Copyright

by

Bo Wang

2011

The Dissertation Committee for Bo Wang Certifies that this is the approved version

of the following dissertation:

Characterization of atherosclerotic plaques using ultrasound guided

intravascular photoacoustic imaging

Committee:

Stanislav Emelianov, Supervisor

Konstantin Sokolov

Richard Smalling

Silvio Litovsky

Andrew Dunn

Salavat Aglyamov

Characterization of atherosclerotic plaques using ultrasound guided

intravascular photoacoustic imaging

by

Bo Wang, B.S.; M.S.

Dissertation

Presented to the Faculty of the Graduate School of

The University of Texas at Austin

in Partial Fulfillment

of the Requirements

for the Degree of

Doctor of Philosophy

The University of Texas at Austin

May 2011

Dedication

To my parents and dear Chen-Guan.

For their love and support.

v

Acknowledgements

Looking back my Ph.D. study at UT-Austin, I am always amazed by how lucky I

was to have such great opportunity to have a research project that I love, an environment

that always gave me full support, and the greatest mentors I could ever imagine of. I

would like to thank my advisor Professor Stanislav Emelianov, for letting me joining his

lab and introducing me to intravascular photoacoustic imaging. It is his understanding,

unconditional support, and tolerance of my mistakes and disagreement that helped me

survived the Ph.D. journey. I would like to thank my committee members Dr. Konstantin

Sokolov, Dr. Richard Smalling, Dr. Silvio Litovsky, Dr. Andrew Dunn, and Dr. Salavat

Aglyamov for their guidance and acknowledgement of the value of my work. Dr.

Wolfgang Frey and Dr. Salavat Aglyamov gave me many valuable suggestions and

comments about this dissertation.

I would not be able to come this far without knowledge and experiences passed on

to me from senior lab members: Dr. Shriram Sethuraman – solid foundation for IVPA,

Dr. Srivalleesha Mallidi – PA and spectroscopic analysis, Dr. Andrei Karpiouk – lasers

and tricks for building stuffs, Dr. Suhyun Park – intravascular beam forming, Evgeniya

Yantsen – cell culture and biology. I was deeply touched by the devotion and passion for

research from James Amerian, my wonderful collaborator in Dr. Smalling’s research

team at Houston Health Science Center. I also received great help from fellow graduate

students from collaborating labs: Justina Tam helped me figure out the best way to

process tissue samples for ICP-MS; Evgeniya Yantsen was always cheerful and willing to

explore new territory with me; Pratixa Joshi helped me making nanoparticles; Dr. Haley

Finley-Jones and Isaac Arnquist from Dr. Holcomb’s lab in the Department of Chemistry

and Biochemistry helped me run ICP-MS. I would like to thank my lab members Dr.

vi

Carolyn Bayer, Dr. Iulia Graf, Dr. Kimberly Homan, Seungsoo Kim, Mohammad

Mehrmohammadi, Yun-Sheng Chen, Jason Cook, Jimmy Su, Seung-Yun Nam, Min Qu,

Soon Joon Yoon, Sangpil Yoon, Katie Wilson, Geoff Luke, Alex Hannah who are always

there whenever I needed help. I also would like to acknowledge the help from

undergraduate research assistants Rick Sweat and Tom Isaac, who prepared nanoparticles

for animal studies. Administrative assistant Tera Sherrard, and lab managers Christopher

Green and Katherine Bontrager were of great help for me with purchasing, scheduling,

and grammar check of documents. It was my honor to have been worked with these

excellent lab members as well as collaborators.

I would like to thank my parents who raised me and gave me the best of

everything that they can provide; and dear Chen-Guan, for the understanding and support

in the past four years.

vii

Characterization of atherosclerotic plaques using ultrasound guided

intravascular photoacoustic imaging

Publication No._____________

Bo Wang, Ph.D.

The University of Texas at Austin, 2011

Supervisor: Stanislav Emelianov

Rupture of atherosclerotic plaque is closely related to plaque composition.

Currently, plaque composition cannot be clinically characterized by any imaging

modality. The objective of this dissertation is to use a recently developed imaging

modality – ultrasound-guided intravascular photoacoustic (IVPA) imaging – to detect the

distribution of two critical components in atherosclerotic plaques: lipid and

phagocytically active macrophages. Under the guidance of intravascular ultrasound

imaging, spectroscopic IVPA imaging is capable of detecting the spatially resolving

optical absorption property inside a vessel wall. In this study, contrast in spectroscopic

IVPA imaging was provided by either the endogenous optical property of lipid or

optically absorbing contrast agent such as gold nanoparticles (Au NPs). Using a rabbit

model of atherosclerosis, this dissertation demonstrated that ultrasound guided

spectroscopic IVPA imaging could simultaneously image lipid deposits as well as

macrophages labeled in vivo with Au NPs. Information of macrophage activity around

lipid rich plaques may help to identify rupture-prone or vulnerable plaques. The results

viii

show that ultrasound guided IVPA imaging is promising for detecting plaque

composition in vivo. Clinical use of ultrasound guided IVPA imaging may significantly

improve the accuracy of diagnosis and lead to more effective treatments of

atherosclerosis.

ix

Table of Contents

List of Tables ........................................................................................................ xii

List of Figures ...................................................................................................... xiii

Chapter 1: Introduction .........................................................................................1

1.1 Motivation .................................................................................................1

1.2 Atherosclerosis and vulnerable plaques ....................................................3

1.3 Imaging of atherosclerosis ........................................................................6

1.3.1 Noninvasive imaging modalities...................................................6

1.3.2 Invasive imaging modalities .........................................................7

1.4 Ultrasound guided intravascular photoacoustic imaging ........................11

1.5 Animal models of atherosclerosis ...........................................................17

1.6 Organization of the dissertation ..............................................................19

1.6 References ...............................................................................................20

Chapter 2: Spectroscopic IVPA imaging of lipid deposits ....................................26

2.1 Introduction .............................................................................................26

2.2 Methods...................................................................................................27

2.2.1 Animal model..............................................................................27

2.2.1 Imaging system ...........................................................................27

2.2.2 Spectroscopic IVPA signal processing ................................................28

2.2.2.1 Spectroscopic analysis methods for photoacoustic imaging ....28

2.2.2.2 Slope based algorithm for spectroscopic analysis ...................30

2.2.2.3 Effect of wavelength dependent tissue property on spectroscopic

analysis ........................................................................................32

2.3 Spectroscopic IVPA imaging of lipid in a rabbit model of atherosclerosis35

2.4 Discussion and conclusion ......................................................................39

2.5 References ...............................................................................................42

Chapter 3: Plasmonic gold nanoparticles (Au NPs) as contrast agent for IVPA

imaging of phagocytically active macrophages ............................................45

3.1 Introduction .............................................................................................45

x

3.2 Au NPs as a contrast agent for photoacoustic imaging ...........................45

3.3 Imaging phagocytically active macrophages using Au NPs ...................47

3.3.1 Imaging system ...........................................................................47

3.3.2 In vitro cell experiment ...............................................................48

3.3.2.1 Plasmon resonance coupling of Au NPs in macrophages48

3.3.2.2 IVUS/IVPA imaging of cell phantom.............................50

3.3.3 Experiment using ex vivo tissue injected with Au NP-labeled

macrophages ...............................................................................55

3.4 Sensitivity of IVPA imaging to detect Au NP-labeled macrophages .....57

3.5 Viability of Au NP-labeled cells exposed to pulsed laser radiation .......59

3.6 Conclusion ..............................................................................................61

3.6 References ...............................................................................................61

Chapter 4: Detection of phagocytically active macrophages in a rabbit model of

atherosclerosis ...............................................................................................64

4.1 Methods...................................................................................................64

4.1.1 Imaging system ...........................................................................64

4.1.2 Synthesis and characterization of Au NPs ..................................68

4.1.3 Animal protocol ..........................................................................69

4.1.4 Isolation of mononuclear cells from whole blood ......................70

4.1.5 Analysis of gold concentration in tissue samples .......................70

4.2 Image processing ....................................................................................70

4.3 Results .....................................................................................................72

4.3.1 Imaging the distribution of phagocytically active macrophages in

atherosclerotic rabbit aortas ........................................................72

4.3.2 Imaging deposits of lipid in atherosclerotic rabbit aorta ............75

4.3.3 Simultaneous imaging of lipid deposits and phagocytically active

macrophages ...............................................................................77

4.4 Discussion ...............................................................................................79

4.4.1 Delivery pathways of Au NPs to phagocytically active macrophages

.....................................................................................................79

4.4.2 Size and shape dependent delivery of Au NPs ...........................80

xi

4.5 Conclusion ..............................................................................................83

4.6 References ...............................................................................................83

Chapter 5: Conclusion and future work .................................................................85

5.1 Summary of research ..............................................................................85

5.2 Limitations ..............................................................................................87

5.2.1 Animal model of atherosclerosis ................................................87

5.2.2 Ex vivo imaging of atherosclerotic plaques ................................87

5.2.3 Imaging speed .............................................................................88

5.3 Future directions .....................................................................................89

5.3.1 Detecting lipids using thermal IVPA imaging ............................89

5.3.2 Imaging lipid in vivo at 1720 nm wavelength .............................93

5.3.3 Designing integrated catheter for combined IVPA/IVUS imaging in

vivo ..............................................................................................95

5.3.4 Accurately detecting of vessel lumen borders ............................96

5.3.5 Imaging thrombus and vasa vasorum .........................................98

5.3.6 Engineering contrast agents for high sensitivity and specificity IVPA

imaging .......................................................................................98

5.3.7 Delivering contrast agents ...........................................................99

5.4 Conclusion ............................................................................................100

5.5 References .............................................................................................101

Bibliography ........................................................................................................104

xii

List of Tables

Table 3.1: Concentration of macrophages and Au NPs in arterial phantoms. ...57

Table 4.1: Au NPs injected in two balloon injured rabbits. ...............................80

xiii

List of Figures

Figure 1.1: (a) Vulnerable plaques in an artery. (b) Insufficient coverage of plaque

by a stent may lead to plaque rupture. (c) Accurate detection of

vulnerable plaques may provide better lesion coverage. ....................2

Figure 1.2: Different types of vulnerable plaques. (Adapted from Naghavi et. al.

(2003) [5]) ...........................................................................................4

Figure 1.3: Development of atherosclerotic lesion. Various biomarkers present at

different stages of the lesion. (Adapted from Sanz and Fayad (2008)

[12]).....................................................................................................5

Figure 1.4: A typical IVUS image processing procedure. Panel (a) is the flowchart

for processing IVUS images. Digitized radio frequency signal (b) is first

band-pass filtered (c). Then, filtered signal goes through envelope

detection (d), and is scan converted (e) to form an IVUS image

demonstrating a cross-section of a vessel. ..........................................8

Figure 1.5: IVUS images of healthy (a,b), and diseased (c-e) vessels. Panel (b) is

the zoomed-in image of panel (a). Panels (c-e) show images of vessels

containing soft (lipid-laden) plaques, mixed (fibrous and calcified)

plaques, and calcified plaques, respectively. (Adapted from Nissen and

Yock (2002) [21] ) ............................................................................10

Figure 1. 6: Theoretical acoustic pressure generated using a long laser pulse (a) and

an ultra-short laser pulse (b) from a spherical inclusion embedded in an

acoustically matched background. Pressure was received at a distance r,

equal to two times the inclusion radius a. (Adapted from Sun and

Gerstman (1999) [40]). .....................................................................13

xiv

Figure 1.7: Realization of combined IVPA and IVUS imaging using an integrated

IVPA/IVUS imaging catheter. (a) Longitudinal view of integrated

catheter inside the vessel lumen. Combined IVPA and IVUS imaging

can be performed in the overlapped region of the optical (red) and

acoustic beam (gray). (b) Cross-sectional view of the catheter and

vessel. ................................................................................................16

Figure 1.8: Optical absorption property of tissues in the vessel [48-49].............16

Figure 1.9: (a) IVPA, (b) IVUS, and (c) combined IVUS/IVPA 3D images of a

tissue mimicking phantom with an optically absorbing inclusion. ...17

Figure 2.1: Laboratory prototype of IVUS-guided multi-wavelength IVPA imaging

system. ..............................................................................................28

Figure 2.2: Image processing algorithm for analyzing multi-wavelength IVPA and

IVUS data..........................................................................................31

Figure 2.3: Wavelength dependent optical absorption and scattering parameters used

in the Monte Carlo simulation. .........................................................33

Figure 2.4: (a) Tissue structure used in Monte Carlo simulation to simulate the ex

vivo imaging experiment. (b) Absorbed laser energy at various depths of

the lipid layer. (c) Normalized laser energy absorption at various depths

of the lipid layer. ...............................................................................34

Figure 2.5: (a) Tissue structure used in Monte Carlo simulation to simulate in vivo

IVPA imaging. (b) Absorbed laser energy at various depths of the lipid

layer. (c) Normalized laser energy absorption at various depths of the

lipid layer. .........................................................................................35

xv

Figure 2.6: Cross-sectional (a,d) IVUS, (b,e) 1200-nm IVPA, and (c,f) combined

IVUS/IVPA images of the diseased and normal aorta. The IVUS and

IVPA images are displayed using a 40 dB dynamic range. ..............36

Figure 2.7: Cross-sectional IVPA images of (a) diseased and (b) normal aortas

obtained using 1200 nm wavelength. (c) Comparison of the wavelength-

dependent photoacoustic responses from the lipid-rich area of the

atherosclerotic plaque (region 1) and media-adventitial layer of diseased

(region 2) and normal (region 3) aortas. ...........................................37

Figure 2.8: Combined IVUS and spectroscopic IVPA images and corresponding

histological slices of the diseased atherosclerotic aorta (a-c) and normal

(i.e., control) aorta (d-e). Lipid-rich regions (orange color) were

identified from multi-wavelength photoacoustic imaging and displayed

over the IVUS images. Lipid-rich regions were detected in the thickened

intima layer of the diseased aorta (a) confirmed by Oil red O stain for

lipid (b) and H&E stain (c). In contrast, spectroscopic IVPA imaging (d)

and tissue histology (e and f) show insignificant lipid-rich regions in

normal rabbit aorta. Both normal and diseased aortas show some

insignificant deposits of lipid in the periadventitia. ..........................38

Figure 3.1: Intravascular photoacoustic (IVPA) and intravascular ultrasound (IVUS)

imaging system setup. .......................................................................48

Figure 3.2: (a) STEM image of Au NPs. (b) Darkfield reflectance images of murine

macrophages. (c) Murine macrophages loaded with Au NPs. The

darkfield optical images (b,c) were obtained using Xe illumination and a

20x darkfield objective (0.5 NA). .....................................................49

xvi

Figure 3.3: Normalized extinction spectra of Au NPs (dashed line) and macrophages

loaded with Au NPs (solid line). Both absorption spectra were

normalized with their corresponding maxima. .................................50

Figure 3.4: (a) Vessel mimicking phantom with four compartments. Different

compartment were injected with cells suspended in gelatin or gelatin

alone. (b) Cross-sectional view of the phantom................................51

Figure 3.5: The structure (a) and the IVUS image (d) of the tissue mimicking

phantom. The IVPA images of the same cross-section of the phantom

were taken at 532 nm wavelength (b) and 680 nm wavelength (e). The

combined IVUS and IVPA images of the phantom (c: 532 nm

wavelength and f: 680 nm wavelength) indicated the origin of the

photoacoustic responses in IVPA images. ........................................53

Figure 3.6: Strength of the photoacoustic signal at different wavelength measured

from the small regions containing macrophages loaded with Au NPs,

gelatin gel and PVA. Each spectrum is normalized to the maximum

signal strength from Au NPs loaded macrophages at 680 nm wavelength.

...........................................................................................................54

xvii

Figure 3.7: IVUS, IVPA and combined IVUS/IVPA images of a diseased rabbit

aorta injected with macrophages loaded with Au NPs. The IVUS image

(panel (a)) is displayed using a 50 dB dynamic range. The injected

macrophages in the outer and inner regions of the aorta are denoted in

the images (a, b, e) with green arrows. The normalized IVPA images

(panels (b)-(d)) and combined IVUS/IVPA images (panels (e)-(g))

obtained using 700 nm, 750 nm and 800 nm wavelengths are displayed

using 20 dB display dynamic range. The IVPA and combined

IVUS/IVPA images taken at 700 nm wavelength (panels (b) and (e))

showed high photoacoustic signals at the injected regions denoted by

arrows. ...............................................................................................56

Figure 3.8: IVUS images (a,d), IVPA images (b,e) and combined IVPA/IVUS

images (c,f) of the vessel phantoms with plaque mimicking

compartments. IVUS images are displayed using a 40 dB dynamic

range. IVPA images, obtained using 680 nm wavelength, are displayed

using a 20 dB dynamic range. ...........................................................59

Figure 3.9: Viability of macrophages loaded with NPs and irradiated with 50 pulses

at 680 nm wavelength: a) cells remain viable after irradiation at laser

fluencies reaching 114 mJ/cm2, b) cell death was observed for 344

mJ/cm2 laser fluence. To cover the extent of the laser beam, the image

in Figure 3.9(b) was assembled from several optical images due to the

limited field of view of the optical microscope. ...............................60

Figure 4.1: Setup for the bench-top combined IVUS/IVPA imaging system. ....65

Figure 4.2: User interface of the combined IVUS/IVPA imaging system. .........66

Figure 4.3: Flow chart for spectroscopic IVUS/IVPA data acquisition. .............67

xviii

Figure 4.4: User interface of a custom developed program to control laser systems.

