Jesse Aaron, Seung-Yup and Chris Condit for their mentoring, involvement, and ...... Kalambur, V.S., Han, B., Hammer, B.E., Shield, T.W., Bischof, J.C. 2005. In.
Copyright by Jung Hwan Oh 2006
The Dissertation Committee for Jung Hwan Oh Certifies that this is the approved version of the following dissertation :
Magneto-Motive Detection of Nanoparticles and Hemoglobin
Committee:
Thomas E. Milner, Supervisor
Marc D. Feldman
Stanislav Emelianov
Shaochen Chen
J. Stuart Nelson
Magneto-Motive Detection of Nanoparticles and Hemoglobin
by Jung Hwan Oh, B.S.; M.S.E
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 December, 2006
Dedication
To my mother, Jung-Ja Kim, and to my wife, Jiyoung Hur, for helping me reach this one.
Acknowledgements
I would like to express my heart-felt appreciation and gratitude to my supervisor, Professor Thomas E. Milner for his unending support, guidance, and understanding to pursue my Ph.D. in the United States. He has allowed me the freedom to work independently and his knowledge and strong theoretical base was indispensable and essential to this whole research. I was fortunate to have the opportunity to work with Professor Marc D. Feldman. Without his guidance, and wise counsel, I could not have done my Ph.D. I cannot express in this short paragraph how much I appreciate his thoughtful insight and guidance during five-and-a-half years. I owe a special thanks to Professor Stanislav Emelianov for his idea and motivations in my experimental research. I would also like to thank Professors Shaochen Chen and J. Stuart Nelson for serving on my dissertation committee. Their advice enhanced the quality of my research. I also want to thank my fellow collaborators and friends, Jeehyun Kim, Ho Lee, Jihoon Kim, Hyun Wook Kang, Suhyun Park, Jesung Park, Nate Kemp, Jesse Aaron, Seung-Yup and Chris Condit for their mentoring, involvement, and enthusiastic contributions to this research. I would like to extend special thanks to many of the people who made contributions to my research.
v
Most importantly, I would like to thank my best friend and wife, Jiyoung Hur, for all her unending support and understanding. I am especially thanks for my two beautiful daughters, Chaeun and Sehyun, who supported me in their special way.
vi
Magneto-Motive Detection of Nanoparticles and Hemoglobin
Publication No._____________
Jung Hwan Oh, Ph.D. The University of Texas at Austin, 2006
Supervisor: Thomas E. Milner
Magneto-motive diagnostic systems combining optical coherence tomography (OCT) and ultrasonography (US) can be used to detect magnetic nanoparticles and red blood cells (RBCs) containing iron in response to an external magnetic field. Magnetic force on magnetic nanoparticles and hemoglobin iron may be varied by applying an external current to a solenoid containing a conical iron core that substantially increases and focuses a magnetic field (Bmax = 2 Tesla). In
studies
using
superparamagnetic
iron
oxide
(SPIO)
and
monocrystalline iron oxide (MION) nanoparticles, the hypothesis of this research is that tissue-based macrophage cells can be detected in an external magnetic field
vii
after taking up SPIO nanoparticles in liver and MION nanoparticles in the atherosclerotic high-risk plaque. Therefore, magneto-motive OCT (MM-OCT) and magneto-motive ultrasound (MM-US) can detect iron-laden tissue motion in response to an external magnetic field. Important parameters of magnetic forceinduced displacement are optical path length change (Δp) in MM-OCT and Doppler frequency shift (fd) in MM-US. Variations of these parameters in response to an external magnetic field may aid understanding and identification of lesions in biomedical engineering applications, especially inflammatory diseases such as cancer and atherosclerosis. In studies involving human red blood cells (RBCs), the hypothesis of the proposed research is that magnetic permeability of deoxygenated RBCs is sufficient such that when positioned in a high magnetic field gradient, translational and rotational motion is modified. Moreover, our hypothesis states that a high magnetic field can increase blood viscosity, resulting in reduction of blood flow rate, enabling not only imaging and measurement of small caliber vessels, but also providing improved laser treatment for port wine stains (PWS), telangiectasias, and hemangiomas.
viii
Table of Contents List of Tables ..................................................................................................... xii List of Figures ................................................................................................... xii Chapter 1 Introduction and Background ........................................................... 1 1.1
Organization of the Dissertation............................................................ 1
1.2
Vascular biology in atherosclerosis ....................................................... 5
1.3
Molecular imaging of atherosclerosis ................................................... 6
Chapter 2 Theoretical development of magnetic force and induced motion in elastic media......................................................................................................... 11 2.1 Magnetic nanoparticles........................................................................ 11 2.1.1 Magnetic field effect on magnetic nanoparticles ............................ 14 2.2. Motion of magnetic nanoparticle dynamics ........................................ 19 2.2.1 Motion of magnetic nanoparticle dynamics; steady state ............... 19 2.2.2 Motion of magnetic nanoparticle dynamics; transient and steady state ........................................................................................................... 22 2.3 Tissue surface displacement in an elastic media ................................ 24 2.3.1 Galerkin’s vector for elasticity analysis .......................................... 24 2.3.2 Force at a point in a semi infinite elastic media ............................ 26 Chapter 3 Detection of atherosclerotic vulnerable plaque using optical coherence tomography ....................................................................................... 37 3.1
Introduction .......................................................................................... 37
3.2
Animal model and experiment setup ................................................... 38
3.3
Results................................................................................................... 40
3.4
Discussion and Conclusions ............................................................... 46
Chapter 4 Magneto-motive detection of magnetic nanoparticles in tissue using DP-OCT ..................................................................................................... 51 4.1
Introduction .......................................................................................... 51
4.2 Materials and methods ......................................................................... 52 4.2.1 Superparamagnetic iron oxide (SPIO) nanoparticles ................ 52
ix
4.2.2 Magnetic force on superparamagnetic iron oxide (SPIO) nanoparticles ................................................................................................ 53 4.2.3 Magnetic field generator .............................................................. 55 4.2.4 Animal model and histology......................................................... 58 4.2.5 DP-OCT measurements ............................................................... 59 4.3.
