

Lihong V. Wang

Downloaded From: http://biomedicaloptics.spiedigitallibrary.org/ on 06/17/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx

Label-free photoacoustic microscopy of peripheral

nerves

Thomas Paul Matthews,

†

Chi Zhang,

†

Da-Kang Yao, Konstantin Maslov, and Lihong V. Wang

Washington University in St. Louis, Department of Biomedical Engineering, Campus Box 1097, One Brookings Drive, St. Louis, Missouri 63130

Abstract.

Peripheral neuropathy is a common neurological problem that affects millions of people worldwide.

Diagnosis and treatment of this condition are often hindered by the difficulties in making objective, noninvasive

measurements of nerve fibers. Photoacoustic microscopy (PAM) has the ability to obtain high resolution, specific

images of peripheral nerves without exogenous contrast. We demonstrated the first proof-of-concept imaging of

peripheral nerves using PAM. As validated by both standard histology and photoacoustic spectroscopy, the

origin of photoacoustic signals is myelin, the primary source of lipids in the nerves. An extracted sciatic

nerve sandwiched between two layers of chicken tissue was imaged by PAM to mimic the

in vivo

case.

Ordered fibrous structures inside the nerve, caused by the bundles of myelin-coated axons, could be observed

clearly. With further technical improvements, PAM can potentially be applied to monitor and diagnose peripheral

neuropathies.

2014 Society of Photo-Optical Instrumentation Engineers (SPIE)

[DOI:

10.1117/1.JBO.19.1.016004

]

Keywords: photoacoustic microscopy; peripheral nerves; myelin; label-free imaging; optical absorption contrast.

Paper 130677R received Sep. 17, 2013; revised manuscript received Dec. 4, 2013; accepted for publication Dec. 5, 2013; published

online Jan. 6, 2014.

1 Introduction

Peripheral neuropathy is a common neurological problem that

affects 8% of people over the age of 55 and 2.4% of people over-

all.

However, it is often difficult to make objective, noninvasive

assessments of nerve fibers.

Nerve conduction studies are

currently the gold standard for diagnosis, but they cannot pro-

vide information on areas of the nerve distal to the injury and

electrophysiological parameters do not always correlate well

with axonal damage and regeneration.

The ability to visualize

nerves noninvasively and monitor them longitudinally could

greatly improve the diagnosis and treatment of peripheral nerve

diseases.

Numerous imaging modalities have been used to image

peripheral nerves: ultrasound,

magnetic resonance imaging

(MRI),

coherent anti-Stokes Raman spectroscopy (CARS),

–

and third-harmonic generation (THG) microscopy.

These

imaging techniques enabled visualization of individual periph-

eral nerves in the body and assisted functional studies of nerves.

However, neurological assessment remains challenging partly

due to the technical limitations of imaging. Ultrasound images

show peripheral nerves in negative contrast, which is nonspe-

cific. THG can detect signals specifically from myelin in nerves,

but it is limited by relatively low-excitation efficiency. Only

nerves within a few tens of microns in depth can be sensitively

detected. Although CARS affords a greater imaging depth than

THG, it is still limited by the need for nonlinear excitation. Most

other optical modalities rely on exogenous stains, which is a

major limitation for

in vivo

applications. MRI is both sensitive

and specific, but it cannot provide cellular resolution. Therefore,

a label-free, sensitive, specific, and high-resolution imaging

technique is still desired.

Optical-resolution photoacoustic microscopy (OR-PAM) is a

three-dimensional (3-D) imaging modality capable of measuring

endogenous optical absorption with a relative sensitivity of

100%.

–

By utilizing the wavelengths for peak absorption,

OR-PAM can image a biomolecule of interest with good

sensitivity and specificity without labeling. It has been used

to measure targets including hemoglobin, melanin, DNA, and

cytochromes at scales down to organelles.

Compared with

other optical microscopy techniques, OR-PAM, which uses

ultrasonic detection, has greater imaging depth as ultrasound

scatters much less readily in tissue. Given the above advantages,

we demonstrated OR-PAM for label-free imaging of peripheral

nerves by exciting lipids at an optical wavelength of 1210 nm.