...........................................................................................................68

Figure 4.5: STEM image of Au NPs. ..................................................................69

Figure 4.6: Imaging processing algorithm for spectroscopic IVPA and IVUS

images. ..............................................................................................70

Figure 4.7: (a) Gold concentration in the blood after 20 nm diameter spherical

PEGylated Au NPs were intravenously injected into the rabbit. The

dashed line is an exponential fit. (b) The spectroscopic photoacoustic

response was different for regions containing Au NP-labeled

macrophages and the region containing blood. (c,f), Combined

spectroscopic IVPA and IVUS images (scale bar 0.5 mm) demonstrated

the location of Au NP-labeled macrophages in the atherosclerotic

plaques. Spectroscopic IVPA images of Au NP-labeled macrophages

were color coded in green, while IVUS images were shown in gray

scale. Corresponding histochemistry stains were shown to the right of

each image. (d,g), Silver stain for nanoparticles. (e,h), RAM11 stain for

macrophages. ....................................................................................74

Figure 4.8: Distribution of Au NPs within the vessel wall. Au NPs are present in or

around the vasa vasorum embedded in the adventitia. .....................75

xix

Figure 4.9: IVPA imaging of lipid. (a) Normalized spectroscopic photoacoustic

signal amplitude from different regions of the vessel wall. For the lipid-

rich region, the signal decreased with increased wavelength, while the

normal vessel had a relatively flat spectroscopic response. (b,d)

Combined spectroscopic IVPA and IVUS images of one cross-section of

the vessel wall. Spectroscopic IVPA images of lipid deposits were color

coded in red, while IVUS images were displayed in gray scale. Scale

bars are 0.5 mm. (c,e) Corresponding Oil red O stain for lipid. .......76

Figure 4.10: An artifact in spectroscopic IVPA imaging of lipid deposits. (a)

Combined spectroscopic IVPA image of lipid. Because of the

misalignment between the laser beam and the IVUS transducer, no lipid

shows up to the right of the aorta sample. (b) Oil Red O stain of the

adjacent cross-section showed a circumferential lipid-rich intimal layer.

...........................................................................................................77

Figure 4.11: 3D IVPA simultaneous imaging of macrophages and lipid. (a,b) Cross-

sectional view of IVUS/spectroscopic IVPA images revealing both Au

NP-labeled macrophages (green) and lipid (red) in atherosclerotic

plaques. (c-h), Reconstructed 3D images showing the distribution of Au

NP loaded macrophages (b,f), lipid (c,g) and macrophages and lipid

together (d,h). The yellow regions in figures (d,h) resulted from the

overlay of green (macrophages) and red (lipid). ...............................78

Figure 4.12: Dark-field image of mononuclear cells separated from a rabbit blood

sample 6 hours after contrast agent administration. Some of the cells

were labeled by Au NPs (arrows). ....................................................79

xx

Figure 4.13: Gold concentration in rabbits injected with 20 nm (Rabbit 1) and 50 nm

(Rabbit 2) spherical PEGylated Au NPs. ..........................................81

Figure 4.14: Bio-distribution of gold in rabbits injected with 20 nm (a) and 50 nm (b)

spherical PEGylated Au NPs. ...........................................................82

Figure 5.1: (a) Oil red O stain for lipid, and (b) H&E stain were performed in tissue

slices adjacent to the imaged cross-section. (c) IVUS image of the aorta.

(d) Combined IVUS and IVPA image acquired at 25 oC. (e)

Temperature dependent photoacoustic responses from plaques and

vessel wall. ........................................................................................91

Figure 5.2: Image processing algorithm to generate combined IVUS and lipid image

of the aorta. .......................................................................................92

Figure 5.3: (a) Lipid image generated by temperature dependent IVPA imaging

overlaid onto IVUS image to demonstrate the distribution of lipid in an

atherosclerotic rabbit aorta. (b) Spectroscopic IVPA image of lipid at the

same cross-section of the aorta. ........................................................93

Figure 5.4: (a-c) IVUS, IVPA, and combined IVPA/IVUS images taken at 1210 nm

wavelength. (d-f) IVUS, IVPA, and combined IVPA/IVUS images taken

at 1720 nm wavelength. The IVUS and IVPA images are shown at a

35 dB dynamic range. .......................................................................94

Figure 5.5: (a) Photo of the distal end of the integrated catheter. (b) Tissue

mimicking phantom with three optical absorbing inclusions. (c) IVUS

image of the phantom. (d) IVPA image of the phantom. (e) Combined

IVPA/IVUS image of the phantom. ..................................................96

xxi

Figure 5.6: IVUS (a), IVPA (b), and combined IVUS/IVPA (c) images of an

atherosclerotic rabbit aorta acquired at 900 nm wavelength using an

integrated IVUS/IVPA imaging catheter. The aorta was embedded inside

30% whole blood. .............................................................................97

1

Chapter 1: Introduction

1.1 MOTIVATION

Coronary atherosclerosis is the cause of the majority of ischemic heart disease.

Disruption of vulnerable plaques in the coronary arterial wall leads to acute coronary

syndromes such as myocardial infarction [1-3]. Clinically available intravascular imaging

modalities are capable of imaging the degree of stenosis. However, because the

vulnerability of plaques is strongly related to plaque composition, information on the

distribution of plaques and the degree of stenosis is not sufficient for effective treatment

of the disease. For example, angiography and IVUS guided stent placement based on the

degree of stenosis may lead to insufficient coverage of the lesion, and vulnerable plaques

without proper stent coverage may rupture (Figure 1.1). Carotid atherosclerosis treatment

also requires plaque vulnerability assessment to choose proper treatment strategy: carotid

angioplasty and stenting or carotid endarterectomy [4]. Therefore, clinical practice

requires real time high resolution imaging of plaque composition.

Atherosclerosis is driven by complex systemic interactions at the molecular and

cellular level. Information such as how the monocytes migrate into the plaques or when

and how the neovasculatures progress in the plaques are critical for understanding the

pathology as well as disease management. Though histopathological analysis can point

out the distribution of molecular or cellular components inside plaques, it does not allow

longitudinal tracking the biomarkers.

The use of nanotechnology in cardiovascular imaging can be a breakthrough in

the molecular imaging of atherosclerosis. Because atherosclerotic vessels have a leaky

endothelium, the nanometer size of particles presented a unique opportunity to analyze

the permeability of endothelium in vivo. Nanoparticles can also be engineered to target

2

disease related molecules or cells to enable molecular/cellular imaging. In order to

observe the distribution of nanoparticles, high sensitivity and resolution imaging

modalities are required.

Figure 1.1: (a) Vulnerable plaques in an artery. (b) Insufficient coverage of plaque by a

stent may lead to plaque rupture. (c) Accurate detection of vulnerable

plaques may provide better lesion coverage.

In this work, ultrasound guided intravascular photoacoustic (IVPA) imaging was

developed to meet the clinical and fundamental research needs for diagnosis and

treatment of atherosclerosis. Ultrasound guided IVPA imaging can image tissue

composition inside the atherosclerotic plaques as well as detect cells enhanced by

IVPA /IVUS guided

Large necrotic core

Angiography or IVUS-guided stent deployment

IVPA/IVUS-guided stent deployment

(a)

(b)

(c)

3

contrast agents. The real-time, high resolution combined IVPA/IVUS images would

improve the management of atherosclerosis.

1.2 ATHEROSCLEROSIS AND VULNERABLE PLAQUES

Atherosclerosis, literally meaning hardening of the artery, is characterized by the

build-up of plaques in the vessel wall. It is the cause of the majority of cardiovascular

events [2]. Atherosclerotic plaques take decades to build up in human vessels, and

generally have a systemic distribution in a number of different types of arteries [2].

Plaques located in specific locations such as the aortic arch, carotid bulb and coronary

arteries are more critical, because these arteries transport blood to the brain or

myocardium. Plaques may cause stenosis, the narrowing of the vessel lumen, thus

obstructing the blood flow. Although vessels may adapt to stenosis through positive

vessel remodeling by increasing the overall vessel diameter, sometimes such local

adjustment is not enough to relieve the stenosis. Severe stenosis formed in the coronary

arteries may cause life-threatening myocardial infarction.

Unstable plaques will eventually rupture due to high shear stress and release their

internal contents into the blood stream. Rupture sites in the coronary arteries may form

thrombus, and have a high likelihood to cause acute coronary syndromes [1]. Meanwhile,

plaque fragments from ruptured plaque may block small diameter arteries downstream

(e.g. cerebrovascular system) causing stroke.

Vulnerable plaques are thrombosis-prone plaques and plaques with a high

probability of undergoing rapid progression [5]. Through histochemistry staining of the

autopsy samples, we learned that atherosclerotic plaques may consist of many

components including lipids, fibrous tissue, calcifications, erythrocytes, macrophages,

4

platelets, etc. [3, 5-6]. It has been acknowledged that vulnerability of plaques was less

related to the degree of stenosis, but more determined by the composition of the plaques

[1] (Figure 1.2). For example, a soft lipid-rich plaque covered with a thin fibrous cap is

more prone to rupture and more vulnerable than a fibrous plaque with a relatively high

degree of stenosis [1, 7].

Figure 1.2: Different types of vulnerable plaques. (Adapted from Naghavi et. al. (2003)

[5])

Microscopically, complex interactions at the molecular and cellular level drive the

development of atherosclerosis (Figure 1.3). The atherosclerotic lesion in the arterial wall

may be triggered by the high cholesterol level in the blood stream, or the chemical or

mechanical damage of the endothelium [8]. In the very early stage of the lesion, low

density lipoprotein (LDL) particles enter the vessel wall from circulating blood through

dysfunctional or leaky endothelium. Meanwhile, the endothelium is over expressing

adhesion molecules. As a result, monocytes are recruited into the vessel wall and evolve

into macrophages. Phagocytically active macrophages internalize modified LDL particles

and become foam cells. The apoptosis or necrosis of foam cells forms soft lipid cores in

plaques [9]. As a self stabilizing process, the number of smooth muscle cells increases

5

inside the plaque, and a fibrous cap is formed covering lipid cores. Lipid fed

macrophages degrade the extra-cellular matrix by secreting matrix metalloproteinase

(MMPs), causing the plaques to be unstable. Advanced plaques also show high density of

neo-vasculature (vasa vasorum) [10-11] expressing αvβ3-integrin [12]. Imaging specific

biomarkers that are critical for the development of the disease can help the understanding

of the pathogenesis of the disease, locate the vulnerable plaques, and reveal the stage of

the disease. In order to enhance the contrast for the biomarkers, in most cases, a contrast

agent must be introduced.

Figure 1.3: Development of atherosclerotic lesion. Various biomarkers present at

different stages of the lesion. (Adapted from Sanz and Fayad (2008) [12]).

6

1.3 IMAGING OF ATHEROSCLEROSIS

Non-invasive imaging modalities such as magnetic resonance imaging (MRI),

computed tomography (CT), and ultrasound are generally used for screening purpose:

identify the population that is at high risk for cardiovascular or cerebrovascular events.

Catheter based intravascular imaging modalities are used in catheterization labs to guide

the interventional procedures.

1.3.1 Noninvasive imaging modalities

MRI and CT have the advantage of whole body imaging. Based on the intrinsic

differences in the relaxation property of tissues, multicontrast MRI imaging can

differentiate among lipid core, fibrous matrix, hemorrhage/thrombus, and calcification

[13]. The major challenge for MRI imaging of plaques is its limited spatial resolution

especially when imaging arteries located deep inside the body (e.g. coronary arteries)

[14]. MRI also suffers from motion artifacts caused by body movement. CT is sensitive

to calcifications in the plaque. The calcium score that is calculated from CT images may

be used to predict the risk factor in coronary heart disease [15]; however, patients are

subject to radiation during CT scan.

MRI, CT and single positron emission tomography (SPECT) are widely used for

imaging contrast agents that are targeted to biomarkers of atherosclerosis [12, 16-17].

These imaging modalities have the advantage of imaging the systemic distribution of

contrast agents in the blood vessel. However, the images generally have a low resolution.

The small vessel diameter, tortuosity and especially the continuous movement of the

coronary arteries challenge the design of these whole-body imaging systems.

7

Ultrasound imaging can provide real time images of the superficial vessel, for

example carotid arteries. Intima-media thickness of the carotid artery measured by

ultrasound was considered to be correlated with cardiovascular risk [18]. However, recent

clinical trials demonstrated that this might not be true [19]. Atherosclerosis in carotid

arteries is closely related to cerebrovascular risk. Ultrasound can image the plaque

distribution near the carotid bulb. Analysis of functional parameters such as shear stress

can identify the rupture-prone regions. Using microbubbles as contrast agents, ultrasound

can detect the neovascularization in carotid plaques [20].

1.3.2 Invasive imaging modalities

X-ray angiography is the most widely used imaging modality in catheterization

labs. In coronary angiography, a radio-opaque contrast agent is injected locally into an

artery with a catheter. The arterial network is imaged in real-time with X-ray imaging.

Using angiography, stenotic sites can be clearly visualized. However, because

angiography projects the 3D arterial network into 2D silhouette, errors are introduced

when estimating the vessel lumen narrowing [21].

Compared to non-invasive and whole body imaging modalities, catheter based

invasive imaging modalities generally provide images with the high resolution that is

necessary for imaging coronary plaques.

IVUS has become an important catheter based, real-time invasive imaging

modality facilitating the diagnosis of atherosclerosis. IVUS provides a relatively high

resolution morphologic image of the vessel’s cross-section. Coronary IVUS transducers

are generally operating in the frequency range from 20 MHz to 60 MHz, which provides

an axial resolution from 30 µm to several hundred micrometers. The ultrasound

transducer located at the tip of the IVUS imaging catheter radiates an acoustic beam

8

towards the vessel wall, and thereafter receives the backscattered acoustic wave. After

rotating the acoustic beam 360o, reflected acoustic waves from one cross-section of the

vessel are acquired. Clinically, two types of imaging catheters are used: single element or

array based. The difference is that the former catheter mechanically rotates the acoustic

beam while the latter rotates the beam electrically.

In a typical IVUS imaging system, the acquired radiofrequency (RF) signals are

first digitized and filtered according to the central frequency of the transducer. Signal

envelopes are then scan converted to form an IVUS image (Figure 1.4). From IVUS

images, the degree of stenosis and the area of large plaques can be measured. IVUS can

also image vessel remodeling and monitor restenosis in stent deployed vessels, which are

critical information for interventions and hard to be accomplished solely by angiography

[21].

Figure 1.4: A typical IVUS image processing procedure. Panel (a) is the flowchart for

processing IVUS images. Digitized radio frequency signal (b) is first band-

pass filtered (c). Then, filtered signal goes through envelope detection (d),

and is scan converted (e) to form an IVUS image demonstrating a cross-

section of a vessel.

Band-pass filter

Digitized IVUS RF signals

Envelope detection

Scan conversion

IVUS image

100 200 300 400 500 600 700 800

-1.5

-1

-0.5

0

0.5

1

x 104

Am

plit

ud

e o

f ultra

sou

nd

sig

nal (a

.u.)

Data points0 200 400 600 800 1000

-2

-1.5

-1

-0.5

0

0.5

1

1.5x 10

4

Data points

Am

plit

ud

e o

f ultra

sou

nd

sig

nal (a

.u.)

0 200 400 600 800 10000

0.5

1

1.5

2x 10

4

Data points

Am

plit

ud

e o

f u

ltra

so

und

sig

na

l (a

.u.)

(a)

(b) (c) (d) (e)

9

Certain tissue types in atherosclerotic plaques can be identified from IVUS

images based on contrast in acoustic impedance (Figure 1.5). Lipid-laden plaques are

hypo-echoic in IVUS images (Figure 1.5(c)). Calcified and fibrous plaques produce

hyper-echoic signals, and may cause shadowing effects behind the plaque (Figure

1.5(d,e)) [21-22]. However, comparison of the acoustic signal strengths cannot reliably

differentiate calcified plaques from dense fibrous plaques, or lipid-rich plaques from

plaques mixed with lipid and fibrous tissue [23]. Researchers tried to extract the tissue

dependent spectral information hidden from the traditional grayscale IVUS images.

Based on 8 spectral signatures extracted from the IVUS signal acquired from 30 MHz

single element transducer, Nair et al. [23] classified the coronary plaques into four

categories (fibrous, fibrolipidic, calcified and calcified-necrotic). Later, Valcano Inc.

incorporated a similar classification method into its 20 MHz array catheter based IVUS

imaging system, and named it Virtual HistologyTM

[24]. In several clinical trials, Virtual

histology IVUS (VH-IVUS) showed improved accuracy of plaque characterization than

IVUS alone [25]. However, due to the variations in spectral responses of each individual

IVUS catheter, extracted spectral features may not be consistent. Moreover, due to the

limited spectral bandwidth of IVUS transducers, there may not be significant spectral

differences between various tissue types [26]. Recently, Thim et al. found that the

necrotic core size determined by VH-IVUS in vivo in atherosclerotic pigs did not

correlate with the histology results [27]. Therefore, in vivo plaque characterization using

spectral IVUS information needs further validation.

10

Figure 1.5: IVUS images of healthy (a,b), and diseased (c-e) vessels. Panel (b) is the

zoomed-in image of panel (a). Panels (c-e) show images of vessels

containing soft (lipid-laden) plaques, mixed (fibrous and calcified) plaques,

and calcified plaques, respectively. (Adapted from Nissen and Yock (2002)

[21] )

Catheter based optical imaging can provide morphological or compositional

information of plaques. Because of the exponential attenuation of optical fluence inside

tissue, luminal blood needs to be removed during imaging by flushing saline or another

optically transparent fluid through the artery. Intravascular angioscopy allows direct

optical visualization of the color and morphology of plaque [28]. Intravascular Raman

spectroscopy can identify the chemical composition by the shift of the optical spectrum

[29]. NIR spectroscopy can image the absorption property of tissue at the presence of

luminal blood [28]. The disadvantages of these optical methods are that the images are

not spatially resolved, and imaging depth is often not sufficient for a reliable assessment

of the plaque.

Intravascular optical coherence tomography (OCT) is an optical imaging modality

capable of spatially resolved imaging of the vessel wall with very high resolution of

several micrometers [30]. Because OCT imaging is based on the coherence of light,

luminal blood needs to be removed during imaging. Frequency domain intravascular

OCT significantly increased the frame rate up to 108 frames/sec [31]. The lipid core can

be imaged based on the higher light attenuation of the lipid [32]. Due to the high spatial

(a) (b) (c) (d) (e)

11

resolution of OCT images, the thickness of fibrous caps in plaques can be accurately

measured. Thin-cap fibroatheroma (TCFA) is defined as a thin fibrous cap (<65 µm in

thickness) covering a large lipid core in a plaque. Intravascular OCT is capable of

identifying TCFA in human coronaries in vivo [33]. A high concentration of

macrophages can also be imaged based on their high intensity in the OCT images [34].