Results................................................................................................... 62
4.4
Discussion ............................................................................................. 70
Chapter 5 Detection of magnetic nanoparticles in tissue using magnetomotive ultrasound ............................................................................................... 77 5.1
Abstract ................................................................................................. 77
5.2
Introduction .......................................................................................... 78
5.3 Material and methods........................................................................... 80 5.3.1 Superparamagnetic iron oxide (SPIO) nanoparticles .................... 80 5.3.2 Animal preparation ......................................................................... 81 5.3.3 Experimental preparation ................................................................ 82 5.4
Results................................................................................................... 85
5.5 Discussion............................................................................................. 96 5.4.1 Application to molecular imaging: MM-US................................ 99 5.4.2 Advantages of magneto-motive ultrasound (MM-US).............. 100 Chapter 6 Magneto-mechanical detection of atherosclerotic macrophages with optical coherence tomography ................................................................ 108 6.1
Abstract ............................................................................................... 108
6.2
Introduction ........................................................................................ 109
6.3. Material and methods......................................................................... 111 6.3.1 Iron oxide nanoparticles (MION).................................................. 111 6.3.2 Experiment preparation ................................................................. 112 6.4
Results................................................................................................. 113
Chapter 7 Hemoglobin contrast in magneto-motive optical Doppler tomography ....................................................................................................... 129 7. 1
Introduction ........................................................................................ 129
7. 2
Method and experimental setup......................................................... 131
7. 3
Results and Discussion....................................................................... 136
x
7. 4
Conclusions ........................................................................................ 142
Appendix A Magneto-motive detection of macrophages in liver and spleen by DP-OCT ............................................................................................ 146 Bibliography ...................................................................................................... 163 VITA ................................................................................................................... 178
xi
List of Tables TABLE 1-1 TARGETED FOR MOLECULAR IMAGING OF ATHEROSCLEROSIS .............. 6 TABLE 2-1 CLASSIFICATION OF SPIO NANOPARTICLES ....................................... 12 TABLE 2-2 PROPERTIES AND APPLICATIONS OF SPIO NANOPARTICLES ............... 12 TABLE 2-3 MAGNETIC SUSCEPTIBILITY OF SPIO AND MION .............................. 17 TABLE 3-1 LIPID CORE AREA MEASUREMENT BY OCT AND HISTOLOGY (μM2) . .. 43 TABLE 3-2 PREPARATION FOR HISTOLOGY SLIDES (ARTERY)............................... 48
xii
List of Figures FIGURE 1-1 PROGRESSION
OF ATHEROSCLEROSIS AND POTENTIAL TARGETS FOR
IMAGING OF HIGH-RISK VULNERABLE PLAQUE. (ADAPTED FROM
FIGURE 2-1 OUTLINE
[4]) .............. 7
OF THEORETICAL MODEL OF MAGNETIC FORCE ACTING ON
MAGNETIC NANOPARTICLES IN ELASTIC MEDIA. ............................................. 13
FIGURE 2-2 MAGNETIZATION MAGNETIC FILED FOR
AS
A
MION
FUNCTION
OF
MAGNETIZATION
VERSUS
NANOPARTICLES AT ROOM TEMPERATURE.
SOLID LINE REPRESENTS FITTING DATA USING FUNCTION AT MAGNETIC FIELD
(0-5 TESLA) (A),
LANGEVIN
THE
NONLINEAR
AND MAGNETIC FIELD
(0-1
TESLA) (B). .................................................................................................... 16 FIGURE 2-3 MAGNETIC FORCE ACTING ON SPIO AND MION NANOPARTICLES..... 19 FIGURE 2-4 SIMULATED
RESULTS
SPIO
NANOPARTICLES MOTION WITH A
1 HZ, 2
TESLA MAGNETIC FORCE APPLIED TO SPIO NANOPARTICLES......................... 21 FIGURE 2-5
SIMULATION RESULTS NANOPARTICLE DISPLACEMENT DRIVEN BY AN
EXTERNAL MAGNETIC FIELD;
(A)
EXTERNAL MAGNETIC FLUX DENSITY,
(B)
TRANSIENT, AND (C) STEADY STATE MOVEMENT ............................................ 23
FIGURE 2-6 CYLINDRICAL VERTICAL
FORCE
COORDINATES FOR A SEMI-INFINITE ELASTIC MEDIA.