2 Methods

The peripheral nerves were imaged using the OR-PAM system,

shown in Fig.

, that was previously described in Ref.

. The

system employed a tunable laser, composed of a diode-pumped

Q-switched Nd:YAG laser and an optical parametric oscillator

system (NT242-SH, Ekspla, Vilnius, Lithuania). The light beam

(5-ns pulse width, 1-KHz pulse repetition rate) was focused onto

the sample by a 10X

0.25 NA

objective (LMH-10X-1064,

ThorLabs, Newton, New Jersey), and the photoacoustic (PA)

waves generated by the laser pulses were detected using an ultra-

sonic transducer (40 MHz, 80% bandwidth). The acoustic sig-

nals were digitized and recorded by a computer. The PA

amplitude, proportional to the optical absorption, was calculated

from each A-line signal. Images were generated by two-dimen-

sional (2-D) raster scanning of the sample. For 3-D images,

depth information was obtained from the time-of-arrival of

the PA signals.

The lateral resolution of this system was evaluated by imag-

ing a 1951 United States Air Force resolution target (Fig.

). The

edge spread function (ESF) was estimated by averaging the edge

of one of the bars and was fitted to an error function (

0.998) based on the assumption that the beam profile was

†

These authors contributed equally to this work.

Address all correspondence to: Lihong V. Wang, E-mail:

lhwang@seas.wustl

.edu

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Gaussian. The point spread function (PSF) was then calculated

as the derivative of the ESF. The lateral resolution, defined as

the full-width half-maximum (FWHM) of the PSF, was

2.7

0.1

The axial resolution, determined by ultrasonic detection

rather than optical focusing, was estimated by the equation

0.88

∕

Δ

, where

is the speed of sound and

Δ

is the bandwidth of the transducer.

The calculated axial reso-

lution was 41

m. The axial resolution was also estimated by

measuring the FWHM of the envelope of the photoacoustic

pulse from a point target (not shown). The measured axial res-

olution was 48

The nerve samples consisted of sciatic nerves extracted from

Swiss-Webster mice (Hsd:ND4, Harlan Laboratories,

Indianapolis, Indiana). The mice were sacrificed prior to sur-

gery. Following extraction, the nerves were fixed in 10% neu-

tral-buffered formalin. Histological samples of the peripheral

nerves were obtained by embedding the nerves in paraffin, sec-

tioning them to 5

m in thickness, and mounting the sections

onto glass slides. Then, the slides were stained with luxol fast

blue, which highlights myelin, and cresyl violet, which high-

lights nuclei and Nissl bodies. The stained slides were imaged

using a bright-field microscope with a 20X

0.75 NA

objective

(NanoZoomer 2.0-HT, Hamamatsu, Hamamatsu City, Japan).

The origins of the optical absorption of nerves were exam-

ined using PA spectroscopy. The primary absorber was hypoth-

esized to be the lipid-rich myelin that surrounds most peripheral

nerves. The absorption of myelin is strongest in the near-infrared

region, where water, the most common molecule in tissue, how-

ever, is also a strong absorber.

3 Results and Discussion

To determine the optimal wavelength for nerve imaging, the

absorption coefficients of lipids and water

were compared

[Fig.

3(a)

]. There are three regions of positive contrast for lipids,

with peaks at 910, 1210, and 1720 nm. The measured PA signal

is proportional to the product of the absorption coefficient and

the optical fluence at the absorber. The fluence is limited by the

pulse energy of the laser at that wavelength and the ability to

focus light. Figure

3(b)

shows the output pulse energy as a func-

tion of wavelength for the laser used in the PA microscope. The

normalized contrast-to-noise ratio (CNR) versus optical wave-

length were calculated for several depths [Fig.