However, because light loses its coherence in deeper tissues, OCT imaging of

atherosclerosis is limited by its 1-2 mm penetration depth. Therefore, the imaging range

of intravascular OCT is not sufficient to cover the region of plaques, and cannot evaluate

the morphology or tissue composition deep inside the plaque.

Because of lacking imaging contrast, contrast agents need to be introduced in

order to image disease related biomarkers (Figure 1.3). Intravascular modalities promise

a high resolution, close up view of the contrast agents. Multiple optically absorbing

contrast agents such as quantum dots, gold or silver nanoparticles, carbon nanotubes, and

fluorescent dyes are designed for intravascular optical based imaging modalities. These

particles can be tuned to specific absorbing wavelengths to minimize the background

signal. Imaging platforms such as photoacoustic imaging or fluorescent lifetime imaging

are capable of detecting these contrast agents [35].

1.4 ULTRASOUND GUIDED INTRAVASCULAR PHOTOACOUSTIC IMAGING

Photoacoustic (optoacoustic) signals are acoustic signals generated as a result of

light irradiation. Photoacoustic signals may be generated through various mechanisms,

including electrostriction, optical breakdown, radiation pressure, thermal expansion or

photochemical processes [36-38]. The mechanism for photoacoustic signal generation is

determined by the power density of light and the optical property of the object. In the

12

scope of biomedical imaging, photoacoustic signals are generated through thermal

expansion after laser irradiation.

Photoacoustic signal generation through thermal expansion can be demonstrated

from [39]:

2 22

2 2 2 2

1 ( , )( , ) ,

s s

T r tp r t

v t v t

(1.1)

where ( , )p r t denotes the acoustic pressure at location r and time t ; T denotes the

temperature; sv denotes the speed of sound; is the thermal expansion of volume

expansion; is the isothermal compressibility. The efficiency of photoacoustic signal

generation through thermal expansion depends on the laser pulse duration in the

relationship with the thermal and stress relaxation time. If the laser pulse duration 0 is

significantly shorter than the thermal and stress relaxation time, the heat generated by

optical absorption does not have time to diffuse out of the heated region during the laser

pulse. Then the maximum initial photoacoustic pressure has the following form:

2

0 ,eff effz zsa a

p

vp Fe Fe

C

(1.2)

where a is the optical absorption coefficient of the inclusion, F is the laser fluence,

eff is the effective attenuation coefficient of light inside the object, is the

Grüeneisen coefficient characterizing the efficiency of photoacoustic generation for a

type of tissue, and z is the depth.

Assuming a homogeneous spherical optical absorber was embedded inside a

homogeneous back ground, the acoustic impedance and speed of sound are matched

between the inclusion and the background. Without satisfying the stress confinement,

13

photoacoustic signal received outside of the absorber has two separated parabolic

shaped signals that are in opposite phases (Figure 1.6(a)) [40]. When the laser pulse

duration satisfies the stress confinement, the photoacoustic signal received outside of the

inclusion has an “N” shape (Figure 1.6(b)) [40].

Figure 1.6: Theoretical acoustic pressure generated using a long laser pulse (a) and an

ultra-short laser pulse (b) from a spherical inclusion embedded in an

acoustically matched background. Pressure was received at a distance r,

equal to two times the inclusion radius a. (Adapted from Sun and Gerstman

(1999) [40])

In photoacoustic imaging, usually a nanosecond duration pulsed laser system is

used. This means that the laser pulse duration satisfies both the thermal and stress

confinements for biological tissue. The photoacoustic signal amplitude can be calculated

using Equation (1.2). The time interval between the positive peak and negative peak of

the “N” shaped photoacoustic signal equals the diameter of the optical absorbing sphere

[41]. The photoacoustic signal amplitude under stress and thermal confinement is

proportional to a tissue dependent dimensionless parameter Γ, the optical absorption

coefficient of tissue, and laser fluence. Because speed of sound ( c ), the thermal

(a) (b)

14

coefficient of tissue expansion ( ), and specific heat ( pC ) are temperature dependent,

Γ varies with temperature. At a constant temperature, if the laser fluence is known, the

optical absorption coefficient of tissue can be calculated. Therefore, photoacoustic

imaging detects contrast based on the optical absorption property of tissue.

A photoacoustic signal generated with ultra-short laser pulses is a broad-band

radiofrequency signal. To preserve the shape and amplitude of the original

photoacoustic signal, transducers with large bandwidth and high sensitivity would be

ideal. Polyvinylidene fluoride (PVDF) membrane hydrophones or transducers designed

with broad receiving bandwidth are used for receiving the photoacoustic signals [42].

An optical delivery system is critical for the design of photoacoustic imaging

systems. Because of the exponential decay of laser energy inside biological tissue, laser

fluence should be strong in order to achieve a large imaging depth and high sensitivity.

The design of the optical system has to balance between the requirement of maximum

exposure of laser energy over the tissue and achieving maximum fluence at the imaging

region deep inside the tissue. One solution is to focus light inside the tissue, which has

been utilized both for single element and array based photoacoustic imaging systems [43-

44].

Synergy of a photoacoustic and a conventional ultrasound system is beneficial.

Photoacoustic images are based on the optical absorption contrast, while ultrasound

images visualize the anatomy of the tissue which is often lacking in photoacoustic images

[45]. Moreover, because photoacoustic signals are fundamentally acoustic signals, the

combination of the two imaging modalities requires little hardware modification of a

traditional ultrasound imaging system. Photoacoustic and ultrasound imaging can share

the same data acquisition and digital signal processing hardware, which happen to be the

most expensive parts in a conventional ultrasound imaging system. Photoacoustic

15

imaging probe can be manufactured by integrating the light delivery system with the

ultrasound transducer. Therefore, combined photoacoustic and ultrasound imaging can

provide both the functional and anatomical information of the tissue, and can be achieved

relatively economically.

Most of the conventional ultrasound imaging systems use piezoelectric material

for ultrasound transducers. Piezoelectric transducers (PZT) have narrower bandwidths

than PVDF transducers, and low receiving sensitivity. Therefore, PZT may not be very

efficient for receiving photoacoustic signals. However, PZT has high acoustic generation

efficiency, which is beneficial to traditional ultrasound imaging. The tradeoff of

sensitivity between photoacoustic and ultrasound imaging need to be considered in the

design for the combined photoacoustic and ultrasound imaging system.

IVPA is an extension of photoacoustic imaging used in intravascular imaging

application. In IVPA imaging, an integrated catheter is introduced into the vessel lumen

(Figure 1.7). The integrated catheter is capable of delivering a laser beam towards the

vessel wall and at the same time performing conventional IVUS imaging. The laser

system is synchronized with the conventional IVUS data acquisition so that

photoacoustic signals can be acquired together with the ultrasound signal at each imaging

angle [46]. Image processing procedures for IVPA imaging is similar to conventional

IVUS imaging (Figure 1.4). The IVPA and IVUS images generated from the imaging

system are co-registered. From IVPA images, information about tissue composition can

be extracted based on characteristic optical absorption spectra of tissue (Figure 1.8) [47].

The co-registered IVUS image demonstrates the location of the photoacoustic signal

source.

16

Figure 1.7: Realization of combined IVPA and IVUS imaging using an integrated

IVPA/IVUS imaging catheter. (a) Longitudinal view of integrated catheter

inside the vessel lumen. Combined IVPA and IVUS imaging can be

performed in the overlapped region of the optical (red) and acoustic beam

(gray). (b) Cross-sectional view of the catheter and vessel.

Figure 1.8: Optical absorption property of tissues in the vessel [48-49].

Lipid

MacrophageAu NPs

(a) (b)

200 400 600 800 1000 1200

10-2

100

102

Wavelength (nm)

Abso

rptio

n c

oeffic

ient (c

m-1

)

Hb

HbO2

Fat

Fatty Acid

Water

Intima

Media

Adventitia

17

IVUS guiding is important in IVPA imaging. IVPA images only show optical

absorbing components in the plaques, while IVUS reveals the structure of the vessel. By

combining co-registered IVUS and IVPA images, morphology and composition

information can be determined in a single image. In Figure 1.9, a vessel mimicking

phantom with an optically absorbing inclusion embedded inside the phantom wall was

imaged by a bench top combined IVUS/IVPA imaging system. IVPA image (Figure

1.9(a)) only shows the inclusion, while IVUS image (Figure 1.9(b)) only shows the

structure of the phantom. Combined IVUS/IVPA image (Figure 1.9(c)) demonstrates the

relative position of the inclusion inside the phantom.

Figure 1.9: (a) IVPA, (b) IVUS, and (c) combined IVUS/IVPA 3D images of a tissue

mimicking phantom with an optically absorbing inclusion.

1.5 ANIMAL MODELS OF ATHEROSCLEROSIS

Animal models are important for studying the progression and treatment of

atherosclerosis. The ideal animal model should grow diffuse plaques, with the same

morphology, composition and molecular responses as human plaques. Unfortunately, no

animal model can completely simulate human atherosclerotic plaques. Rabbit models of

(b)(a) (c)

18

atherosclerosis have been extensively used for invasive imaging studies because of their

cost effectiveness and their aorta artery is of similar size to human coronary arteries.

Two types of NZW rabbit models were created: rabbits which had undergone

balloon injury on the aorta and were subjected to high a cholesterol diet, and rabbits on a

long term low cholesterol diet. Cholesterol chow dramatically increases blood LDL levels

in NZW rabbits, which will induce plaque formation in the arterial wall. Mechanical

injury over the artery can accelerate the disease progress. Plaques created by balloon

injury are rich in macrophages [51], and have a high density of vasa vasorum [52]. This

type of plaque can build up in several months. On the other hand, plaques created by a

long term low cholesterol diet are rich in lipids, and usually of a higher degree of stenosis

compared to balloon injured ones. This type of plaque takes over 10 months to build up.

Both types of NZW rabbit models have been extensively used in the study of molecular

imaging with MRI, CT, and PET [51, 53-54]. The disadvantages of NZW rabbit models

are 1) the distribution of the plaques mainly locates in the aorta or iliac arteries; 2) plaque

composition is simpler in comparison to human atherosclerotic plaques; 3) biomarkers

are fewer than in human plaques.

The WHHL rabbit is another widely used rabbit model in atherosclerosis studies.

WHHL rabbits have high LDL levels in blood due to the deficiency of LDL receptors,

and will spontaneously develop atherosclerosis in the aorta and coronary arteries [55].

Within 12 to 18 months of age, severe plaques are developed in the WHHL rabbits. The

atherosclerotic plaques developed by WHHL rabbits are morphologically similar to

human plaques and therefore are considered a better model of human atherosclerosis than

the NZW rabbit model.

19

1.6 ORGANIZATION OF THE DISSERTATION

The dissertation is focused on detecting lipid deposits and macrophages in

atherosclerotic plaques. Lipids and macrophages are not only involved in the

development of atherosclerosis, but more importantly, the distribution of these two

components may indicate the rupture prone regions in the plaques.

Based on the endogenous optical absorption contrast, Chapter 2 demonstrates that

lipid deposits can be detected by spectroscopic IVPA imaging. Fatty acids are present in

all kinds of lipid particles, and have a unique optical absorption peak around 1210 nm

wavelength. After acquiring multi-wavelength IVPA images around the 1210 nm

absorption peak, a slope based spectroscopic analysis was used to identify lipids in an

atherosclerotic rabbit aorta. This work has been published in Optics Express (Detection

of lipid in atherosclerotic vessels using ultrasound-guided spectroscopic intravascular

photoacoustic imaging, vol. 18, pp. 4889-4897, 2010).

Chapter 3 and Chapter 4 are focused on molecular imaging of macrophages in

atherosclerosis using gold nanoparticles (Au NPs) as a contrast agent. Chapter 3

describes that Au NPs can be used as contrast agents for IVPA imaging to image

phagocytically active macrophages. Both in vitro cell phantom and ex vivo tissue

experiments demonstrated that IVPA imaging in the near infrared wavelength range can

selectively image macrophages labeled by Au NPs. This part of the work was published

in Nano Letters (Plasmonic Intravascular Photoacoustic Imaging for Detection of

Macrophages in Atherosclerotic Plaques, vol. 9, pp. 2212-2217, 2009). The sensitivity of

imaging macrophages labeled by Au NPs, and the viability of cells under laser irradiation

were also investigated in Chapter 3.

In Chapter 4, plasmonic IVPA imaging of macrophages was applied to the rabbit

model of atherosclerosis, where Au NPs were injected in vivo into a rabbit, and the aorta

20

was imaged ex vivo using an upgraded IVPA/IVUS imaging system. Phagocytically

active macrophages were imaged and compared to histological stains. Particle delivery,

blood circulation half-time, and bio-distribution of Au NPs were investigated. Lastly,

because the absorption spectra of Au NPs and lipid do not overlap, simultaneous imaging

of Au NPs and lipid deposits was performed.

Finally, Chapter 5 summarizes the results of the dissertation, addresses limitations

of the study, draws conclusions, and proposes areas of future work.

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26

Chapter 2: Spectroscopic IVPA imaging of lipid deposits

2.1 INTRODUCTION

Lipid is an important component in atherosclerotic plaques. Lipid in the plaques

originates from LDL particles circulating in the blood stream. After entering the leaky

endothelial layer, LDL particles are endocytosed by macrophages located in the arterial

wall. These LDL loaded macrophages later contribute to the lipid-rich necrotic core in the

classical rupture prone plaques [1]. Moreover, it has been shown that periadventitial fat is

related to vessel remodeling and inflammation in atherosclerosis [2]. Imaging lipid

deposits in atherosclerotic vessels will benefit both diagnosis and the understanding of

the pathology of atherosclerosis.

IVPA imaging is well suited for lipid detection in atherosclerosis. The Grüneisen

coefficients of fat and lipid are about two orders of magnitude higher than that of water.

Therefore, lipid is one of the most efficient biological media for the generation of

photoacoustic transients [3]. Consequently, IVPA imaging may detect lipid with high

sensitivity even though the optical absorption coefficient of lipid is lower compared to

other tissue types. In the wavelength range between 1150 nm and 1250 nm, the optical

absorption spectra of fatty acid and water behave differently (Figure 1.8) – the optical

absorption spectrum of fatty acid has a local maxima in this spectral range, while the

spectrum of water is nearly constant [4]. Therefore, spectroscopic IVPA imaging of lipid

may be used to differentiate lipid-rich tissue from other water-based tissues in

atherosclerotic vessels [5].

27

2.2 METHODS

2.2.1 Animal model

A New Zealand white rabbit was kept under a 0.25% cholesterol chow for 20

months. A rabbit subject to such a diet will develop advanced atherosclerosis in the aorta

[6]. Another rabbit fed a normal diet was used as a control. After sacrificing the rabbits,

the aortas were removed and preserved in saline dampened gauze at 4°C. Imaging

experiments were performed within 36 hours of sacrificing the rabbits.

2.2.1 Imaging system

The combined IVUS/IVPA imaging system consisted of a tunable Nd:YAG

pumped OPO laser (OPOTEK, Inc.) capable of generating laser pulses within 680 –

950 nm and 1200 – 2400 nm spectral ranges. The laser pulse duration was 5–7 ns and the

maximum wavelength-dependent fluence was 30 mJ/cm2. A 40 MHz single element

IVUS catheter (Boston Scientific, Inc.) driven by a pulser/receiver (5073PR, Olympus

Inc.) was used for both ultrasound pulse-echo imaging and photoacoustic imaging.

During the imaging experiment, the arterial sample was placed into a water tank and

immersed in saline solution. The IVUS catheter was inserted into the lumen of aorta

while the laser light was delivered by an optical fiber and irradiated the aorta from the

outside (Figure 2.1). The ultrasound beam of the transducer located at the tip of the IVUS

imaging catheter was aligned with the laser beam from the optical fiber. A stepper motor

mechanically rotated the artery for cross-sectional scanning. At each angular position, the

laser light irradiated the tissue and the IVUS transducer was used to receive the

photoacoustic signal. To increase signal-to-noise ratio, 8 photoacoustic signals were

collected and averaged. Then, followed by a user defined delay of several microseconds,

the same IVUS transducer was used to transmit and receive the ultrasound pulse-echo

28

signal. After rotating the arterial sample 360 degrees in 256 incremental angular steps,

co-registered IVPA and IVUS images of the sample were collected. Both IVUS and

IVPA radio frequency signals were acquired using an A/D card (Gage, Inc.) at 200 MHz

sampling rate. A power meter (Ophir, Inc.) was used to measure the energy of laser

pulses at various wavelengths.

Figure 2.1: Laboratory prototype of IVUS-guided multi-wavelength IVPA imaging

system.

2.2.2 SPECTROSCOPIC IVPA SIGNAL PROCESSING

2.2.2.1 Spectroscopic analysis methods for photoacoustic imaging

The specific chemical composition of tissue or plasmon resonance frequency of

metal nanoparticles provides them characteristic optical absorption spectra. Based on the

reconstructed optical absorption spectrum from photoacoustic imaging, spectroscopic

analysis may yield tissue composition information. Various methods have been used for

29

spectroscopic photoacoustic analysis. Most of the methods were applied to measure the

oxygen saturation (SO2) of blood. Because blood is a very strong optical absorber in the

visible-NIR wavelength range, and the difference in blood oxygen saturation changes its

optical absorption spectrum (Figure 1.8), oxygen saturation may be estimated from the

reconstructed spectrum using photoacoustic imaging[8]. However, because of the

wavelength dependent optical property of the tissue, absolute value of the optical

absorption coefficient (i.e. oxygen saturation) is very difficult to find. Pre-knowledge

such as tissue composition is required [9-10]. However, the changes in blood oxygenation

can be measured without wavelength dependent photoacoustic signal compensation [10-

11].

The goal of this work is to identify tissue composition rather than measuring the

absolute optical absorption coefficient. To achieve this goal, the normalized

photoacoustic spectrum is compared with the known tissue absorption spectrum. Two

types of comparison methods are generally used – least square error based and correlation

coefficient based.

1) If the least square error between the measured spectrum and tissue spectrum is

small, then the photoacoustic signal is classified as generated from a certain tissue type.

However, wavelength dependent tissue optical property along the laser beam path can

affect the measured photoacoustic spectrum, especially when the imaging depth is large.