(P)
IS APPLIED AT POINT
(0, 0,
C) IN THE POSITIVE Z-
DIRECTION [30]. ............................................................................................. 27
FIGURE 2-7 SIMULATION RESULT OF IRON-LADEN TISSUE SURFACE DISPLACEMENT DUE TO NANOPARTICLE MOVEMENT. .............................................................. 31
FIGURE 3-1 EXPERIMENTAL
SETUP FOR IMAGING MOUSE ARTERY USING OPTICAL
COHERENCE TOMOGRAPHY (OCT). ................................................................ 40
FIGURE 3-2 COMPARISON
OF VULNERABLE PLAQUE BY OPTICAL COHERENCE
TOMOGRAPHY AND HISTOLOGY: HISTOLOGY (A) AND OCT IMAGE (B). ......... 41
xiii
FIGURE 3-3 COMPARISON
OF
STABLE
PLAQUE
BY
OPTICAL
COHERENCE
TOMOGRAPHY AND HISTOLOGY: HISTOLOGY (A) AND OCT IMAGE (B). ......... 42
FIGURE 3-4 THREE-DIMENSIONAL RECONSTRUCTION OF INNOMINATE ARTERIES.. 43 FIGURE 3-5 CALCIFICATION
OF PLAQUE.
THE
UPPER PANEL IS THE
VON KOSSA
STAIN DEMONSTRATING THE PRESENCE OF CALCIUM IN ATHEROSCLEROTIC PLAQUE BY THE SPECKLED BLACK STAINING. CORRESPONDING
OCT
THE
LOWER PANEL IS THE
IMAGE SHOWING ONLY A PORTION OF THE PLAQUE
WHICH CONTAINS THE SPECKLED CALCIUM. ................................................... 45
FIGURE 4-1 COMPUTED
MAGNETIC FLUX DENSITY DISTRIBUTIONS SURROUNDING
THE MAGNETIC FIELD GENERATOR USING FINITE ELEMENT METHOD THE TWO-DIMENSIONAL AXISYMMETRIC
(A)
R-Z
PLANE.
MAGNETIC
(FEM)
IN
FIELD WITH
AND WITHOUT (B) IRON CORE INSIDE SOLENOID ARE SHOWN IN TOP PANEL
AND ILLUSTRATION OF THE MAGNETIC FIELD GENERATOR WITH AN IRON CORE IN THE CENTER OF THE SOLENOID (C).............................................................. 57
FIGURE 4-2 SCHEMATIC DIAGRAM OF A DIFFERENTIAL PHASE OPTICAL COHERENCE TOMOGRAPHY
(DP-OCT)
GENERATOR: (A)
DP-OCT
DP-OCT
SYSTEM COMBINED WITH A MAGNETIC FIELD SYSTEM, (B) COLLINEAR CONFIGURATIONS OF THE
SAMPLE PATH AND DESIGN OF THE MAGNETIC FIELD GENERATOR
CONTAINING A CONICAL IRON CORE. .............................................................. 60
FIGURE 4-3 TISSUE SPIO
DOSES
SURFACE DISPLACEMENT
(1.0, 0.1
MMOL
FE/KG
MAGNETIC FIELD EXCITATION DISPLACEMENT
(ΔZS)
(ΔZS)
IN LIVERS WITH DIFFERENT
AND SALINE CONTROL) USING FOCUSED
(2 HZ, 4 VPP) (A). TISSUE
IN SPECIMENS WITH DOSES
1.0
MMOL
SURFACE
FE/KG SPIO (B),
0.1 MMOL FE/KG SPIO, AND A SALINE CONTROL LIVER................................. 63 FIGURE 4-4 MAXIMUM
TISSUE SURFACE DISPLACEMENT
LIVER SPECIMENS DUE
(ΔZS)
IN IRON-LADEN
TO NANOPARTICLE MOVEMENT IN RESPONSE TO A
FOCUSED MAGNETIC FIELD FOR MICEINJECTED WITHVARIOUS SPIO DOSES (1.0
xiv
AND
0.1
MMOL
FE/KG
BODY WEIGHT).
APPLIED VOLTAGE RANGING FROM
2
THE TO
INPUT FREQUENCY IS
8 VPP (A)
2 HZ
WITH
AND MAGNETIC FIELD
STRENGTH AT EACH INPUT VOLTAGE (B)......................................................... 64
FIGURE 4-5 TISSUE
SURFACE
DISPLACEMENT
(ΔZS)
IRON-LADEN
IN
LIVER
SPECIMENS DUE TO NANOPARTICLE MOVEMENT IN RESPONSE TO A FOCUSED MAGNETIC FIELD WITH A SWEPT FREQUENCY
SPIO
INJECTED WITH VARIOUS
DOSES
(1.0
(1-10 HZ)
AND
0.1
INPUT FOR MICE
MMOL
FE/KG). (A).