3(c)

]. Here, the

noise was assumed to be primarily electronic and thus constant

over the wavelength range. The contrast in relative units was

calculated as the product of the fluence at that depth and the

difference between the absorption coefficients of lipids and

water. The fluence, in turn, was calculated as the pulse energy

of the laser divided by the area of the diffraction-limited spot

size. The decay in the fluence with depth was calculated based

on the light absorption in a background consisting of 50% water

and 50% lipids. Scattering was ignored as it changes more

slowly with the wavelength. Among the three peaks, the CNR

at 1720 nm is the highest at the surface, but attenuates fastest

over the depth. The CNR at 1210 nm is higher than that at

1720 nm starting from approximately 1000

m in depth. The

CNR at 910 nm is the lowest at all depths. Therefore, the

1210-nm peak was selected for both the greatest CNR at

depth and the finer diffraction-limited spatial resolution com-

pared with the 1720-nm peak. In the future, measurements at

this wavelength could be combined with measurements at the

most negative contrast wavelengths for lipids (i.e., positive con-

trast for water) in order to further separate the contributions from

these two absorbers.

To validate that the PA image contrast is specific to myelin, a

PA image was obtained of a sectioned nerve sample. The image

was formed by taking the maximum amplitude projection

(MAP) for each A-line signal [Fig.

4(a)

]. Each pixel was then

normalized by the laser pulse energy. After the PA image was

acquired, the nerve section was stained with luxol fast blue, a

myelin-sensitive stain, and cresyl violet, a nuclei and Nissl

Fig. 1

Schematic of the photoacoustic microscope (PAM). A laser

pulse is attenuated by a neutral density (ND) filter, spatially filtered,

and then focused by the objective onto the nerve sample. Optical

absorption leads to the generation of photoacoustic waves, which

are measured using an ultrasonic transducer. An image is generated

by two-dimensional raster scanning of the sample.

Fig. 2

(a) PAM image of a region of a 1951 United States Air Force

resolution target. (b) Edge spread function (ESF) (dashed line) esti-

mated from the region denoted by the red box. The ESF was fitted to

the equation shown on the left, where

is the amplitude,

is the DC

offset,

is the horizontal axis,

0

is the position of the edge,

is the

standard deviation,

is the measured pressure, and erf denotes the

error function. The corresponding point spread function (solid line) is

also shown. Its full-width half-maximum is

2

7

0

1

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Matthews et al.: Label-free photoacoustic microscopy of peripheral nerves

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body-sensitive stain. This stained section was then imaged using

a bright-field microscope [Fig.

4(b)

]. The areas in blue denote

myelin. These two images share many features. To quantify the

similarity, the two images were scaled, smoothed, and coregis-

tered, and then the correlation coefficient

between them was

calculated to be 0.75. These results indicate that PAM can be

used to visualize myelin.

The source of contrast was also confirmed by examining the

PA spectrum of an excised nerve from 1140 to 1260 nm. This

spectrum was compared against the absorption spectrum of lip-

ids [Fig.

4(c)

]. The two spectra are in good agreement (

0.938), supporting the hypothesis that myelin, the primary

source of lipids in the nerves, is responsible for the PA signal.

An unsectioned,

“

whole

”

nerve was also imaged

ex vivo

using the PA microscope. A MAP image of the nerve, again

normalized by the laser pulse energy, is shown in Fig.

. The

wavy fibrous structure in the image is believed to be caused

by the bundles of myelin-coated axons that form the nerve fas-

cicles. The bright round structures may be surrounding fat

cells.

The image originally contained many bright, noise-like

spots, which were selectively and repetitively filtered in order

to enhance the inner structure of the nerve. The source of the

bright spots seen in the unsectioned nerve was uncertain, but

they were not observed in the sectioned nerve samples, perhaps

due to the tissue processing for histological staining.

A 3-D image of the nerve was also generated by taking the

Hilbert transformation of each A-line. A similar filtering process

was also applied. Video

steps through the image stack along

the depth direction. The depth is measured from the surface of

the nerve closest to the light source.

To better mimic the

in vivo

case, the unsectioned nerve sam-

ple was placed between two layers of chicken tissue. These

layers are used to simulate the situation where the nerve is

located some distance beneath the surface of the skin. The

layer of chicken tissue between the optical objective and

the sample was approximately 250-

m thick, and the layer

between the sample and the ultrasonic transducer was approx-

imately 400-

m thick. A 3-D image was generated as before.