To minimize estimation error, specific wavelength ranges for spectroscopic imaging need

to be carefully selected [10]. However, the selected imaging wavelengths are related to

the pre-knowledge of tissue composition, which is unavailable in the intravascular

imaging scenario. Moreover, in the case of contrast enhanced imaging, it would be ideal

to image at the absorption peak of the contrast agent to achieve better imaging depth than

the wavelength range that the estimation error is small.

30

2) Another type of comparison is utilizing the correlation based method (e.g.

intraclass correlation) as a measure of the similarity between the reconstructed spectrum

and the tissue spectrum [12]. However, prior knowledge of tissue composition (e.g. skin

thickness when imaging mouse tumor) is still required. Therefore, neither of these two

spectroscopic analysis methods is suitable for IVPA imaging. An algorithm needs to be

developed for tissue characterization in IVPA imaging.

2.2.2.2 Slope based algorithm for spectroscopic analysis

A slope based spectroscopic analysis method is developed to differentiate

photoacoustic signals generated from lipid. In contrast to the relatively constant optical

absorption spectrum of water within 1200 – 1230 nm wavelength range, the spectrum of

fatty acid decreases in this spectral range (Figure 1.8). Therefore, for lipid, the

photoacoustic signal amplitude at 1230 nm should be lower than that at 1200 nm. We

further assume that the absorption spectrum of lipid decreases nearly linearly within this

wavelength range. To identify the lipid region from the multi-wavelength IVPA data, a

three-step image processing algorithm was developed.

The flowchart in Figure 2.2 outlines the image processing algorithm used to

analyze multi-wavelength IVPA data. To obtain cross-sectional scans at multiple

wavelengths, the arterial sample was mechanically rotated several times. Consequently,

the elastic arterial tissue may not return to exactly the same position from one scan to

another. Therefore, the displacement of tissue between multi-wavelength scans was

estimated first. Since there was a co-registered IVUS image for each IVPA scan, IVUS

images with abundant anatomical information were used to estimate the tissue

displacement. Suppose the spectroscopic IVPA imaging was performed at multiple

wavelengths 1,[ ], ( 2,3,...),k l l the IVUS image taken at wavelength 1 was then

31

selected as the reference image, and the relative displacements of tissue in the scans at the

other wavelengths ( 2 l ) were estimated using a correlation-based motion tracking

method [13]. IVPA images at other wavelengths ( 2 l ) were then re-registered to the

reference ( 1 ) IVPA image to compensate for tissue motion due to inconsistent rotation

of the arterial sample.

Figure 2.2: Image processing algorithm for analyzing multi-wavelength IVPA and

IVUS data.

In the second step, the slopes of the photoacoustic signal amplitude from 1 to

l were calculated. All IVPA images were first low-pass filtered using a (m+1) by (n+1)

moving average filter. Then, at each pixel, the slope S of the photoacoustic signal

amplitude was calculated and normalized to the photoacoustic signal amplitude at 1

wavelength:

, , 1

,

, 1 1

( ) ( )1,

( )

i j l i j

i j

i j l

S SS

S

(2.1)

where S is the photoacoustic signal amplitude and is the laser wavelength.

Regions with negative slopes within a certain range were selected to indicate the potential

lipid region.

Estimation of Displacement

Calculation of PA Slope

Multi-wavelength IVPA Images

Co-registered IVUS Images

Generation of Error Mask

Combined IVUS and

Spectroscopic IVPA image

Realignment of IVPA images

Image Segmentation

32

In the third step, an error mask was introduced to identify regions with a high

level of noise based on the assumption that the photoacoustic signal amplitude should

have a nearly linear decline from 1 to l . Multi-wavelength IVPA images from 2 to

1l were utilized to identify and reject large photoacoustic signal amplitude fluctuations

from the linear decline with a slope of ,i jS :

, , 1

1 ,

, 1

( ) ( )( , ) ( ) , 2,3,..., 1.

( )

i j k i j

k i jki j

S SE i j S k l

S

(2.2)

An error ( , )E i j is the difference between the measured photoacoustic signal

amplitude at 2 to 1l and the linear fit of the photoacoustic signal amplitude between

1 and l . The potential lipid regions defined in step two were rejected if the error E

exceeded a certain value. The remaining regions were considered to contain lipid.

For display purposes, tissue boundaries, identified from the IVUS image taken

during the IVPA scan at 1 wavelength, were used to segment the spectroscopic IVPA

image. Furthermore, because the images were acquired and processed in the polar system

of coordinates, the IVUS and the spectroscopic IVPA images were scan converted to a

Cartesian grid and displayed using logarithmic scale.

In this study, the tissue sample was imaged every 10 nm within 1200–1230 nm

wavelength range. A kernel measuring 79 µm axially (21 samples) and 7 degrees

azimuthally (5 beams) was used for low-pass filtering. Potential lipid regions were

identified using negative slopes in the range from -0.02/nm to -0.007/nm (Equation 2.2).

An error threshold of 40% was used to reject regions with large fluctuations of the slope.

2.2.2.3 Effect of wavelength dependent tissue property on spectroscopic analysis

As discussed in section 2.2.2.1, the wavelength dependent optical property affects

the spectroscopic analysis. One-dimensional Monte Carlo simulation was performed to

33

analyze the effect of wavelength depended fluence distribution and its effect on the

regional optical absorption of tissue. Four types of tissues were used in the simulation:

water, lipid, adventitia and blood. Due to the limited information on the optical property

of tissue around the 1200 nm wavelength range, scattering coefficients of adventitia and

lipid are assumed to be the same as dermis. Optical scattering from water is assumed to

be negligible, and the absorption coefficient of water was used for the absorption

coefficient of adventitia tissue (Figure 2.3). The optical properties of tissues were

digitized from papers by Roggan et al., Tai et al. and online resources [4, 14-15]. We

also assumed that the anisotropic factor g is 0.99 for all tissue types.

Figure 2.3: Wavelength dependent optical absorption and scattering parameters used in

the Monte Carlo simulation.

To simulate the ex vivo experiment performed in saline, a two layer tissue model

was used for simulation (Figure 2.4(a)). The absorbed optical energy at different depths

in the lipid layer was calculated and plotted (Figure 2.4(b)). The photoacoustic signal

amplitude generated from different depths of lipid did not change significantly at

1180 1190 1200 1210 1220 1230 12400

2

4

6

8

10

12

14

16

18

Wavelength (nm)

Scatt

ering S

pectr

a (

1/c

m)

adventitia

water

blood

lipid

1180 1190 1200 1210 1220 1230 12400.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Wavelength (nm)

Absorp

tion S

pectr

a (

1/c

m)

adventitia

water

blood

lipid

34

different wavelengths. More importantly, the normalized absorbed laser energy (Figure

2.4(c)) indicated that the shape and the peak of the absorption spectrum remained nearly

the same as the optical absorption spectrum of lipid.

In the second scenario, a blood-lipid two-layer model was used to simulate the

condition of in vivo IVPA imaging, in which the laser light illuminated the arterial tissue

from the inside and through a layer of oxygenated blood (Figure 2.5(a)). Due to the

optical scattering of the blood, the absorption peak of lipid at different imaging depth was

slightly blue-shifted (Figure 2.5(b)). However, after normalization, the absorbed laser

energy still followed a near linear decline with increasing wavelength (Figure 2.5(c)).

Figure 2.4: (a) Tissue structure used in Monte Carlo simulation to simulate the ex vivo

imaging experiment. (b) Absorbed laser energy at various depths of the lipid

layer. (c) Normalized laser energy absorption at various depths of the lipid

layer.

1-D Monte Carlo simulation results indicated the slope based spectroscopic

analysis performed in a small wavelength range around 1200 nm was not affected by the

wavelength dependent optical property of tissue. Therefore, lipid can be distinguished

from the spectroscopic analysis. Moreover, the algorithm may also be used in future in

vivo IVPA imaging in the presence of oxygenated blood.

Adventitia

Lipid0

.6 m

m0

.8 m

m

1180 1190 1200 1210 1220 1230 12400.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Norm

aliz

ed A

bsorp

tion

Wavelength (nm)

lipid

0.65 mm

0.85 mm

1.05 mm

1.25 mm

1180 1190 1200 1210 1220 1230 12400.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Absorp

tion (

1/c

m)

Wavelength (nm)

lipid

0.65 mm

0.85 mm

1.05 mm

1.25 mm

(a) (b) (c)

35

Figure 2.5: (a) Tissue structure used in Monte Carlo simulation to simulate in vivo

IVPA imaging. (b) Absorbed laser energy at various depths of the lipid

layer. (c) Normalized laser energy absorption at various depths of the lipid

layer.

2.3 SPECTROSCOPIC IVPA IMAGING OF LIPID IN A RABBIT MODEL OF

ATHEROSCLEROSIS

Cross-sectional IVUS, 1200-nm IVPA and combined IVUS/IVPA images of the

diseased and normal (i.e., control) rabbit aortas are shown in Figure 2.6. All images cover

7.5 mm diameter areas. The IVUS images (Figure 2.6(a,d)) clearly demonstrate the

structure of the vessels. A thickened intima layer in the diseased aorta corresponds to the

hypoechoic regions in the IVUS image (Figure 2.6(a)). Combined IVUS/IVPA images

(Figure 2.6(c, f)) highlight the amplitude and location of photoacoustic signals in relation

to the arterial anatomy. Because the artery was irradiated externally, higher laser fluence

at the outer boundary of the artery resulted in higher photoacoustic response. Notice that

despite the exponential decline of laser fluence with imaging depth, photoacoustic signals

with relatively high amplitude were detected in the thickened intima layer of the diseased

aorta.

1180 1190 1200 1210 1220 1230 12400.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

Absorp

tion (

1/c

m)

Wavelength (nm)

lipid

2.1 mm

2.3 mm

2.5 mm

2.7 mm

1180 1190 1200 1210 1220 1230 12400.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Norm

aliz

ed A

bsorp

tion

Wavelength (nm)

lipid

2.1 mm

2.3 mm

2.5 mm

2.7 mm

Blood

Lipid

2 m

m0

.8 m

m

(a) (b) (c)

36

Figure 2.6: Cross-sectional (a,d) IVUS, (b,e) 1200-nm IVPA, and (c,f) combined

IVUS/IVPA images of the diseased and normal aorta. The IVUS and IVPA

images are displayed using a 40 dB dynamic range.

The multi-wavelength photoacoustic response from several representative regions

of the aortas are presented in Figure 2.7. Specifically, a photoacoustic response in the

thickened intima (region 1, Figure 2.7(a)) is compared with that in the media-adventitia

of both the diseased (region 2, Figure 2.7(a)) and normal aorta (region 3, Figure 2.7(b)).

The signal amplitude in region 1 monotonically decreases with increased wavelength

(Figure 2.7(c)). This decreasing trend corresponds to the absorption spectrum of fatty

acid (Figure 1.8). Therefore, we assumed that photoacoustic signals in region 1 were

generated from the lipid-rich areas. In contrast, photoacoustic signal amplitudes from the

media-adventitia of both the diseased and normal aorta remain relatively constant – such

photoacoustic response in this spectral region closely corresponds to the optical

(a) (b) (c)

(d) (e) (f)

Dis

ease

dC

on

tro

l

37

absorption spectrum of water-based tissues. Therefore, lipid-rich regions in

atherosclerotic vessels may be detected by analyzing the multi-wavelength photoacoustic

signal, e.g. by differentiating areas with different spectral behavior of multi-wavelength

photoacoustic signals.

Figure 2.7: Cross-sectional IVPA images of (a) diseased and (b) normal aortas obtained

using 1200 nm wavelength. (c) Comparison of the wavelength-dependent

photoacoustic responses from the lipid-rich area of the atherosclerotic

plaque (region 1) and media-adventitial layer of diseased (region 2) and

normal (region 3) aortas.

Given the differences in tissue type-dependent spectral behavior of photoacoustic

signals, analysis of multi-wavelength IVPA images was performed to identify regions

with an enhanced content of lipid. The lipid-rich regions, i.e. regions with anticipated

spectroscopic behavior of lipid (Figure 2.7), were color-coded and plotted over co-

registered IVUS images (Figure 2.8(a) and Figure 2.8(d)). Clearly, lipid-rich regions

were detected in the thickened intima of the diseased aorta but no significant lipid-rich

regions were present in the normal aorta. The location of lipid-rich areas was further

confirmed by examination of tissue cross-sections adjacent to the imaged location. Both

the Oil red O stain for lipid (Figure 2.8 (b)) and H&E stain (Figure 2.8 (c)) show that the

plaques in the diseased aorta are lipid-rich, whereas no lipid was present in the intima of

1

2

1200 1205 1210 1215 1220 1225 1230

0.7

0.8

0.9

1

1.1

Wavelength (nm)

No

rma

lize

d P

ho

toa

co

ustic A

mp

litu

de

Region 1

Region 2

Region 3

3

(a) (b) (c)

38

the normal aorta (Figure 2.8 (e) and Figure 2.8(f)). Both normal and diseased aortas show

some lipid in the periadventia but this is unrelated to atherosclerosis. The Oil red O stain

of the diseased aorta shows diffuse distribution of the lipid deposits. A similar scattered

distribution of lipid is reflected in the spectroscopic IVPA image (Figure 2.8(a)). These

results suggest that spectroscopic IVPA imaging may be used to identify the lipid-rich

regions in atherosclerotic vessels.

Figure 2.8: Combined IVUS and spectroscopic IVPA images and corresponding

histological slices of the diseased atherosclerotic aorta (a-c) and normal (i.e.,

control) aorta (d-e). Lipid-rich regions (orange color) were identified from

multi-wavelength photoacoustic imaging and displayed over the IVUS

images. Lipid-rich regions were detected in the thickened intima layer of the

diseased aorta (a) confirmed by Oil red O stain for lipid (b) and H&E stain

(c). In contrast, spectroscopic IVPA imaging (d) and tissue histology (e and

f) show insignificant lipid-rich regions in normal rabbit aorta. Both normal

and diseased aortas show some insignificant deposits of lipid in the

periadventitia.

(a) (b) (c)

(d) (e) (f)

Dis

ease

dC

on

tro

l

39

2.4 DISCUSSION AND CONCLUSION

To quantitatively evaluate the optical absorption property of tissue based on the

photoacoustic response, wavelength dependent optical properties of tissues need to be

taken into account.[9]. In this chapter, a narrow wavelength range of 1200–1230 nm was

used for IVPA imaging to minimize the effect of wavelength-dependent optical

properties on the spectroscopic IVPA data analysis. The narrow imaging wavelength

range benefited the spectroscopic analysis in two ways. First, the limited range of IVPA

imaging wavelength guaranteed the nearly linear decline of the photoacoustic signal from

lipid-rich regions within 1200–1230 nm. Second, the effect of wavelength-dependent

laser fluence distribution was minimal and thus did not significantly affect the relative

changes of the photoacoustic signal amplitude.

The photoacoustic response of the suspected lipid-rich region in the diseased aorta

followed a monotonic decrease in the 1200–1230 nm range (region 1 in Fig. 5). However,

other researchers have found that fatty acid, pork lard and human fat have an absorption

peak at around 1210 nm wavelength [4, 16]. The discrepancy between multi-wavelength

photoacoustic signal amplitude and the optical absorption spectrum of lipid may be due

to several factors including the wavelength dependent fluence distribution in the tissue,

the spectral line width of the laser source, the mixture of lipid and other tissue types in

the intima of the diseased aorta, the small inaccuracy in the reported wavelength of our

OPO laser, and the differences in the absorption spectrum between fatty acid and lipid in

plaques. To capture the peak absorption of the lipid, the artery should be imaged within,

for example, 1170–1230 nm range to include anticipated peak absorption – our pulsed

laser system was operating at the spectral edge of its idler mode (1200 nm to 2400 nm)

and did not allow such measurements. However, if the measurements are performed

around the peak optical absorption of tissue, other correlation based methods, e.g.

40

intraclass correlation analysis [17], may provide better sensitivity than the slope-based

method. Nevertheless, the slope-based method is computationally efficient and is less

sensitive to the shift or shape change of the measured photoacoustic signal peak caused

by wavelength dependent optical properties. The slope-based algorithm only requires

imaging at several wavelengths thus shortening the imaging time and reducing the

complexity of image processing. In comparison, the correlation-based methods may

require measurements covering a broader range of wavelengths and resulting in larger

datasets.

The parameters of the slope-based spectroscopic analysis were selected based on

the optical absorption spectrum of fatty acid. After the peak absorption at 1210 nm

wavelength, the absorption coefficient of fatty acid drops 60% as the wavelength

increases to 1230 nm. Considering the smoothing effect of spectral line width of the laser

source, we selected the slopes ranging between –0.02/nm to –0.007/nm to represent lipid-

rich areas. Given the wavelength dependent fluence distribution and laser pulse energy

variation, we used a 20% error per wavelength to tolerate the change in the photoacoustic

signal amplitude.

The false positive signals in the normal aorta and the media-adventitial layer of

the diseased aorta may be due to inaccuracies in tissue displacement estimation due to

out-of-plane motion during mechanical rotation of the tissue sample. The normal aorta

was more likely subject to this type of artifact because it was more flexible compared to

the diseased aorta characterized by a thick vessel wall. However, compensation for tissue

motion may become even more critical in spectroscopic IVPA imaging in vivo because

cardiac motion will introduce tissue displacement between multi-wavelength IVPA scans.

The sensitivity and specificity of the measurements were affected by the laser

system and the limited knowledge of optical properties of arterial tissue. Because the

41

OPO laser was operating at the spectral edge of its idler mode, the line width of the laser

pulse was around 10 nm. Such broad line width may reduce the sensitivity for imaging

lipid, which has a sharp absorption peak. Using a laser with a narrower spectral line

width may increase the sensitivity and reduce the required laser energy to detect lipid-

rich regions in the vessels. Because of limited available measurements of optical spectra

of different tissue types in the wavelength around 1200 nm, we generally classify tissues

into two categories: lipid-rich tissues or water-based tissues. Knowledge of the absorption

spectra of lipid and other tissue will improve the specificity of identifying lipid-rich

regions.