TISSUE SURFACE DISPLACEMENT (ΔZS) AT 1.0 MMOL FE/KG SPIODOSE (B), 0.1 MMOL FE/KG SPIO DOSE (C), AND A SALINE CONTROL LIVER (D)................... 66
FIGURE 4-6 MAXIMUM
TISSUE SURFACE DISPLACEMENT
(ΔZS)
IN IRON-LADEN
LIVER SPECIMENS DUE TO NANOPARTICLE MOVEMENT IN RESPONSE TO A FOCUSED MAGNETIC FIELD WITH A SWEPT FREQUENCY
(1-10 HZ)
INPUT FOR
MICE INJECTED WITH VARIOUS SPIO DOSES (1.0 AND 0.1 MMOL FE/KG). INPUT SWEPT FREQUENCY RANGED FROM
1-10 HZ
VOLTAGES INCREASING FROM 2 TO 10
OVER
2
SECONDS WITH INPUT
VPP (A) AND MAGNETIC FIELD STRENGTH
AT EACH INPUT VOLTAGE (B).......................................................................... 68
FIGURE 4-7 HISTOLOGICAL CROSS-SECTION OF IRON LADEN LIVER SPECIMEN WITH PRUSSIAN
BLUE STAIN.
A
HIGH CONCENTRATION OF IRON IS OBSERVED
(MAGNIFICATION: 20 X). BLUE COLORED REGIONS ARE IRON NANOPARTICLES ENGULFED BY LIVER BASED MACROPHAGE
KUPFFER
CELLS (A), AND IRON-
LADEN MACROPHAGES BY IMAGE PROCESSING (B). ........................................ 69
FIGURE 5-1 SCHEMATIC DIAGRAM OF EXPERIMENTAL SETUP WITH MAGNETIC FIELD GENERATOR AND CONICAL IRON CORE INSIDE SOLENOID................................ 84
FIGURE 5-2 ULTRASOUND
GRAYSCALE (A-E), COLOR POWER
DOPPLER (F-J)
AND
M-MODE (K-O) IMAGES OF LIVERS WITH DIFFERENT SPIO DOSES (1.5, 1.0, 0.5, AND
0.1
MMOL
FE/KG BODY WEIGHT AND CONTROL LIVER). LIVER WITH HIGH
DOSE ADMINISTRATION OF
SPIO (F)
SHOWS SIGNIFICANT INCREASING COLOR
xv
DOPPLER
SIGNAL WHILE NORMAL LIVER
DOPPLER
APPRECIABLE COLOR
SIGNAL.
(J)
DOES NOT EXHIBIT ANY
M-MODE
SIGNAL INTENSITY AND
DISPLACEMENT IS PROPORTIONAL TO CONCENTRATION OF
SPIO
MODE SIGNAL OBTAINED FROM A HIGH DOSE SPECIMEN
DOSE.
(K)
M-
CLEARLY
DEMONSTRATES SINUSOIDAL PATTERN OF THE DISPLACEMENT ONCE THE MAGNETIC FIELD IS TURNED ON...................................................................... 88
FIGURE 5-3 DOPPLER SHIFT MEASURED IN LIVER SPECIMENS WITH DIFFERENT SPIO DOSES
(1.5, 1.0, 0.5,
AND
0.1
MMOL
FREQUENCY INPUT ((A)-(E)) AND 1
FIGURE 5-4 DOPPLER
FE/KG
BODY WEIGHT) USING SWEPT
HZ SINUSOIDAL INPUT ((F)-(J)). ............... 90
SHIFT FROM LIVER SPECIMENS
WEIGHT) WITH CONSTANT
(8 VPP)
(1.0
MMOL
FE/KG
AMPLITUDE SINUSOIDAL INPUT.
BODY
IN
ALL
EXPERIMENTS, THE PEAK DOPPLER SHIFT PATTERN EXHIBITS A PERIODICITY AT EXACTLY TWICE THE FREQUENCY OF THE APPLIED SIGNAL............................. 91
FIGURE 5-5 PEAK FREQUENCY SHIFT IN LIVERS WITH DIFFERENT SPIO 1.0, 0.5,
AND
0.1
MMOL
FREQUENCY INPUT (1-10
INSERT
GRAPH
(B)
FE/KG
DOSES
(1.5,
AND CONTROL) WHEN APPLYING A SWEPT
HZ) WITH DIFFERENT INPUT VOLTAGES (2 TO 10 VPP).
SHOWS MAGNETIC FLUX DENSITY OF THE SWEPT
FREQUENCY INPUT SIGNAL VS. INPUT PEAK-TO-PEAK VOLTAGE. .................... 93
FIGURE 5-6 HISTOLOGICAL CROSS-SECTION OF IRON-LADEN LIVER WITH PRUSSIAN BLUE STAIN.