Video

shows the frames from this image along the depth

direction.

Figure

shows one frame from this video. Even at depth, the

wavy structure of the nerve is still visible. Unfortunately, both

the water and lipids in the chicken tissue contributed signifi-

cantly to the background. Although the background reduced

the contrast of the image, the nerve can still be distinguished

by its ordered structure.

4 Conclusions

The first proof-of-concept measurements of peripheral nerves

using PAM were demonstrated. A good agreement was shown

between the PA images and the histology images as well as

between the PA spectrum and the known absorption spectrum

of lipids. The nerves were also imaged beneath a layer of

chicken tissue to simulate imaging the nerve at depth. Addi-

tional work is needed to improve the signal-to-noise ratio

beneath the surface and to allow

in vivo

in situ

images to be

Fig. 3

(a) The absorption coefficients of water and lipids versus wavelength. Three peaks of positive

contrast for lipids occur at 910 nm, 1210 nm, and 1720 nm. (b) The pulse energy of the laser measured

at each wavelength. (c) The normalized contrast-to-noise ratio as a function of wavelength estimated for

several depths: 0, 400, 800, and 1200

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acquired. Due to the difficulty of optically focusing in tissue,

imaging nerves more than a few millimeters deep using OR-

PAM could prove challenging. In those cases, a technique

that does not require optical focusing, such as acoustic-resolu-

tion photoacoustic microscopy,

could be used to target myeli-

nated nerves using this contrast mechanism. With further

developments, photoacoustic imaging could potentially be

used to monitor and diagnose peripheral neuropathies.

Acknowledgments

This work was sponsored in part by the National Institutes of

Health Grant Nos. DP1 EB016986 (NIH Director

’

s Pioneer

Award), R01 CA134539, and R01 CA159959. Lihong Wang

has a financial interest in Microphotoacoustics, Inc. and

Endra, Inc., which, however, did not support this work. Kon-

stantin Maslov has a financial interest in Microphotoacoustics,

Inc., which, however, did not support this work.

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Thomas Paul Matthews

is a PhD student in biomedical engineering

at Washington University in St. Louis. His research focuses on the

development of photoacoustic imaging systems for medical and bio-

logical applications.

Chi Zhang

is currently a PhD student studying biomedical engineer-

ing at Washington University in St. Louis, St. Louis, Missouri, USA. He

received his MS and BS in electrical engineering from Fudan

University, Shanghai, China. His research interests include the tech-

nical development and biomedical applications of photoacoustic

imaging.

Lihong Wang

holds the Gene K. Beare Distinguished Professorship

of Biomedical Engineering at Washington University in St. Louis. His

book titled

“

Biomedical Optics: Principles and Imaging,

”

one of the first

textbooks in the field, won the 2010 Joseph W. Goodman Book

Writing Award. He also edited the first book on photoacoustic tomog-

raphy. He has published 363 peer-reviewed journal articles and deliv-

ered 370 keynote, plenary, or invited talks. His Google Scholar h-

index and citations have reached 84 and over 28,000, respectively.

He is the Editor-in-Chief of the

Journal of Biomedical Optics

. He chairs

the annual conference on Photons plus Ultrasound, and chaired

the 2010 Gordon Conference on Lasers in Medicine and Biology

and the 2010 OSA Topical Meeting on Biomedical Optics. He serves

as the founding chair of the scientific advisory boards for two compa-

nies having commercialized photoacoustic tomography. He received

NIH

’

s FIRST, NSF

’

s CAREER, NIH Director

’

s Transformative

Research, and NIH Director

’

s Pioneer awards. He was awarded

the OSA C.E.K. Mees Medal, IEEE Technical Achievement Award,

and IEEE Biomedical Engineering Award for

“

seminal contributions

to photoacoustic tomography and Monte Carlo modeling of photon

transport in biological tissues and for leadership in the international

biophotonics community.

”

Biographies of the other authors are not available.

Journal of Biomedical Optics

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Matthews et al.: Label-free photoacoustic microscopy of peripheral nerves

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