Using integrated IVUS/IVPA catheter, high sensitivity and high resolution

spectroscopic IVPA imaging in vivo is possible [18]. Indeed, the low optical scattering of

blood and arterial tissue around 1200 nm wavelength ensures sufficient penetration depth

in IVPA imaging [14]. The higher threshold of the maximum permissible exposure at this

wavelength range reduces the concern of laser thermal damage [19]. Moreover, IVPA

imaging with a high frequency IVUS transducer can achieve axial resolution of tens of

micrometers. Since modest low-pass filtering was applied in spectroscopic IVPA

imaging, the axial resolution of the spectroscopic IVPA image is decreased by 2-3 times

compared to the axial resolution of the IVPA image alone.

In the future, quantitative studies will be performed to examine the agreement

between lipid-rich regions identified from spectroscopic IVPA and histological stain.

Furthermore, human atherosclerotic lesions tend to have more complex plaques.

Therefore, the performance of spectroscopic IVPA to differentiate various tissue types

including lipid needs to be studied.

In conclusion, a method to differentiate lipid-rich regions in atherosclerotic

vessels using spectroscopic IVPA imaging together with IVUS imaging was introduced.

42

Ex vivo tissue studies demonstrated that the spectroscopic IVPA imaging in the 1200-

1230 nm wavelength range can successfully identify lipid-rich regions in the

atherosclerotic rabbit aorta. Generally, spectroscopic IVPA imaging has the potential to

identify tissue composition based on intrinsic optical absorption contrast between various

types of tissues.

2.5 REFERENCES

[1] E. Falk, "Pathogenesis of Atherosclerosis," J Am Coll Cardiol, 47(8_Suppl_C),

pp. C7-12, April 18, 2006 (2006).

[2] D. Vela, L. Buja, M. Madjid, A. Burke, M. Naghavi, J. Willerson, S. Casscells,

and S. Litovsky, "The role of periadventitial fat in atherosclerosis," Archives of

pathology & laboratory medicine, 131(3), p. 481, (2007).

[3] A.A.Oraevsky and A.A.Karabutov, Optoacoustic tomography vol. 34: CRC Press,

2003.

[4] C. L. Tsai, J. C. Chen, and W. J. Wang, "Near-infrared absorption property of

biological soft tissue constituents," Journal of Medical and Biological

Engineering, 21(1), pp. 7-14, (2001).

[5] T. J. Allen and P. C. Beard, "Photoacoustic characterisation of vascular tissue at

NIR wavelengths," Proceedings of SPIE, 7177p. 71770A, (2009).

[6] F. D. Kolodgie, A. S. Katocs, Jr, E. E. Largis, S. M. Wrenn, J. F. Cornhill, E. E.

Herderick, S. J. Lee, and R. Virmani, "Hypercholesterolemia in the rabbit induced

by feeding graded amounts of low-level cholesterol: methodological

considerations regarding individual variability in response to dietary cholesterol

and development of lesion type," Arterioscler Thromb Vasc Biol, 16(12), pp.

1454-1464, December 1, 1996 (1996).

[7] B. Wang, J. L. Su, J. Amirian, S. H. Litovsky, R. Smalling, and S. Emelianov,

"Detection of lipid in atherosclerotic vessels using ultrasound-guided

spectroscopic intravascular photoacoustic imaging," Opt. Express, 18(5), pp.

4889-4897, (2010).

43

[8] H. F. Zhang, K. Maslov, G. Stoica, and L. V. Wang, "Functional photoacoustic

microscopy for high-resolution and noninvasive in vivo imaging," Nature

Biotechnology, 24pp. 848-851, (2006).

[9] J. Laufer, D. Delpy, C. Elwell, and P. Beard, "Quantitative spatially resolved

measurement of tissue chromophore concentrations," Physics in Medicine and

Biology, 52pp. 141-168, (2007).

[10] K. Maslov and et al., "Effects of wavelength-dependent fluence attenuation on the

noninvasive photoacoustic imaging of hemoglobin oxygen saturation in

subcutaneous vasculature in vivo," Inverse Problems, 23(6), p. S113, (2007).

[11] H. P. Brecht, D. S. Prough, Y. Y. Petrov, I. Patrikeev, I. Y. Petrova, D. J. Deyo, I.

Cicenaite, and R. O. Esenaliev, "In vivo monitoring of blood oxygenation in large

veins with a triple-wavelength optoacoustic system," Optics Express, 15(24), pp.

16261-16269, (2007).

[12] S. Mallidi, T. Larson, J. Tam, P. P. Joshi, A. Karpiouk, K. Sokolov, and S.

Emelianov, "Multiwavelength Photoacoustic Imaging and Plasmon Resonance

Coupling of Gold Nanoparticles for Selective Detection of Cancer," Nano Letters,

9(8), pp. 2825-2831, (2009).

[13] S. Kim, S. Park, S.R. Aglyamov, M. O'Donnell, and S. Y. Emelianov,

"Improvement of displacement estimation using autocorrelation," Proc.

International Conference on the Ultrasonic Measurement and Imaging of Tissue

Elasticity, p. 58, (2008).

[14] A. Roggan, M. Friebel, K. Dorschel, A. Hahn, and G. Muller, "Optical Properties

of Circulating Human Blood in the Wavelength Range 400--2500 nm," Journal of

Biomedical Optics, 4(1), pp. 36-46, (1999).

[15] Prahl, S. A. "Optical properties spectra compiled by Scott Prahl." 2009, from

http://omlc.ogi.edu/spectra/.

[16] R. R. Anderson, W. Farinelli, H. Laubach, D. Manstein, A. N. Yaroslavsky, J.

Gubeli 3rd, K. Jordan, G. R. Neil, M. Shinn, and W. Chandler, "Selective

photothermolysis of lipid-rich tissues: a free electron laser study," Lasers in

Surgery and Medicine, 38(10), pp. 913-9, (2006).

[17] S. Mallidi, T. Larson, J. Tam, P. Joshi, A. Karpiouk, K. Sokolov, and S.

Emelianov, "Multiwavelength photoacoustic imaging and plasmon resonance

coupling of gold nanoparticles for selective detection of cancer," Nano letters,

(2009).

44

[18] A.B. Karpiouk, B. Wang, and S. Y. Emelianov, "Development of a catheter for

combined intravascular ultrasound and photoacoustic imaging," Review of

Scientific Instruments, 81(014901), pp. 1-7, (2010).

[19] L. I. o. American, "American National Standard for Safe Use of Lasers," vol.

ANSI Z136.1-2007, ed: American National Standards Institute, Inc., 2007.

45

Chapter 3: Plasmonic gold nanoparticles (Au NPs) as contrast agent

for IVPA imaging of phagocytically active macrophages

3.1 INTRODUCTION

Atherosclerosis is an inflammatory disease. Many risk factors for cardiovascular

disease, such as hypercholesterolemia, hypertension, diabetes or obesity, can be directly

related to the inflammatory process [1]. Monocyte derived macrophages are the primary

players in the physiological responses to inflammation. Monocytes first enter the intimal

layer of the vessel wall through disrupted endothelium, and derive into phagocytically

active macrophages. Activated macrophages engulf modified low density lipoprotein

(LDL) particles through scavenger receptors and LDL receptors [2], and become foam

cells. Foam cells undergo apoptosis and release the internalized lipids into the vessel

wall, which turn into the lipid pool [3]. Plaque regions containing active macrophages

indicate ongoing inflammation processes and are prone to rupture [4].

The goal of this chapter is to demonstrate through in vitro cell studies that

phagocytically active macrophages can be imaged using contrast enhanced IVPA

imaging.

3.2 AU NPS AS A CONTRAST AGENT FOR PHOTOACOUSTIC IMAGING

Plasmonic gold nanoparticles are attractive candidates as contrast agents for

photoacoustic imaging because of their large optical absorption cross-sections per

volume, superior biocompatibility, and tunable plasmon resonance peak [5-7]. Plasmonic

Au NPs are not subject to photo bleaching like many kinds of dyes, thus can be reliably

imaged using photoacoustic imaging [8]. Spherical Au NPs have a plasma resonance

peak around 530 nm, which is not preferable for in vivo imaging, because the high optical

scattering of tissue and the high optical absorption of blood. Gold nanorods, on the other

46

hand, have two plasmon resonance peaks – one around 530 nm, the other peak can be

tuned to the near infrared wavelength range by changing particles aspect ratio [9]. The

high optical absorption of gold nanorods in the near infrared range is favorable for

photoacoustic imaging because larger imaging depths can be achieved with relatively low

blood absorption. Gold nanoshells that have a broad absorption spectrum were also used

in optical based imaging or photothermal therapy [7, 10]. Moreover, antibodies that target

specific biomarkers can be bio-conjugated to the surface of the particles to achieve active

delivery of the contrast agent [11]. In this chapter, spherical Au NPs with a diameter

under 50 nm were used to image macrophages.

Photoacoustic signals can be generated by irradiating Au NPs with laser pulses

with a duration from several to tens of nanoseconds [8, 12]. It is interesting to look into

the photoacoustic signal generation mechanism. Apparently, for nanostructures,

nanosecond-duration laser pulses do not satisfy the thermal or stress confinement

requirements for photoacoustic signal generation. The acoustic signals can be generated

by microbubbles formed by boiling water surrounding the particle [13]. It turns out the

bubble generation mechanism is very different at the nano-scale comparing to at the

micro-scale. Because of greater surface tension of water around particles with a diameter

in the nanometer range, very high fluence is required for bubble generation [14].

However, bubbles are unlikely to be generated under the laser fluence used for

photoacoustic imaging, which is usually under the ANSI standard of laser exposure

threshold for skin (typically 15 mJ/cm2 in the visible wavelength range) [15].

Photoacoustic signals from the medium containing NPs can be generated through thermal

expansion mechanism. Once the laser energy has been absorbed by a nanoparticle, heat

will be generated and conduct to the medium surrounding the nanoparticle. Therefore,

photoacoustic signals will be produced by the particle and its intermediate surrounding

47

medium. The temperature profile around Au NPs determines the amplitude of

photoacoustic signal. As a result, photoacoustic signal amplitude not only depends on the

optical absorption property of Au NPs, but also on the thermal properties of the medium

surrounding the particles [16].

3.3 IMAGING PHAGOCYTICALLY ACTIVE MACROPHAGES USING AU NPS

3.3.1 Imaging system

The IVUS/IVPA imaging system for cell study is shown in Figure 3.1. During

imaging, the sample was placed in a water cuvette filled with saline. The IVPA images of

the phantom were obtained using either a 532 nm wavelength Nd:YAG laser or an OPO

laser system (OPOTEK, Inc.) tunable within 680-750 nm, respectively. Both laser

systems produced 4-7 ns pulses. The photoacoustic signals generated by each laser pulse

were collected with a 40 MHz single element IVUS transducer (Boston Scientific, Inc.)

inserted into the lumen of the modeled vessel. The radio frequency (RF) data were

digitized at 200 MHz with data acquisition card (CompuScope 14200, GAGE, Inc.).

After a 9 µs user defined time delay, an ultrasound signal was generated and received by

the same transducer. Once the photoacoustic and ultrasound signals were acquired, the

sample was then rotated around the longitudinal axis to a new angular position using a

stepper motor. As the phantom was rotated 360°, co-registered IVUS and IVPA images

of the vessel’s cross-section were collected.

48

Figure 3.1: Intravascular photoacoustic (IVPA) and intravascular ultrasound (IVUS)

imaging system setup.

3.3.2 In vitro cell experiment

3.3.2.1 Plasmon resonance coupling of Au NPs in macrophages

Fifty nanometer diameter spherical Au NPs (Figure 3.2 (a)) were synthesized via

citrate reduction of HAuCl4 under reflux [17]

. To passivate the surface of NPs, the NPs

were coated with methoxy-polyethylene glycol-thiol (mPEG-SH): a small volume of

104M mPEG-SH solution (MW 5kD, Shearwater) was added to the gold suspension and

allowed to react for 30 minutes on shaker. After incubation, a small volume of 2% PEG

polymer (MW 15 kD, Sigma) was added to the mixture as a surfactant to prevent

aggregation of NPs during centrifugation.

Mouse monocytes – macrophages (J774A.1 cell line) are characterized by a high

rate of non-specific uptake, similar to most cells of a macrophage phenotype. Cells were

cultivated in DMEM supplemented with 5% FBS at 37°C in 5% CO2. To load cells with

Au NPs, macrophages were incubated with a suspension of PEGylated nanoparticles

(approximately 4·1010 particles/ml) in phenol red free and serum free DMEM overnight

(Figure 3.2(b,c)). The optical density of the incubating medium was measured at 530 nm

49

wavelength before and after incubation to calculate the number of particles internalized

by cells. Then, macrophages were counted using a cell counting chamber under the

microscope. The concentration of particles per cell was later determined by dividing the

number of nanoparticles by the number of cells.

Figure 3.2: (a) STEM image of Au NPs. (b) Darkfield reflectance images of murine

macrophages. (c) Murine macrophages loaded with Au NPs. The darkfield

optical images (b,c) were obtained using Xe illumination and a 20x

darkfield objective (0.5 NA).

The absorbance spectra of NP suspension, NP loaded macrophages, and

macrophages only were measured using a UV-Vis spectrometer (BioTek) (Figure 3.3).

The particle suspension has an absorbance peak at 530 nm, whereas cells loaded with

particles have an absorbance peak around 540 nm. Also, the absorbance peak of cells

loaded with particles is broader than the peak of NP suspension. The red-shift and

spectral broadening are attributed to plasmon resonance coupling of particles inside the

macrophages [18-20]

. These features show that the NPs taken by macrophages are in an

aggregated state.

50 um 50 um50 nm

(a) (b) (c)

50

Figure 3.3: Normalized extinction spectra of Au NPs (dashed line) and macrophages

loaded with Au NPs (solid line). Both absorption spectra were normalized

with their corresponding maxima.

3.3.2.2 IVUS/IVPA imaging of cell phantom

A vessel mimicking phantom (Figure 3.4) was made to test whether Au NPs can

be used as contrast agents in IVPA imaging. To simulate the arterial wall, a 25 mm long

and 6 mm in diameter cylindrical tube was made out of 8% polyvinyl alcohol mixed with

0.4% silica by weight to mimic the optical and acoustic scattering of tissue [21]

. Within

the phantom wall, four compartments near and around the lumen were made. Each of the

four compartments was filled with 10% gelatin gel containing either 1) Au NPs (2∙1011

NPs per ml), 2) gelatin only, 3) murine macrophages loaded with Au NPs (1∙104 - 6∙104

NPs per cell, 2∙1011 NPs per ml), or 4) murine macrophages without Au NPs. The last

two compartments, containing an equal number of cells, simulated the macrophage-rich

atherosclerotic plaques before and after the intravenous injection of Au NPs. The PVA

400 450 500 550 600 650 700 750 8000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Wavelength (nm)

No

rma

lize

d a

bso

rptio

n in

ten

sity

51

and gelatin gel simulated healthy tissue, and the compartment with Au NPs simulated

segregated Au NPs in blood stream. An IVPA image of the phantom was collected at

532 nm wavelength to verify the phantom’s composition. Then, a tunable OPO laser

operating from 680 nm to 750 nm wavelength was used for IVPA imaging.

Figure 3.4: (a) Vessel mimicking phantom with four compartments. Different

compartment were injected with cells suspended in gelatin or gelatin alone.

(b) Cross-sectional view of the phantom.

The IVUS, IVPA and combined IVUS/IVPA images of the same cross-section of

the phantom are shown in Figure 3.5 [22]. Images presented in Figure 3.5(b)-(c) were

collected at 532 nm wavelength, and images in Figure 3.5(e)-(f) were collected at

680 nm. In the IVUS image (Figure 3.5(d)), the compartments filled with macrophages

are characterized by the presence of a weak echo signal (small intensity of grayscale

ultrasound). Neither gelatin nor Au NPs affect contrast in ultrasound images – low

concentrations of Au NPs cannot be seen directly from IVUS images. At 532 nm

wavelength, both isolated Au NPs and the nanoparticles aggregated inside of the

macrophages have high contrast in the IVPA image (Figure 3.5(b)). However, the IVPA

image alone may not provide sufficient anatomical information. By combining the IVUS

1mm

(a) (b)

52

and IVPA images (Figure 3.5(c)), the location of Au NPs can be identified and the

composition in each compartment can be further inferred. At 680 nm wavelength (Figure

3.5(e)), only the compartment filled with NP loaded macrophages produces photoacoustic

signal. This is due to the elevated absorption of aggregated NPs at this wavelength

(Figure 3.3). In contrast, the signal from the compartment filled with suspended Au NPs

is very weak and below the noise level of the imaging system. The high photoacoustic

signal strength from the aggregated NPs compared to the non-aggregated or suspended

NPs suggests that only Au NPs internalized by the macrophages will provide contrast in

clinical IVPA imaging performed using 680 nm wavelength. Indeed, the photoacoustic

response from macrophages is enhanced once the Au NPs are endocytosed. At the same

time, the IVPA imaging at this wavelength can be used to avoid imaging of non-

aggregated Au NPs, such as NPs circulating in the luminal blood. Finally, imaging in this

spectral range reduced the influence of optical absorption of luminal blood.

53

Figure 3.5: The structure (a) and the IVUS image (d) of the tissue mimicking phantom.

The IVPA images of the same cross-section of the phantom were taken at

532 nm wavelength (b) and 680 nm wavelength (e). The combined IVUS

and IVPA images of the phantom (c: 532 nm wavelength and f: 680 nm

wavelength) indicated the origin of the photoacoustic responses in IVPA

images.

Multi-wavelength IVPA imaging was performed to further confirm the presence

of aggregated particles and to differentiate labeled macrophages from other tissue

constituents such as red blood cells or lipids. The phantom was imaged every 10 nm

within the 680-750 nm wavelength range. Figure 3.6 [22] shows the quantitative behavior

of the wavelength-dependent photoacoustic response from specific parts of the phantom:

macrophages loaded with Au NPs, 10% gelatin and PVA. The highest normalized energy

of the IVPA signal was detected from NP-loaded macrophages at 680 nm wavelength. As

the wavelength increases, the IVPA signal amplitude from NP-loaded macrophages

NPs

Gelatin

Macrophages

Macrophages

loaded with NPs

Lumen

(a) (b) (c)

(d) (e) (f)

54

decreases. This measurement qualitatively correlates with the direct measurements of

absorbance spectrum from labeled macrophages (Figure 3.3). In contrast, the

photoacoustic response from gelatin gel and PVA is much lower and increases with

optical wavelength. This trend of increasing photoacoustic signal strength with increasing

wavelength is typical of many soft tissues including blood, muscle and fat. Since the

absorption spectrum of arterial tissue behaves differently from aggregated Au NPs at

wavelengths from 680 nm to 750 nm, Au NPs and, therefore, labeled macrophages may

be distinguished by multi-wavelength IVPA imaging.