CONTROL
SPECIMEN (A) AND A HIGH CONCENTRATION OF IRON
(1.5 MMOL FE /KG BODY WEIGHT) (B) ARE OBSERVED (MAGNIFICATION: 20 X). BLUE COLORS REGIONS ARE IRON OXIDE NANOPARTICLES ENGULFED BY LIVER BASED MACROPHAGE KUPFFER CELLS............................................................ 95
FIGURE 5-7 AVERAGE
GREY SCALE VALUE OF
B-SCAN
IMAGES WITH DIFFERENT
SPIO DOSES (1.5, 1.0, 0.5, 0.1 MMOL FE/KG AND CONTROL) ((A)-(E)). ......... 97 FIGURE 6-1 MAGNETO-MECHANICAL 0.2
MMOL
FE/KG
OF
TISSUE SURFACE DISPLACEMENT
MION-LADEN
VPP (BMAX = 0.25 TESLA) (A),
(ΔZS(T))
AORTA SPECIMENS BY APPLYING
IN
2 HZ 4
AND MAGNETO-MECHANICAL TISSUE SURFACE
xvi
DISPLACEMENT
(ΔZS(T))
IN
0.2
FE/KG
MMOL
OF
MION-LADEN
SPECIMENS BY APPLYING A SWEPT FREQUENCY EXCITATION (1-
AORTA
10 HZ) OVER A
1 SECOND TIME-PERIOD (BMAX = 1.70 TESLA) (B). ....................................... 115 FIGURE 6-2 MAGNETO-MECHANICAL MION-LADEN
TISSUE SURFACE DISPLACEMENT
(ΔZS(T))
IN
AORTA SPECIMENS WITH INPUT FREQUENCY RANGING FROM
HZ TO 5 HZ IN 1 HZ INCREMENTS WITH MION
DOSE
(0.2
MMOL
2
FE/KG BODY
WEIGHT). ...................................................................................................... 117
FIGURE 6-3 QUANTITATIVE AND-WHISKER
PLOT
ANALYSIS OF
PEAK-TO-PEAK
OF
SURFACE DISPLACEMENT
MION
(ΔZS(T))
AORTA SPECIMENS USING BOXMAGNETO-MECHANICAL
VS. SINUSOIDAL
(2 HZ)
TISSUE
INPUT VOLTAGE
WITH 0.2 MMOL FE/KG MION DOSE (A) AND CONTROL SPECIMENS (B). ...... 119
FIGURE 6-4 TISSUE
HISTOLOGICAL IMAGES OF ATHEROSCLEROTIC MION-LADEN AORTA SECTION
WHERE
MAGNETO-MECHANICAL
DISPLACEMENT WAS MEASURED WITH DP-OCT SINUSOIDAL INPUT).
MION
DOSE
(0.2
PRUSSIAN BLUE (A)
MMOL
FE/KG
TISSUE
(ΔZS= 80 NM WITH 2 HZ, 2 VPP
AND
RAM-11
STAINS
BODY WEIGHT) ARE SHOWN.
HISTOLOGIC SECTIONS INDICATED IN
(A)
SURFACE
AND
(B)
ARE
5 μM
(B)
AT A
ADJACENT APART AND
DEMONSTRATE PRESENCE OF MION IN MACROPHAGES. .............................. 120
FIGURE 7-1 SCHEMATIC
DIAGRAM OF THE
LUMINESCENT DIODE,
FIGURE 7-2 SCHEMATIC
MM-ODT
SYSTEM.
SLD: SUPER-
HPF: HIGH PASS FILTER, LPF: LOW PASS FILTER....... 134
DIAGRAM OF THE PROBE BEAM, BLOOD FLOW SAMPLE,
SOLENOID COIL, AND FUNCTION GENERATOR. .............................................. 135
FIGURE 7-3 OCT/ODT
IMAGES OF A TURBID SOLUTION WITH AND WITHOUT AN
EXTERNAL MAGNETIC FIELD.
(A), (B) OCT
MAGNETIC FIELD, RESPECTIVELY. (C), (D)
AND
OCT
ODT
AND
IMAGES WITHOUT A
ODT
IMAGES WITH A
50
HZ MAGNETIC FIELD, RESPECTIVELY............................................................ 137
xvii
FIGURE 7-4 M-MODE ODT (HCT 18%) ODT
IMAGES OF THE DILUTED DEOXYGENATED BLOOD FLOW
WITH AND WITHOUT AN EXTERNAL MAGNETIC FIELD.
IMAGES OF
5
MM/S BLOOD FLOW WITHOUT/WITH A
FIELD, RESPECTIVELY. WITHOUT/WITH A 50
FIGURE 7-5 DOPPLER
(C), (D) ODT
IMAGES OF
30
50 HZ
(A), (B)
MAGNETIC
MM/S BLOOD FLOW
HZ MAGNETIC FIELD, RESPECTIVELY........................... 139
FREQUENCY SHIFT PROFILES
MAGNETIC FIELD, (B) WITH A 50
(A)
WITHOUT AN EXTERNAL
HZ MAGNETIC FIELD. ................................ 141
xviii
LIST OF SYMBOLS Acronyms apoE
Apolipoprotein E
CAD
Coronary Artery Disease
CD40
Cluster of Differentiation
CHD
Coronary Heart Disease
CLIO
Cross-linked Iron Oxide
ECM
Extracellular Cell Membrane
EGF
Epidermal Growth Factor
E-Selectin
Formally ELAM-1
FMT
Fluorescence Mediated Tomography
FRI
Fluorescence Reflectance Imaging
Gd-DTPA
Gadolinium (Iii)-Diethyltriaminepentaacetic Acid
HDL
High Density Lipoprotein
HSPs
Heat-Shock Proteins
ICAM
Intercellular Cell Adhesion Molecule
IFN-γ
Interferon Gamma
IL
Interleukin
IVUS
Intravascular Ultrasound
LDL
Low Density Lipoprotein
MB
Microbubble
MCP-1
Monocyte Chemoattractant Protein-1
M-CSF
Macrophage-Colony Stimulating Factor
MMP
Matrix Metalloproteinase
MRI
Magnetic Resonance Imaging
xix
MT-MMPS
Membrane Type Mmps
NF-kB
Nuclear Factor-Kb
NIRF
Near Infrared Fluorescence
OCT
Optical Coherence Tomography
Ox-LDL
Oxidized Low Density Lipoprotein
PET-CT
Positron Emission Tomography-Computed Tomography
P-Selectin
Formally GMP-140
RAM-11
Anti-Rabbit Monocyte/Macrophage Antibody
SMC
Smooth Muscle Cells
SPIO
Superparamagnetic Iron Oxide
SRA
Scavenger Receptor A
TGF-β
Transform Growth Factor
TNF-α
Tumor-Necrosis Factor-α
USPIO
Ultrasmall Superparamagnetic Iron Oxide
VCAM-1
Vascular Cell Adhesion Molecule-1
PECAM-1
Platelet-Endothelial Cell Adhesion Molecule-1
WHHL
Watanabe Hereditable Hyperlipidemic
xx
Chapter 1 Introduction and Background 1.1
Organization of the Dissertation Chapter 1 of this dissertation contains an introduction and review of the
basic mechanisms and progression of atherosclerosis in the inflammatory process of coronary artery disease, and discusses new insights into the role of cardiovascular molecular imaging. Chapter 2 describes properties of magnetic nanoparticles. Theoretical development of magnetic force and induced motion while applying magnetic field acting on magnetic nanoparticles is described. I derived analytic expression for tissue-surface displacement from Mindlin’s theory of elasticity in semi-infinite media. The initial motion of magnetic nanoparticles is driven by a constant magnetic force and displays a damped transient motion before steady state motion dominates at twice the modulation frequency of the applied sinusoidal magnetic field. Motion of the nanoparticles at double the modulation frequency originates from the magnetic force being proportional to the product of magnetic flux density and its gradient. Chapter 3 describes imaging modalities to identify atherosclerotic vulnerable plaque using optical coherence tomography (OCT). The feasibility of OCT to identify the components of vulnerable plaque is demonstrated in a wellestablished murine model of human atherosclerosis. These findings suggest that
1
OCT holds promise for the identification of features characteristic of vulnerable plaque including fibrous cap thickness, lipid core size, and the percentage of lipid content. Chapter 3 was published in Journal of Catheterization and Cardiovascular Interventions on April 6, 2006, Volume 67, issues 6, pp.915-923, “Detection of Vulnerable Plaque in a Murine Model of Atherosclerosis with Optical Coherence Tomography” and also formed a basis in a Veterans Administration (VA) Grant 2006 received by Dr. Feldman entitled “Identification of vulnerable plaque with optical coherence tomography”. Chapter 4 describes the capability of magneto-motive differential-phase optical coherence tomography (DP-OCT) to detect magnetic nanoparticles taken up by liver parenchymeal macrophages (Kupffer cells). By applying an external time-varying and high-intensity focused magnetic field, these experiments demonstrate a novel diagnostic modality to detect macrophages that have taken up SPIO nanoparticles. A portion of this chapter was submitted to Laser Surgery and Medicine Journal, entitled “Magneto-motive detection of tissue based macrophages by differential phase optical coherence tomography” and is under review for publication. Chapter 5 demonstrates magneto-motive ultrasonic detection of superparamagnetic iron oxide (SPIO) nanoparticles as marker of macrophage recruitment in tissue. Frequency response of the ultrasound Doppler signal from the iron-laden tissue was exactly twice the exciting frequency of the input signal
2
as predicted by magnetic force equations. Results of this chapter indicate that ultrasound imaging of magneto-motive excitation is a candidate imaging modality for identifying tissue-based macrophages containing SPIO nanoparticles. MM-US may provide several advantages for diagnosis and therapy of various diseases. The content of this chapter are taken from “Detection of magnetic nanoparticles in tissue using magneto-motive ultrasound”, Nanotechnology 17 (2006), 41834190. Chapter 6 describes capability of differential phase optical coherence tomography (DP-OCT) to detect quantitatively macrophages in atherosclerotic lesions that have taken up monocrystalline iron oxide nanoparticles (MION). Histological analysis with Prussian blue stain for iron and RAM-11 for macrophage identification was used to confirm the presence of iron in macrophages in DP-OCT magneto-mechanic positive aortic regions. Molecular imaging of tissue-based macrophages with DP-OCT is feasible by magnetomechanical detection of iron nanoparticles. Coupling this technique with cardiac catheterization is a candidate method for detection of macrophage laden vulnerable plaques in patients. A portion of this chapter was submitted to The Proceedings of the National Academy of Sciences USA in September 2006, entitled “Magneto-mechanically detection of atherosclerotic macrophages with optical coherence tomography”
3
Chapter 7 introduces a novel contrast mechanism for imaging blood flow by use of magneto-motive optical Doppler tomography (MM-ODT), which combines an externally applied temporally oscillating high-strength magnetic field with ODT to detect erythrocyte movement. Hemoglobin contrast was demonstrated in a capillary tube filled with moving blood by imaging the Doppler frequency shift, which was observed independently of blood flow rate and direction. Results suggest that MM-ODT may be a promising technique to image blood flow and vessel mapping. Portions of this chapter was published in Optics Letters 31(6) 2006, 778-780, “Hemoglobin contrast in magneto-motive optical Doppler tomography” and was accepted by Nanotechnology, entitled “Imaging nanoparticle flow using magneto-motive optical Doppler tomography” in September 2006.