Figure 3.6: Strength of the photoacoustic signal at different wavelength measured from

the small regions containing macrophages loaded with Au NPs, gelatin gel

and PVA. Each spectrum is normalized to the maximum signal strength

from Au NPs loaded macrophages at 680 nm wavelength.

680 690 700 710 720 730 740 7500.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Wavelength (nm)

No

rma

lize

d e

ne

rgy

Macrophages loaded with Au NPs

Gelatin gel

PVA

55

3.3.3 Experiment using ex vivo tissue injected with Au NP-labeled macrophages

To further demonstrate that IVPA imaging with Au NPs can be used for imaging

of macrophages in atherosclerotic plaques, ex vivo tissue experiments were performed on

a diseased rabbit aorta. A section of the aorta was extracted from a rabbit that subjected

to high cholesterol diet for 3 months. Macrophages loaded with Au NPs (approximately

4∙104

nanoparticles per cell) were mixed with gelatin (2∙107 cells per ml) and injected into

the outer and inner boundary of the aorta. The sample was imaged by the same

IVPA/IVUS imaging system used in phantom experiments. The hypoechoic regions in

the IVUS image, denoted by green arrows in Figure 3.7(a,b,e) indicate the areas of the

injection of macrophages loaded with Au NPs. IVPA images of this cross-section were

taken at 700 nm, 750 nm and 800 nm wavelengths. As shown in Figure 3.7 [22], Au NPs

produce the strongest photoacoustic signal when irradiated with laser pulses at 700 nm

wavelength. At a laser fluence of 15 mJ/cm2, the particles produce readily detectable

photoacoustic signal from the laser light traveling through more than 1 mm of the arterial

tissue. As the wavelength increased, the photoacoustic signal strength from Au NPs

decreased – the photoacoustic response is hardly visible at 800 nm wavelength. This

decreasing trend of photoacoustic signal magnitude closely corresponds to the absorbance

spectra of aggregated Au NPs. Therefore, the ex-vivo tissue experiment demonstrates the

ability of IVPA imaging to detect macrophages loaded with Au NPs.

56

Figure 3.7: IVUS, IVPA and combined IVUS/IVPA images of a diseased rabbit aorta

injected with macrophages loaded with Au NPs. The IVUS image (panel

(a)) is displayed using a 50 dB dynamic range. The injected macrophages in

the outer and inner regions of the aorta are denoted in the images (a, b, e)

with green arrows. The normalized IVPA images (panels (b)-(d)) and

combined IVUS/IVPA images (panels (e)-(g)) obtained using 700 nm,

750 nm and 800 nm wavelengths are displayed using 20 dB display dynamic

range. The IVPA and combined IVUS/IVPA images taken at 700 nm

wavelength (panels (b) and (e)) showed high photoacoustic signals at the

injected regions denoted by arrows.

57

3.4 SENSITIVITY OF IVPA IMAGING TO DETECT AU NP-LABELED MACROPHAGES

IVPA imaging of Au NP-labeled macrophages would be performed in-vivo in the

NIR wavelength range to achieve large penetration depth. In order to guide the in-vivo

experiment, the sensitivity of the imaging system on detecting Au NP-labeled

macrophages at 680 nm was investigated. Different concentrations of murine

macrophages loaded with Au NPs were injected into different compartments of the vessel

mimicking phantoms (Figure 3.4). The detailed concentration of cells/volume and

number of Au NPs/cell is listed in Table 3.1[23].

Upper Right Lower Right Lower Left Upper Left

Phantom

A

NPs/Cell (1.6±0.5) · 104 (1.6±0.5) · 10

4 (8.3±2.4) · 10

2 (8.3±2.4) · 10

2

Cell/mL 1.3 · 107 3.2 · 10

6 2.2 · 10

8 5.5 · 10

7

NPs/mL 2.1 · 1011

5.0 · 1010

1.8 · 1011

4.5 · 1010

Phantom

B

NPs/Cell (2.8±0.3) · 104 (2.8±0.3) · 10

4 (1.9±0.1) · 10

3 (1.9±0.1) · 10

3

Cell/mL 7.9 · 106 1.8 · 10

6 5.7 · 10

7 1.1 · 10

7

NPs/mL 2.2 · 1011

5.0 · 1010

1.1 · 1011

2.0 · 1010

Table 3.1: Concentration of macrophages and Au NPs in arterial phantoms.

The IVUS, IVPA and combined cross-sectional images of the phantoms are

shown in Figure 3.8 [23]. The IVUS images (Figure 3.8(a,d)) clearly demonstrated the

structure of each phantom. Clearly, ultrasound images alone neither detect the presence

of nanoparticles nor differentiate the concentration of nanoparticles within each

compartment. However, macrophages loaded with spherical Au NPs could be detected

using IVPA imaging at 680 nm wavelength (Figure 3.8(b,e)) since the aggregation of

58

NPs inside the macrophages shifts the peak and broadens the absorption spectra of Au

NPs. However, given the finite sensitivity of the IVPA imaging system, macrophages

could be reliably imaged once both the concentration of NPs/cell and concentration of

cells within a volume reaches certain level. Indeed, for both phantoms irradiated at a laser

fluence around 11 mJ/cm2, the upper right and lower right compartments generated a

photoacoustic signal strong enough to be detected by the imaging system. Interestingly,

the signal strength was not correlated with the concentration of particles per volume, but

was determined by the number of particles in each cell. As shown in Table 3.1, the lower

left compartments in both phantoms have higher numbers of NPs per volume than the

lower right compartments. However, the photoacoustic signals generated from the lower

left compartments were weaker than the signals from the lower right compartments.

Similarly, in Phantom A, the upper right and lower left compartments contain about the

same number of particles per volume, but the macrophages in the lower left compartment

did not generate photoacoustic signals of the same strength as the macrophages in the

upper right compartment. This is because the number of particles per cell in the lower left

compartment was too low although the cell concentration in the lower left compartment

was more than ten times higher than the upper right compartment. Imaging results from

Phantom B (Figure 3.8(d-f)) further confirmed that the amplitude of photoacoustic

signals is more related with the size of Au NPs cluster inside macrophages but not the

particle concentration. Due to close distance between Au NPs inside a cluster, the laser-

induced temperature profiles of single particles spatially overlap with each other. As a

result, local hot spots may be generated inside particle clusters, and further enhance the

photoacoustic signal from cells loaded with Au NPs [24].

59

Figure 3.8: IVUS images (a,d), IVPA images (b,e) and combined IVPA/IVUS images

(c,f) of the vessel phantoms with plaque mimicking compartments. IVUS

images are displayed using a 40 dB dynamic range. IVPA images, obtained

using 680 nm wavelength, are displayed using a 20 dB dynamic range.

The results presented in Figure 3.8 showed that the IVPA imaging system

operating at 680 nm wavelength can detect the macrophages loaded with nanoparticles

when the concentration of particles is around 1.5·104 NPs/cell and the concentration of

cells is around 1.3·107 cells/mL (lower right compartments of phantom A and and

phantom B). This concentration of Au NPs corresponds to 0.015 µmol/mL of gold. The

sensitivity of intravascular photoacoustic imaging is higher compared to the detection

limit of ferromagnetic nanoparticles in MRI (within 0.089-0.893 µmol/mL of iron [25]).

3.5 VIABILITY OF AU NP-LABELED CELLS EXPOSED TO PULSED LASER RADIATION

Increasing the laser energy would increase the detection limit of the IVPA

imaging system. However, heat generated by Au NPs because of optical absorption may

cause cell death. We have initially tested the safety of IVPA imaging with the laser

Ph

an

tom

A

(a) (b) (c)

Ph

an

tom

B

(d) (e) (f)

60

source operating in the near infrared range using Au NP loaded macrophages. The

concentration of NPs/cell was around 104. A single layer of macrophage cells was

irradiated with 50 laser pulses at 680 nm wavelength. After laser irradiation,

macrophages were stained with fluorescein diacetate (FDA) – live cells should exhibit the

florescence while the damaged cells should not. The cells showed metabolic activity and

membrane integrity with a laser irradiation as high as 114 mJ/cm2 (Figure 3.9(a)). At a

fluence of 344 mJ/cm2, cell death was observed within the region corresponding to the

irradiation area of the laser beam (Figure 3.9(b)). The macrophages loaded with NPs

remain alive after laser irradiation around 10 times of the laser energy used in the IVPA

imaging experiment (Figure 3.8). Therefore, IVPA imaging of Au NP labeled

macrophages in the NIR wavelength range will not cause cell death.

Figure 3.9: Viability of macrophages loaded with NPs and irradiated with 50 pulses at

680 nm wavelength: a) cells remain viable after irradiation at laser fluencies

reaching 114 mJ/cm2, b) cell death was observed for 344 mJ/cm2 laser

fluence. To cover the extent of the laser beam, the image in Figure 3.9(b)

was assembled from several optical images due to the limited field of view

of the optical microscope.

(a) (b)

61

3.6 CONCLUSION

Contrast enhanced IVPA imaging of in-vitro macrophages have been studied. The

results demonstrated that plasmon resonance coupling of Au NPs internalized by

macrophages broadened the optical absorption spectrum of the Au NP-labeled

macrophages. Utilizing this spectrum change, IVPA imaging in the NIR wavelength

range can selectively identify contrast agent labeled (phagocytically active) macrophages

but not isolated Au NPs. Au NP-labeled macrophages were also injected into a vessel

sample to demonstrate the possibility of identify Au NP-labeled macrophages in the

tissue environment. In all, cell experiments showed that IVPA imaging has the potential

to image phagocytically active macrophages located inside atherosclerotic plaques with

high specificity and sensitivity. Moreover, IVPA imaging of Au NP-labeled macrophages

does not induce tissue damage.

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64

Chapter 4: Detection of phagocytically active macrophages in a rabbit

model of atherosclerosis

As an intermediate step towards in-vivo IVPA imaging, ex vivo imaging of

macrophages were performed on atherosclerotic rabbit aortas with a bench-top IVPA

imaging system. Au NPs were injected in-vivo to label phagocytically active

macrophages. Slope based spectroscopic analysis was applied to extract signals generated

from Au-NP-labeled macrophages based on multi-wavelength IVPA images. Delivery

and bio-distribution of Au NPs was also investigated. Finally, simultaneous imaging of

active macrophages and deposits of lipid was achieved by spectroscopic IVPA imaging in

two NIR spectral ranges.

4.1 METHODS

4.1.1 Imaging system

The imaging system consists of an OPO laser tunable from visible to NIR

wavelength range (PRO-290-10, Spectra Physics). The spectral linewidth is within 2 nm

from 700 to 1300 nm wavelength, and output laser pulse duration is around 6-11 ns. A

pulser/receiver (5073PR, Olympus) was connected with a 40 MHz single element IVUS

catheter (Atlantis SR Pro, Boston Sci. Inc.). The IVUS catheter was inserted into the

vessel lumen. The transducer located at the tip of the IVUS catheter was aligned with the

laser beam (Figure 4.1). After each laser pulse, the IVUS catheter first received

photoacoustic signals generated from vessel. After a user defined 9 µs delay, the catheter

performed ultrasound pulse-echo imaging at the same position of the vessel. A stepper

motor (T-NM, Zaber) rotated the vessel to complete a cross-sectional scan. Each cross-

sectional image consisted of 256 beams. At each cross-section, combined IVPA/IVUS

65

imaging was performed from 710 to 770 nm wavelength, 20 nm step size. The energy of

each laser pulse was monitored by a power meter (Ophir, Inc.) to compensate for the

laser energy fluctuation. A linear axis (T-LSR, Zaber) moved the sample at a 0.25 µm

step size for the longitudinal scan along the vessel. All radio frequency data was digitized

by a 14 bit data acquisition card (GageScope 14200, GaGe) working at 200 MHz

sampling frequency.

Figure 4.1: Setup for the bench-top combined IVUS/IVPA imaging system.

Figure 4.2 and Figure 4.3 are the user interface and the flow chart of the data

acquisition program (based on LabWindowsTM) for acquiring combined IVUS/IVPA

images. The program features an automatic 3D multi-wavelength IVUS/IVPA scan and

tracking the energy of each laser pulse. Because the OPO and the pump laser have their

own stand alone controlling program, another LabWindows based program – OPO

CONTROL – was developed to control and synchronize the OPO (for wavelength tuning)

and pump laser (for tuning laser output energy) (Figure 4.4). The main scanning program

PulserReceiver

IVUS Catheter

Optical Fiber

1-D Motion Axis

Computer

Sample

Water Tank

Motor

Laser

Delay

Power Meter

66

(Figure 4.3) communicates with OPO CONTROL and the power meter through the

DataSocketTM server (National Instruments, Inc.). Each acquired photoacoustic signal

can be registered with its corresponding laser pulse energy by matching the receiving

time stamps from the data acquisition system and power meter.

Figure 4.2: User interface of the combined IVUS/IVPA imaging system.

67

Figure 4.3: Flow chart for spectroscopic IVUS/IVPA data acquisition.

Initialize motors, A/D card;Read laser parameters

Start

End of scan ?

Set laser parameters

A/D cardtriggered?

First cross-section?

Start recording laser power

RF data acquisition

Motion control

Y

N

End

N

Y

Y

N

OPO

Pump Laser

Wavelength

Energy

68

Figure 4.4: User interface of a custom developed program to control laser systems.

4.1.2 Synthesis and characterization of Au NPs

Twenty nanometer diameter spherical Au NPs were synthesized via citrate

reduction of HAuCl4 under reflux and PEGylated as discussed in section 3.2.2.1 (Figure

4.5). The PEGylated Au NPs have a hydrodynamic diameter of around 42.5 nm

(DelsaNano, Beckman Coulter).

69

Figure 4.5: STEM image of Au NPs.

4.1.3 Animal protocol

Balloon injured rabbit was used in this study. A one year old New Zealand white

rabbit was subjected to a 0.5% cholesterol diet for 2 weeks. Balloon injury was

performed with a 4F Fogarty embolectomy catheter with 5 passes on the aorta from the

4th

to 11th

rib. The rabbit was fed a 0.5% cholesterol diet for another 4 months before the

imaging experiment. During the imaging experiment, Au NPs with a dose of 27.3 mg

Au/kg of body weight was injected through the rabbit’s ear vein. Blood samples were

collected at different time points post particle injection for analyzing the plasma

circulation time of Au NPs. The rabbit was sacrificed 28 hours post contrast agent

injection, and the abdominal aorta was extracted and used for ex vivo imaging. Major

organs were harvested and used for the contrast agent bio-distribution study. All animal

experiments were approved by the Animal Welfare Committee of the University of Texas

Health Science Center at Houston, and the Institutional Animal Care and Use Committee

of the University of Texas at Austin.

20 nm

70

4.1.4 Isolation of mononuclear cells from whole blood

Cell separation was performed within 2 hours after sampling the blood. Two mL

of whole blood was diluted with 2 mL of PBS, and then carefully layered on top of 4 mL

of Histopaque (Histopaque-1077, Sigma-Aldrich) solution. After centrifugation at 400 g

for 30 minutes, mononuclear cells were collected for dark field microscopic imaging.

4.1.5 Analysis of gold concentration in tissue samples

In order to analyze the concentration of gold in tissue samples, each tissue sample

(1-2 mL for blood, ~1 g for other tissues) was digested in 10 mL 35% HNO3 and 1 mL

18.5% HCL at a high pressure and temperature using a microwave digestion system

(Mars, CEM). The digested sample was diluted to around 7% acid concentration and

analyzed using an inductively coupled plasma mass spectrometry (ICP-MS) system.

4.2 IMAGE PROCESSING

Slope based spectroscopic analysis similar to that described in Chapter 3 was

applied to identify macrophages loaded with Au NPs and deposits of lipid using multi-

wavelength IVPA images. For imaging Au NP-labeled macrophages, multi-wavelength

IVPA images were acquired within 710-770 nm wavelength range, with a step size of

20 nm. Each acquired cross-sectional IVPA image was processed according to the

sequence of the following procedures (Figure 4.6).

Figure 4.6: Imaging processing algorithm for spectroscopic IVPA and IVUS images.

Calculation of PA Slopes

Multi-wavelength IVPA Images

Co-registered IVUS Images

Generation of Masks

Combined IVUS and

Spectroscopic IVPA image

Image Segmentation

Scan conversion

71

1) Multi-wavelength IVPA images were first spatially low-pass filtered using

running average with a kernel size of 80 µm (axial) by 7 degrees (lateral). The

size of the kernel is around 2 times that of the resolution of the IVPA image.

2) Three slope maps of the photoacoustic amplitude between 710 nm to 730, 750 and

770 nm were calculated at each pixel of the image:

, , 710

,

, 710

( ) ( )1, 730,750,770

( ) 710

i j l i jl

i j

i j

S SS l

S l

, (4.1)

where ,i jS is the normalized photoacoustic amplitude at pixel i, j, and ,

l

i jS is the

photoacoustic amplitude slope at wavelength l .

3) Three masks where generated in order to differentiate PA signal from Au NPs.

From 710 to 770 nm, other than Au NPs, oxygenated blood is another strongly

absorbing chromophore that may generate photoacoustic signal. The

spectroscopic photoacoustic amplitude from blood has a positive slope, while

macrophages loaded with Au NPs has a negative one. Therefore, the first mask

selected signals with a negative photoacoustic amplitude slope in the range of

770

,0.8 0

(770 710) i jS

. Then, two other masks were introduced to reject regions

with high level of noise based on the assumption that the photoacoustic amplitude

should have a nearly linear decline in 710-770 nm wavelength. Regions with

photoacoustic slope maps satisfying equation (4.2) are considered as regions

containing Au NP-labeled macrophages.

770

, ,

0.3, 730,750

710

l

i j i jS S ll

. (4.2)

72

4) For display purposes, vessel regions in the spectroscopic IVPA images were

segmented based on the co-registered IVUS images.

5) Spectroscopic IVPA and IVUS images were scan converted to the Cartesian grid.