4
1.2
Vascular biology in atherosclerosis Atherosclerosis, characterized by the sequence of lipid core and fibrous
tissues in the artery walls, have been studied with growing interest in vascular biology [1]. High-risk atherosclerotic vulnerable plaque is a leading medical cause of death and illness in developed countries and will become a growing burden in coronary artery disease (CAD). Over the past decade, atherosclerosis was considered to progress chronically. However, more recently this symptom has been observed to progress rapidly such as acute coronary syndrome induced by an inflammation process, including monocyte infiltration, macrophage and lymphocytes (T-cell) activity [1, 2]. Macrophages are thought to participate in breaking and weakening the connective tissue matrix in the intima, which leads to plaque rupture [3]. Contributions of macrophages to weakening of atherosclerotic plaque are an area with much potential for an improvement in diagnostic and therapeutic methods aimed at reducing high-risk vulnerable plaque rupture.
5
1.3
Molecular imaging of atherosclerosis Molecular imaging of cardiovascular disease is an emerging area that aims
to develop both specific nanoparticle probes and detection techniques to identify high-risk vulnerable plaque. The main features for molecular imaging in atherosclerosis can be classified in Figure 1-1 [4]: 1) endothelial dysfunction, 2) inflammatory process including monocyte derived macrophage activation, 3) proteolytic enzymes such as matrix metalloproteinases (MMPs) that induce thinning fibrous cap in vulnerable plaque, and 4) angiogenesis. Table 1-1 illustrates the potential molecular targets for imaging of vulnerable plaque.
Table 1-1
Targeted for molecular imaging of atherosclerosis
Process
Targeted for Molecular Imaging
Ref
ICAM (Intercellular adhesion molecules) VCAM (Vascular cell adhesion molecules) P-selectin E-selectin Monocyte recruitment
[5] [6] [7-9] [10, 11] [12]
Macrophages scavenger receptor
[13-15]
MMPs
MMP-2, MMP-9
[16, 17]
Tissue Factor
Angiogenesis
[18, 19]
Endothelial Dysfunction
Inflammation
6
Figure 1-1
Progression of atherosclerosis and potential targets for imaging of high-risk vulnerable plaque. (adapted from [4])
7
1.
Libby, P., Vascular biology of atherosclerosis: overview and state of the art. Am J Cardiol, 2003. 91(3A): p. 3A-6A.
2.
Plutzky, J., The vascular biology of atherosclerosis. American Journal of Medicine, 2003. 115: p. 55-61.
3.
Ross, R., Distinguished vascular biology lecture - Atherosclerosis is an inflammatory disease. Circulation, 1998. 98(17): p. G-G.
4.
Choudhury, R.P., V. Fuster, and Z.A. Fayad, Molecular, cellular and functional imaging of atherothrombosis. Nat Rev Drug Discov, 2004. 3(11): p. 913-25.
5.
Weller, G.E., et al., Targeted ultrasound contrast agents: in vitro assessment of endothelial dysfunction and multi-targeting to ICAM-1 and sialyl Lewisx. Biotechnol Bioeng, 2005. 92(6): p. 780-8.
6.
Tsourkas, A., et al., In vivo imaging of activated endothelium using an anti-VCAM-1 magnetooptical probe. Bioconjug Chem, 2005. 16(3): p. 576-81.
7.
Marschang, P., et al., Reduction of soluble P-selectin by statins is inversely correlated with the progression of coronary artery disease. Int J Cardiol, 2006. 106(2): p. 183-90.
8.
Wang, K., et al., Platelet, not endothelial, P-selectin is required for neointimal formation after vascular injury. Arterioscler Thromb Vasc Biol, 2005. 25(8): p. 1584-9.
8
9.
Li, G., et al., Arterial macrophages and regenerating endothelial cells express P-selectin in atherosclerosis-prone apolipoprotein E-deficient mice. Am J Pathol, 2005. 167(6): p. 1511-8.
10.
Ley, K., The role of selectins in inflammation and disease. Trends Mol Med, 2003. 9(6): p. 263-8.
11.
Kang, H.W., et al., Magnetic resonance imaging of inducible E-selectin expression in human endothelial cell culture. Bioconjug Chem, 2002. 13(1): p. 122-7.
12.
Bobryshev, Y.V., Monocyte recruitment and foam cell formation in atherosclerosis. Micron, 2006. 37(3): p. 208-22.
13.