Image processing procedures for the detection of lipid deposits are similar to Au

NP-labeled macrophages. Instead of imaging at four wavelengths, IVPA images acquired

at three wavelengths (1210-1230 nm, step size 10 nm) were used. Multi-wavelength

IVPA images were first spatially filtered using a running average. Then, a photoacoustic

amplitude slope was calculated between 1210 and 1230 nm using equation (4.3).

, , 1210

,

, 1210

( ) ( )1, 1220,1230.

( ) 1210

i j l i jl

i j

i j

S SS l

S l

(4.3)

Based on the optical absorption spectrum of fatty acid (Fig. 1c), slopes satisfying

the following condition: 1230

,0.7 0.25

(1230 1210) (1230 1210)i jS

were selected. A

mask generated using the image at 1220 nm was used to further differentiate lipid

deposits from water based tissue: 1220 1210

, ,

0.2.

1220 1210i j i jS S

4.3 RESULTS

4.3.1 Imaging the distribution of phagocytically active macrophages in

atherosclerotic rabbit aortas

PEGylated 20 nm diameter spherical Au NPs were injected into a rabbit model of

atherosclerosis through the ear vein. PEG coating was used to improve the

biocompatibility and to prolong the circulation of nanoparticles [1]. Analysis of gold

concentration in the blood samples showed a long plasma circulation halftime of over 20

hours (Figure 4.7(a)). Aorta sections were scanned ex-vivo for macrophages at 710-

770 nm wavelength.

73

In order to identify regions containing Au NP-labeled macrophages or lipid

deposits, spectroscopic analysis was performed to separate the tissue components of

interest from other major absorbing chromophores. With increasing wavelength within

710-770 nm range, regions with increased photoacoustic amplitude indicate the presence

of oxygenated hemoglobin; while regions with decreased amplitude outline regions

containing Au NPs (Figure 4.7(b)). For advanced plaques, most of the labeled

macrophages were located in the subendothelial layer, where phagocytically active

macrophages are normally localized (Figure 4.7(c,f)). In some regions, Au NPs were

located 0.5 mm deep into the plaques (3 o’clock in Figure 4.7(c,d)). For early plaques,

both the spectroscopic IVPA image and the silver stain showed a high concentration of

Au NPs located in the “shoulder region” of the fatty streaks (Figure 4.7(f,g), region at 6

o’clock), where macrophage infiltration and plaque disruption most frequently occurs [2].

Au NPs may penetrate into the plaques and be internalized by activated macrophages

through different pathways. Particles located in the subendothelial layer may infiltrate

into the plaques through leaky endothelium. Au NPs may also be delivered deep into the

plaques through the intraplaque vasa vasorum. Similar to dysfunctional endothelium, the

vasa vasorum can be leaky. The density of vasa vasorum may indicate the stage of the

atherosclerotic plaques [3-4]. In the combined IVUS/spectroscopic IVPA images

(Figure 4.7(c,f)), we observed Au NPs delivered through vasa vasorum into the adventitia

(Figure 4.8). These Au NPs may enter the plaques through incomplete endothelial

junctions [4]. Note that although plaques were rich in macrophages, not all macrophages

were labeled with Au NPs (Figure 4.7(c-h)). Insufficient labeling may be because the

macrophages deep inside the plaques were not phagocytically active although it is

possible that not enough nanoparticles diffused deep into the plaques. However, the 28

74

hour post-injection images shown here effectively indicate regions with leaky

endothelium.

Figure 4.7: (a) Gold concentration in the blood after 20 nm diameter spherical

PEGylated Au NPs were intravenously injected into the rabbit. The dashed

line is an exponential fit. (b) The spectroscopic photoacoustic response was

different for regions containing Au NP-labeled macrophages and the region

containing blood. (c,f), Combined spectroscopic IVPA and IVUS images

(scale bar 0.5 mm) demonstrated the location of Au NP-labeled

macrophages in the atherosclerotic plaques. Spectroscopic IVPA images of

Au NP-labeled macrophages were color coded in green, while IVUS images

were shown in gray scale. Corresponding histochemistry stains were shown

to the right of each image. (d,g), Silver stain for nanoparticles. (e,h),

RAM11 stain for macrophages.

1

3

2

0

20

40

60

80

100

120

0 5 10 15 20 25 30

% r

emai

nin

g A

u N

Ps

in b

loo

d

Hours

a b

c d e

gf h

710 720 730 740 750 760 7700

0.5

1

1.5

2

wavelength (nm)

No

rma

lized

PA

am

plit

ud

e (

a.u

.)

Region 1 (Au NPs)

Region 2 (Au NPs)

Region 3 (Tissue/blood)

75

Figure 4.8: Distribution of Au NPs within the vessel wall. Au NPs are present in or

around the vasa vasorum embedded in the adventitia.

4.3.2 Imaging deposits of lipid in atherosclerotic rabbit aorta

Lipid in the atherosclerotic plaques can be detected using spectroscopic IVPA

imaging based on the difference in the optical absorption spectra between fatty acid and

water based tissue (Figure 1.5). In advanced plaques, the thickened intimal layer is rich in

lipid (Figure 4.9(b,c)) whereas, in early plaques, lipid is located inside the fatty streaks

(Figure 4.9(d,e)). In several cross-sections, spectroscopic IVPA imaging did not delineate

all lipid content in the thickened intimal layer, as seen in the Oil Red O stain

(Supplementary Fig. S3). This may be caused by finite sensitivity of our IVPA imaging.

system.

100 µm

76

Figure 4.9: IVPA imaging of lipid. (a) Normalized spectroscopic photoacoustic signal

amplitude from different regions of the vessel wall. For the lipid-rich region,

the signal decreased with increased wavelength, while the normal vessel had

a relatively flat spectroscopic response. (b,d) Combined spectroscopic IVPA

and IVUS images of one cross-section of the vessel wall. Spectroscopic

IVPA images of lipid deposits were color coded in red, while IVUS images

were displayed in gray scale. Scale bars are 0.5 mm. (c,e) Corresponding Oil

red O stain for lipid.

1

2

3

1210 1215 1220 1225 12300

0.2

0.4

0.6

0.8

1

wavelength (nm)

No

rma

lized

PA

am

plit

ud

e (

a.u

.)

Region 1 (lipid)

Region 2 (lipid)

Region 3 (normal vessel)

a

b

d e

c

77

Figure 4.10: An artifact in spectroscopic IVPA imaging of lipid deposits. (a) Combined

spectroscopic IVPA image of lipid. Because of the misalignment between

the laser beam and the IVUS transducer, no lipid shows up to the right of the

aorta sample. (b) Oil Red O stain of the adjacent cross-section showed a

circumferential lipid-rich intimal layer.

4.3.3 Simultaneous imaging of lipid deposits and phagocytically active macrophages

Macrophage activity around lipid laden plaques may be critical to predict the

development and rupture of the plaque. Co-registered spectroscopic IVPA images of Au

NP-labeled macrophages and lipid were combined, and then overlaid onto the

corresponding IVUS image (Figure 4.11). In advanced plaques, most of the labeled

macrophages were observed in the subendothelium, close to the vessel lumen, while lipid

was in the thickened intima (Figure 4.11(a-d)). In the vessel section that had few fatty

streaks, macrophage activity was only observed close to and around lipid-laden plaques

(Figure 4.11(e-h)).

a b

78

Figure 4.11: 3D IVPA simultaneous imaging of macrophages and lipid. (a,b) Cross-

sectional view of IVUS/spectroscopic IVPA images revealing both Au NP-

labeled macrophages (green) and lipid (red) in atherosclerotic plaques. (c-h),

Reconstructed 3D images showing the distribution of Au NP loaded

macrophages (b,f), lipid (c,g) and macrophages and lipid together (d,h). The

yellow regions in figures (d,h) resulted from the overlay of green

(macrophages) and red (lipid).

Lipid and Au NPs

Cross-sectional view

Au NPs 3D view

(macrophage activity)

Lipid

3D view

Lipid and Au NPs

3D view

a

b

c

d

e

f

g

h

79

4.4 DISCUSSION

4.4.1 Delivery pathways of Au NPs to phagocytically active macrophages

Plasmonic Au NPs were introduced to label macrophages in atherosclerotic

plaques in vivo. Macrophage labeling may occur via two different pathways. First,

isolated Au NP may diffuse through the leaky endothelium and then be internalized by

phagocytically active macrophages inside the plaques. Second, Au NPs may first be

internalized by peripheral blood monocytes and then these labeled monocytes enter

plaques through the endothelium. We observed Au NP uptake by mononuclear cells in

peripheral blood 6 hours post contrast agent injection (Figure 4.12).

Figure 4.12: Dark-field image of mononuclear cells separated from a rabbit blood

sample 6 hours after contrast agent administration. Some of the cells were

labeled by Au NPs (arrows).

80

4.4.2 Size and shape dependent delivery of Au NPs

Delivery of contrast agents specifically targeting a cell type depends on many

factors such as the cell type, as well as the size, shape and coating of the contrast agent.

The surface charge of the particles dramatically affects the cell uptake. Positively charged

particles were internalized within an hour of incubation [5], therefore they may increase

the non-specific uptake by untargeted cells and are not ideal to use as a contrast agent.

For antibody coated spherical Au NPs, studies have shown that the optimal cellular

uptake happens when the size of the particle is around 40-50 nm diameter. Smaller or

larger Au NPs may shorten the cell membrane wrapping time, which resulted in

decreased internalization [6]. However, in the in vivo scenario, particle delivery may vary

significantly from the observations in cell culture. Parameters such as plasma circulation

half time and the ability for the particle to penetrate through the endothelium will

significantly affect the in vivo cellular uptake. Meanwhile, the size and the coating of the

particles will also significantly affect the bio-distribution, and ultimately the clearance

pathway for the contrast agent. Different studies shows quantitatively different bio-

distribution of the Au NPs with most of the particles accumulated in the liver or spleen

[1, 7-8].

Table 4.1: Au NPs injected in two balloon injured rabbits.

Particle

diameter (nm)

Injected concentration

(mg/kg)

Rabbit 1 20 27.4

Rabbit 2 50 19.41

81

As a preliminary study, two sizes of spherical Au NPs coated with 5 kD PEG

were injected into two balloon injured rabbits (Table 4.1). The circulation time of 20 nm

spherical Au NPs was significantly longer than 50 nm ones. Interestingly, the bio-

distribution of gold shows that up to 28 hours post injection, more 20 nm particles

accumulated in spleen than 50 nm particles, while 50 nm particles were more

concentrated in liver. Small particles may accumulate more easily in brain. However,

because around half of the particles were still in circulation at the time of sacrifice for the

rabbit injected with 20 nm particles, the bio-distribution of gold in different organs may

be confounded by the gold in the blood vessels.

Figure 4.13: Gold concentration in rabbits injected with 20 nm (Rabbit 1) and 50 nm

(Rabbit 2) spherical PEGylated Au NPs.

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30

% r

em

ain

ing A

u N

Ps

in b

loo

d

Hours after injection

Rabbit 1

Rabbit 2

82

Figure 4.14: Bio-distribution of gold in rabbits injected with 20 nm (a) and 50 nm (b)

spherical PEGylated Au NPs.

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

lung liver spleen pancreas brain kidney

Au

co

nce

ntr

atio

n (m

g/g)

(a)

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

lung liver spleen pancreas brain kidney

Au

co

nce

ntr

atio

n m

g/g

(b)

83

4.5 CONCLUSION

We demonstrated in vivo delivery of Au NPs to macrophages in atherosclerotic

plaques. The long circulation time of these Au NPs facilitated in vivo labeling of

macrophages deep inside the plaques. Due to plasmon resonance coupling of aggregated

Au NPs internalized by macrophages, spectroscopic IVPA imaging can identify

phagocytically active macrophages inside plaques. Furthermore, lipid deposits were

simultaneously imaged based on their characteristic optical absorption peak. Therefore,

combined spectroscopic IVPA and IVUS images can depict macrophage activity around

lipid-rich plaques, which is critical for characterization and treatment planning of

atherosclerotic plaques.

4.6 REFERENCES

[1] G. von Maltzahn, J.-H. Park, A. Agrawal, N. K. Bandaru, S. K. Das, M. J. Sailor,

and S. N. Bhatia, "Computationally guided photothermal tumor therapy using

long-circulating gold nanorod antennas," Cancer Research, 69(9), pp. 3892-3900,

May 1, 2009 (2009).

[2] E. Falk, "Pathogenesis of Atherosclerosis," J Am Coll Cardiol, 47(8_Suppl_C),

pp. C7-12, (2006).

[3] M. Gössl, D. Versari, H. A. Hildebrandt, T. Bajanowski, G. Sangiorgi, R. Erbel,

E. L. Ritman, L. O. Lerman, and A. Lerman, "Segmental Heterogeneity of Vasa

Vasorum Neovascularization in Human Coronary Atherosclerosis," JACC:

Cardiovascular Imaging, 3(1), pp. 32-40, (2010).

[4] J. C. Sluimer, F. D. Kolodgie, A. P. J. J. Bijnens, K. Maxfield, E. Pacheco, B.

Kutys, H. Duimel, P. M. Frederik, V. W. M. van Hinsbergh, R. Virmani, and M.

J. A. P. Daemen, "Thin-Walled Microvessels in Human Coronary Atherosclerotic

Plaques Show Incomplete Endothelial Junctions: Relevance of Compromised

Structural Integrity for Intraplaque Microvascular Leakage," Journal of the

American College of Cardiology, 53(17), pp. 1517-1527, (2009).

[5] S. E. A. Gratton, P. A. Ropp, P. D. Pohlhaus, J. C. Luft, V. J. Madden, M. E.

Napier, and J. M. DeSimone, "The effect of particle design on cellular

84

internalization pathways," Proceedings of the National Academy of Sciences,

105(33), p. 11613, (2008).

[6] W. Jiang, B. Kim, J. Rutka, and W. Chan, "Nanoparticle-mediated cellular

response is size-dependent," Nature Nanotechnology, 3(3), pp. 145-150, (2008).

[7] T. Niidome, M. Yamagata, Y. Okamoto, Y. Akiyama, H. Takahashi, T. Kawano,

Y. Katayama, and Y. Niidome, "PEG-modified gold nanorods with a stealth

character for in vivo applications," Journal of Controlled Release, 114(3), pp.

343-347, (2006).

[8] Q.-Y. Cai, S. H. Kim, K. S. Choi, S. Y. Kim, S. J. Byun, K. W. Kim, S. H. Park,

S. K. Juhng, and K.-H. Yoon, "Colloidal Gold Nanoparticles as a Blood-Pool

Contrast Agent for X-ray Computed Tomography in Mice," Investigative

Radiology, 42(12), pp. 797-806 10.1097/RLI.0b013e31811ecdcd, (2007).

85

Chapter 5: Conclusion and future work

5.1 SUMMARY OF RESEARCH

IVPA imaging is a recently developed imaging modality that may non-invasively

image the composition of the atherosclerotic plaques at a resolution similar to IVUS

images (tens of micron), and at an imaging depth of several millimeters [1]. The

uniqueness of IVPA imaging is that it provides a direct measurement of the spatially

resolved optical absorption property of the plaques. The optical absorption information

can be used to identify tissue composition, or detect the optically absorbing contrast

agents. In this dissertation, IVPA imaging was used to detect lipid deposits and

macrophages labeled by gold nanoparticles.

Lipid deposits in atherosclerotic plaques were first imaged using spectroscopic

IVPA imaging. The imaging contrast for lipid came from the characteristic optical

absorption peak of fatty acid around 1210 nm wavelength range. An ex vivo combined

IVPA and IVUS imaging system based on a single element 40 MHz IVUS imaging

catheter and OPO tunable pulsed laser was developed to acquire co-registered IVUS and

multi-wavelength IVPA images. A healthy rabbit aorta and a rabbit aorta from a

cholesterol fed rabbit were imaged from 1200 to 1230 nm wavelengths. A slope based

algorithm was applied to generate spectroscopic IVPA image of the lipid in plaques.

Histology stain confirmed that spectroscopic IVPA imaging can successfully detect lipid

deposits in atherosclerotic plaques.

Contrast enhanced molecular IVPA imaging of macrophages was presented in

Chapter 3. In vitro cell phantom studies were first performed to investigate the feasibility

of using Au NPs as a contrast agent for IVPA imaging of macrophages. Murine

macrophages labeled with Au NPs showed elevated optical absorption in the NIR

wavelength range compared to Au NPs alone. Macrophages labeled with Au NPs were

86

microinjected into a vessel mimicking phantom and an excised rabbit aorta. Due to

increased optical absorption of cells labeled with Au NPs, IVPA imaging at NIR

wavelength range, e.g. 680 nm, can selectively image Au NP-labeled macrophages. The

results indicate that NIR IVPA imaging can detect phagocytically active macrophages.

Experiments also showed that NIR IVPA imaging of macrophages has high sensitivity

and the laser fluence used for imaging does not cause cell death.

PEGylated Au NPs were then injected in vivo into a balloon injured

atherosclerotic rabbit aorta. The excised rabbit aorta was scanned at multiple wavelengths

in the NIR range for simultaneous detection of phagocytically active macrophages and

lipid deposits. An ex vivo imaging system was designed for the 3D spectroscopic scan

from 710-770 nm for imaging macrophages, and 1210-1230 nm for imaging lipid.

Because the optical absorption peaks of Au NPs and lipids do not overlap, simultaneous

imaging of Au NP-labeled macrophages and lipid deposits can be achieved. Results

showed that 20 nm diameter PEGylated Au NPs had a long plasma circulation time and

penetrated deep inside the plaques. IVPA imaging successfully detected the distribution

of macrophages loaded with Au NPs, as well as the distribution of lipid deposits.

Macrophage activity in or around the lipid-rich plaques provides valuable information in

indentifying vulnerable plaques. For example, Au NP-labeled macrophages located at the

shoulder region of the lipid-rich plaques indicated the rupture-prone regions.

In summary, using rabbit models of atherosclerosis, the study presented in this

dissertation demonstrated that IVPA imaging can detect lipid deposits using

spectroscopic IVPA imaging. PEGylated Au NPs can label phagocytically active

macrophages in atherosclerotic plaques in vivo, and Au NP-labeled macrophages were

detected using IVPA imaging in the NIR wavelength range. Simultaneous detection of

87

macrophage activity and lipid deposits were achieved using spectroscopic IVPA imaging

at two NIR wavelength ranges.

5.2 LIMITATIONS

5.2.1 Animal model of atherosclerosis

In this study, characterization of plaques was performed using rabbit models of

atherosclerosis. Similarity of plaques between the animal model and human is critical to

ensure that the plaque characterization methods can be transferred to clinical use.

Atherosclerotic plaques induced in NZW rabbit generally are lipid-rich and have high

macrophage activity. These plaques are suitable for the detection of lipid and

macrophages. However, vulnerable human plaques usually contain many other

components such as calcification and intraplaque hemorrhage. Complex plaque

composition may affect the laser fluence distribution inside the vessel wall, and therefore

may introduce error when using the spectroscopic analysis presented in this paper. Fine

adjustments of the imaging wavelength range or the threshold in the spectroscopic

analysis are necessary to increase the sensitivity and specificity of human plaque

characterization.

5.2.2 Ex vivo imaging of atherosclerotic plaques

In the current setup, the laser beam was delivered externally onto the vessel. The

ex vivo imaging system guaranteed superior alignment between the laser beam and the

IVUS catheter, and the consistency of laser fluence distribution between experiments.

However, for the in vivo application, an integrated catheter that can deliver laser pulses

into the vessel is required. When using an integrated catheter for in vivo imaging, light

distribution will be affected by the luminal blood. Laser fluence reaching the vessel wall

88

will be lower than that in the ex vivo imaging setup. Moreover, the optical property of

blood may change the spectroscopic responses of photoacoustic signals. Imaging in a

small NIR wavelength range may help the spectroscopic analysis (Figure 2.5). However,

higher fluence and further validation of spectroscopic analysis may be necessary for the

in vivo imaging.

5.2.3 Imaging speed

IVPA imaging can potentially be performed real-time imaging. Imaging speed of

the current ex vivo imaging system is limited by the 10 Hz repetition rate of the laser

system. The OPO laser system is suitable for bench-top imaging because of its

nanosecond duration laser pulses, broad tunable wavelength range, and high laser energy

output. In the clinical practice, when the laser wavelength range has been selected based

on the optical absorption spectrum of tissue of interest, dye or other lasers with high

repetition rate may be used. Another option to achieve real-time IVPA imaging is to

design the combined IVPA/IVUS imaging system based on IVUS array transducers.

After irradiating a region of the vessel wall with laser pulse, photoacoustic signals may

be acquired simultaneously through multiple channels. However, an array based

IVPA/IVUS imaging system requires a significant modification from the current array

catheter based IVUS imaging system, for example, by adding more parallel data

acquisition channels. Moreover, array based catheter will have a larger profile than

rotational catheter.

89

5.3 FUTURE DIRECTIONS

5.3.1 Detecting lipids using thermal IVPA imaging

Unlike previous studies reported here, where plaques were characterized based on

their optical contrast, temperature dependent Grüneisen coefficient may also be used to

differentiate tissue composition. When the laser pulse duration satisfies stress

confinement and thermal confinement, the photoacoustic signal amplitude generated from

optically absorbing biological tissue is proportional to the product of the Grüneisen

coefficient, the tissue’s optical absorption coefficient, and the local optical fluence

(Equation (1.2)). The Grüneisen coefficient is defined as:

2

s

p

v

C

, (5.1)

where sv is the speed of sound, is the thermal coefficient of volume expansion, and

pC is the specific heat capacity at constant pressure. Generally, all three parameters are

temperature dependent and differ between types of tissue. Studies have shown the

opposite trend of sound speed and the thermal coefficient of volume expansion between

animal fat and water [2-4]. Meanwhile, the specific heat capacity also behaves differently

in animal fat and water [2]. Therefore, there may be imaging contrast between lipid in

plaques and other water based tissue as a result of the temperature dependent Grüneisen

coefficient. This imaging contrast may be used for detecting lipids in plaques using IVPA

imaging. We named this approach as thermal IVPA imaging.

One cross-section of the WHHL rabbit aorta was imaged with thermal IVPA

imaging. Histology stains of the aorta cross-section showed eccentric and lipid rich

plaques in the inner lumen of the vessel (Figure 5.1 (a,b)). An IVUS image of the

adjacent cross-section showed two hypo-echoic regions that correspond to the plaques

90

(yellow arrows in Figure 5.1(c)). The IVPA image acquired at 25 oC with 1210 nm

wavelength was overlaid onto the IVUS image. Strong photoacoustic signals were

presented at the plaque region because of the strong optical absorption of lipid at

1210 nm wavelength (Figure 1.8). Strong photoacoustic signals were also observed at the

outer boundary of the aorta. These signals may be generated from the connective adipose

tissue due to either high optical absorption or high subsurface optical fluence caused by

the optical scattering mismatch between saline and arterial tissue. Temperature dependent

photoacoustic responses from four regions in the plaques and vessel wall were

normalized and are plotted in Figure 5.1(e). The photoacoustic amplitude generated from

the vessel wall remained relatively constant, while the IVPA signal amplitude from

plaques decreased with increasing temperature. This different trend of photoacoustic

amplitude indicates that the Grüneisen coefficient for lipid in plaques and other types of

tissue has a different temperature dependence. Therefore, lipid distribution may be

imaged based on the temperature dependent photoacoustic signal amplitude.

Figure 5.2 shows the image processing algorithm used to generate the lipid image

based on the temperature dependent IVPA images. The IVPA images acquired at two

different temperatures were first running averaged with a kernel size of 266 µm by 15.5

degrees. Then, the finite difference of the photoacoustic amplitude between the two

images was calculated:

1 2

2

, ,

,

,

,

T T

i j i j

i j T

i j

S SD

S

(5.2)

where in ,

T

i jS is the photoacoustic signal amplitude at pixel ,i j at temperature T and

,i jD is the resulting finite difference map. ,i jD was used to form the lipid image.

91

Figure 5.1: (a) Oil red O stain for lipid, and (b) H&E stain were performed in tissue

slices adjacent to the imaged cross-section. (c) IVUS image of the aorta. (d)

Combined IVUS and IVPA image acquired at 25 oC. (e) Temperature

dependent photoacoustic responses from plaques and vessel wall.

15 20 25 30 35 400.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.2

Temperature oC

Nor

mal

ize

d P

A a

mp

litud

e a

.u.

x Plaquex Vessel wall

(a) (b)

(c) (d)

(e)

92

Figure 5.2: Image processing algorithm to generate combined IVUS and lipid image of

the aorta.

IVPA images taken at 38 ºC and 25 ºC were used to generate thermal IVPA

image. The finite difference map was formed based on Equation (5.2), with

1 238 , 25o oT C T C . Regions with decreasing photoacoustic amplitude versus

temperature ( ,0.4 0.95i jD ) were color coded red and overlaid onto the co-registered

IVUS image. As shown in Figure 5.3(a), red-colored regions coincide with the location of

plaques. Oil red O stain for lipid and H&E stains (Figure 5.3 (c,d)) of the adjacent cross-

sections also confirmed that the plaques are eccentric and lipid rich.

A spectroscopic IVPA image of lipid at the same cross-section of the aorta was

generated using the method introduced in Chapter 4. The spectroscopic IVPA image also

successfully delineated lipid-rich regions inside the plaque (Figure 5.3(b)), confirming

that the lipid image generated based on the temperature dependent photoacoustic

response reflects lipid deposits inside the plaque. However, compared to Figure 5.3(a),

Figure 5.3(b) showed more lipid in the periadventitial regions of the aorta. The difference

indicates that although the lipid deposits in plaques and the periadventitial fat have

similar optical property, their thermal photoacoustic responses are different.

IVPA Images taken at two temperatures

Co-registered IVUS Images

Combined IVUS and thermal IVPA image

Spatial Filter(Running average)

Calculate PA difference

Image segmentation

93

Figure 5.3: (a) Lipid image generated by temperature dependent IVPA imaging overlaid

onto IVUS image to demonstrate the distribution of lipid in an

atherosclerotic rabbit aorta. (b) Spectroscopic IVPA image of lipid at the

same cross-section of the aorta.

5.3.2 Imaging lipid in vivo at 1720 nm wavelength

Besides the 1210 nm wavelength peak used for spectroscopic IVPA imaging of

lipid presented in Chapter 2, lipid has another optical absorption peak at 1720 nm [5-6].

An atherosclerotic aorta from a balloon injured rabbit was imaged ex vivo at both 1210

and 1720 nm wavelength using the bench-top IVPA/IVUS imaging system (Figure 4.1).

With the same optical alignment, the IVPA image acquired at 1210 nm wavelength

showed much stronger photoacoustic signal from the outer boundary than the image

taken at 1720 nm wavelength (Figure 5.4(c,f)). The high photoacoustic signal at the outer

boundary is induced by the scattering mismatch between the vessel tissue and saline

solution. The scattering mismatch created a strong subsurface fluence that led to strong

photoacoustic signal. At 1720 nm, tissue optical scattering is significantly lower than that

at 1210 nm. Therefore, the IVPA image showed lower photoacoustic signal at the outer

(b)(a)

94

boundary (Figure 5.4(e)). Unlike lipid imaging at 1210 nm wavelength, where

spectroscopic analysis has to be performed to eliminate strong photoacoustic signals

generated by strong subsurface fluence but not strong optical absorption, lipid imaging at

1720 nm may directly detect lipid without spectroscopic analysis (Figure 5.4(e-f)).

Moreover, due to the reduced optical scattering of blood, in vivo lipid imaging at

1720 nm may achieve better imaging depth than imaging at shorter wavelengths.

Figure 5.4: (a-c) IVUS, IVPA, and combined IVPA/IVUS images taken at 1210 nm

wavelength. (d-f) IVUS, IVPA, and combined IVPA/IVUS images taken at

1720 nm wavelength. The IVUS and IVPA images are shown at a 35 dB

dynamic range.

(a) (b) (c)

(d) (e) (f)

95

5.3.3 Designing integrated catheter for combined IVPA/IVUS imaging in vivo

An integrated catheter capable of in vivo combined IVPA/IVUS imaging is

required for in vivo imaging. The catheter should deliver nanosecond duration laser

pulses into the vessel, receive photoacoustic signals and perform conventional IVUS

imaging. The diameter of the catheter should be around 1 mm, and flexible enough for

intracoronary imaging. Figure 5.5 showed one of the designs for an integrated catheter

based on a side-fire optical fiber and a single element IVUS catheter [7]. The distal end

of the side-fire fiber was polished 45 degrees, and capped with a quartz tube to redirect

the light towards the vessel wall. The integrated catheter could image the optical

absorbing inclusions embedded in the tissue mimicking phantom in both IVPA and IVUS

modes (Figure 5.5(c-e)). Jansen et al. used a similar design and made an integrated

catheter 1.2 cm in diameter [8]. Other designs of the light delivery system, such as micro-

optics based assembly, can also be used to construct the integrated catheter [9].

96

Figure 5.5: (a) Photo of the distal end of the integrated catheter. (b) Tissue mimicking

phantom with three optical absorbing inclusions. (c) IVUS image of the

phantom. (d) IVPA image of the phantom. (e) Combined IVPA/IVUS image

of the phantom.

5.3.4 Accurately detecting of vessel lumen borders

High frequency IVUS imaging provides high resolution images, but at the same

time is more likely to be affected by the high acoustic scattering from the blood than

imaging at low frequencies. Strong scattered acoustic signals from blood impair

visualization of the border of the vessel lumen, and therefore affect accurate estimation of

the luminal narrowing and area of the necrotic core. Blood signal in conventional IVUS

imaging can be reduced by subtraction, averaging, saline flush, or more sophisticated

image processing based on the temporal and spatial variation of speckles from blood [10-

IVUS Catheter

Optical Fiber

(a) (b)

(c) (d) (e)

97

11]. IVPA imaging may image the lumen borders with minimal image processing. Two

methods can be used to accurately detect the lumen borders. The first method is utilizing

the optical absorption property of blood: detect the luminal border by accurately

delineating the border of the luminal blood. The optical wavelength chosen for this

purpose should satisfy 1) optical absorption of blood at the wavelength is strong enough

to produce IVPA signals, and 2) the optical absorption and scattering of blood is not too

strong so that imaging depth can be guaranteed. The second method for border detection

is utilizing the scattering mismatch of the blood and vessel wall. As shown in Figure 5.6,

when imaging with an integrated catheter, due to scattering mismatch between blood and

the vessel wall, strong photoacoustic signals were presented at the luminal borders when

imaging at 900 nm wavelength. Note that the excised aorta was immersed in 30% whole

blood in this experiment. In the future, the optimal wavelength for lumen border

detection should be investigated.

Figure 5.6: IVUS (a), IVPA (b), and combined IVUS/IVPA (c) images of an

atherosclerotic rabbit aorta acquired at 900 nm wavelength using an

integrated IVUS/IVPA imaging catheter. The aorta was embedded inside

30% whole blood.

(a) (b) (c)

98

5.3.5 Imaging thrombus and vasa vasorum

Thrombus in an artery is a blood clot formed after plaque rupture. After plaque

rupture, the constituents inside plaques are released into the lumen, which attract platelets

and forming thrombus [12]. Arterial thrombus is rich in platelets and fibrin and has a high

possibility lead to severe stenosis, myocardium infarction or stroke. Thrombus may be

identified by spectroscopic IVPA imaging based on the difference on optical property

between thrombus and luminal blood.

Vasa vasorum are micro-vessels developed inside or around the arterial wall.

Atherosclerotic plaques have more extensive vasa vasorum distribution [13]. Although

spectroscopic photoacoustic imaging has been widely used to image blood vessels, IVPA

imaging of vasa vasorum is challenging because it requires to image through luminal

blood. Meanwhile, the distance between the micro-vessels and the catheter, and the small

vessel diameter of the vessel make IVPA hard to resolve an individual micro-vessel.

However, spectroscopic IVPA has the potential to detect high density vasa vasorum.

5.3.6 Engineering contrast agents for high sensitivity and specificity IVPA imaging

Using spherical Au NPs as a contrast agent for IVPA imaging has the advantage

of detecting the interaction of particles with cells. However, spherical Au NPs needs to

aggregate at a relatively high concentration to elevate their optical absorption spectrum in

the NIR wavelength range and therefore, to become detectable for IVPA imaging. Other

types of Au NPs, such as gold nanorods, have high optical absorption in the NIR range

[14-16]. The detection limit of IVPA imaging for these contrast agents may be much

lower than for spherical Au NPs. Moreover, gold nanorods have a narrow tunable

absorption peak in the NIR range, and high optical absorption contrast compared to other

types of tissue. Therefore gold nanorods may be more easily distinguished from

background tissue using spectroscopic analysis.

99

The Au NPs used in this study were coated with PEG-thiol, which prevented the

aggregation of particles and prolonged the particle circulation time. PEGylated Au NPs

were internalized passively by macrophages. Active delivery of contrast agents can be

achieved by conjugating antibodies or ligands to the surface of the nanoparticles that

specifically target the biomarkers. Active delivery may increase the delivery efficiency of

the contrast agents. One challenge facing the design of targeting particles is the avoidance

of fast clearance of the particles. Surface modification may trigger the immune system to

eliminate the contrast agents before they reach the targeted cells or molecules. Therefore,

there may be a tradeoff between uptake or binding speed and clearance time when

designing the targeted nanoparticles.

Nanoparticles can also be engineered to simulate assemblies inside the human

body to avoid triggering the immune response and achieve efficient delivery. HDL-like

nanoparticles were engineered to encapsulate various contrast agents inside the

monolayer phospholipid. The surface of the particle was decorated apolipoprotein to

simulate HDL particles [17]. Contrast agents can also be loaded inside the cells, such as

monocytes, to image plaques as well as monitor the cell tracking in atherosclerotic

disease [18].

5.3.7 Delivering contrast agents

The delivery of contrast agents to their target sites in molecular imaging is

challenging. Plasma circulation time, particle size and shape will all affect the efficiency

of contrast agent delivery. In chapter 4, it has been shown that in vivo delivery efficiency

of spherical Au NPs is different from the results acquired in cell culture environments.

Twenty nanometer diameter particles had a longer blood circulation time than 50 nm

particles and can penetrate deep inside the plaques. It is not clear what the optimal size of

100

a particle is for molecular imaging of atherosclerosis. The size of lipoprotein particles

may provide some insight. LDL and HDL particles are more likely to enter into the vessel

wall than larger particles such VLDL (very low density lipoprotein) particles. Therefore,

there may be an upper limit of size around 40 nm for engineered contrast agents to be

passively delivered into atherosclerotic plaques. Meanwhile, the shape of particles (e.g.

rods versus sphere) will also affect how the particles enter the leaky endothelium in a

diseased artery.

For intravascular imaging, the mechanical property of the flow and the

morphology of the artery and plaque may affect the distribution of particles inside the

vessel wall. Atherosclerotic plaques tend to accumulate at the vessel bifurcation, which

may due to the flow-related haemodynamics. Research on the relative distribution of

plaques and nanoparticles delivered through blood may provide insights on the

distribution of plaques inside the artery.

5.4 CONCLUSION

Intravascular photoacoustic imaging is an emerging intravascular imaging

modality that can provide the depth-resolved optical absorption property of the vessel

wall. Based on the characteristic optical absorption spectra of tissues or contrast agents,

IVPA imaging may determine plaque composition, and perform molecular/cellular

specific imaging. Therefore, intravascular ultrasound guided IVPA imaging has the

potential for real-time detection of vulnerable plaques with high accuracy and sufficient

resolution.

Lipid deposits and phagocytically active macrophages in atherosclerotic plaques

were detected ex vivo with spectroscopic IVPA imaging. Lipid deposits were detected

101

based on their absorption peak around 1210 nm wavelength. Phagocytically macrophages

that were in vivo labeled with PEGylated Au NPs can also be detected with spectroscopic

IVPA imaging in the NIR wavelength range with high sensitivity. Because the spectra of

lipids and macrophages loaded with Au NPs do not overlap, IVPA can image

macrophage activity around the lipid-rich plaques in a rabbit model of atherosclerosis. In

the future, in vivo lipid and macrophage detection will be studied with an integrated

IVPA/IVUS imaging catheter, and IVPA imaging of other constituents in atherosclerotic

plaques will be investigated.

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