Chen, L.H. and Y.F. Guan, [Macrophage migration inhibitory factor and its role in atherosclerosis]. Sheng Li Ke Xue Jin Zhan, 2006. 37(1): p. 457.
14.
Choudhury, R.P., J.M. Lee, and D.R. Greaves, Mechanisms of disease: macrophage-derived foam cells emerging as therapeutic targets in atherosclerosis. Nat Clin Pract Cardiovasc Med, 2005. 2(6): p. 309-15.
15.
Boyle, J.J., Macrophage activation in atherosclerosis: pathogenesis and pharmacology of plaque rupture. Curr Vasc Pharmacol, 2005. 3(1): p. 638.
16.
Loftus, I.M., et al., Increased matrix metalloproteinase-9 activity in unstable carotid plaques. A potential role in acute plaque disruption. Stroke, 2000. 31(1): p. 40-7.
9
17.
Libby, P., P.M. Ridker, and A. Maseri, Inflammation and atherosclerosis. Circulation, 2002. 105(9): p. 1135-43.
18.
Couffinhal, T., et al., Mouse model of angiogenesis. Am J Pathol, 1998. 152(6): p. 1667-79.
19.
Lewin, M., et al., In vivo assessment of vascular endothelial growth factor-induced angiogenesis. Int J Cancer, 1999. 83(6): p. 798-802.
10
Chapter 2 Theoretical development of magnetic force and induced motion in elastic media 2.1
Magnetic nanoparticles Magnetic nanoparticles have been studied intensively over the past decade
as a contrast agents for magnetic resonance imaging [1]. More recently, use of magnetic nanoparticle probes have been expanded to many novel biomedical applications, such as reagents for cell labeling and cell tracking [2], drug delivery [3], cell separation [4], and treatment of cancer cells [5] [6]. Table 2-1 shows commercial magnetic nanoparticles classified by their overall size and surface coating. Magnetic nanoparticles can be divided into three categories; 1) standard superparamagnetic iron oxide (SPIO) ranging from 60150 nm; 2) ultrasmall SPIO (USPIO) ranging from 10-40 nm; 3) monocrystalline iron oxide (MION-a subset of USPIO) ranging from 10-30 nm [7]. Table 2-2 illustrates properties and applications of magnetic nanoparticles including SPIO, USPIO and MION. Figure 2-1 is an illustration that summarizes analysis presented in this chapter and explains the theoretical development of magnetic force and induced motion of magnetic nanoparticles and derivations of the tissue-surface displacement equation from Mindlin’s elastic theory in a semi-infinite model.
11
Table 2-1 Agent
Classification of SPIO nanoparticles [5, 7, 8] Class
Trade and common names
Status
AMI-121
Oral SPIO
Lumirem, Gastromark, Ferumoxsil
Approved > 300 nm
OMP
Oral SPIO
Abdoscan
Approved 3.5 μm
AMI-25
SPIO
Feridex, Endorem, Ferumoxide
Approved 80~150 nm
SHU555A
SPIO
Resovist
Phase III
62 nm
AMI-227
USPIO
Sinerem, Combidex, Ferumoxtran
Phase III
20~40 nm
NC100150
USPIO
Clariscan
Phase II
20 nm
CODE 7228
USPIO
Advanced Magnetics
Phase II
18~20 nm
1
Mean size
MION-46
MION
MION46 (manufactured by CMIR )
-
20~25 nm
MION-47
MION
MION47 (manufactured by CMIR)
-
27.5
MION-48
MION
MION48 (manufactured by CMIR)
-
20~25 nm
Table 2-2 Agent
Properties and applications of SPIO nanoparticles [8] Class Target Organs Dose
Ref
AMI-121
Oral SPIO
GI lumen
1.5~3.9 mmol/Fe
[9]
OMP
Oral SPIO
GI lumen
0.5 g/l 400-600 ml
[10]
AMI-25
SPIO
Liver / Spleen
15 μmol Fe/kg
[11]
SHU555A
SPIO
Liver / Spleen
8 μmol Fe/kg
[11-13]
Perfusion
4~16 μmol Fe/kg
MRA
10 μmol Fe/kg
Lympnodes
30~45 μmol Fe/kg
MRA
14~30 μmol Fe/kg
[14-17]
Perfusion
7 μmol Fe/kg
[18]
MRA
50~100 μmol Fe/kg
[19]
AMI-227
NC100150
MION
USPIO
USPIO
MION
Liver
[2, 5, 20, 21]
Atherosclerosis
1
nm
Center for Molecular Imaging Research, Massachusetts General Hospital, Harvard University.
12
Magnetic Field on Nanoparticle (SPIO, MION) (Table 2-3)
Magnetic Force on Nanoparticle (SPIO, MION): (Figure 2-3) F = −∇U = ∇ (
χ sV 2u0
2
B ) = χ sV ∇ (
B
)
Motion of Nanoparticle (SPIO, MION): (Figure 2-4) ∂ 2 znp (t ) ∂t 2
+γ
∂znp (t ) ∂t
Motion of Nanoparticles using Laplace Transform s 2 Z np ( s ) +
2
2u0
Transient Motion of Nanoparticle (Figure 2-5)
+ ω0 2 znp (t ) = a[1 − cos(ω B t )]
r k a as sZ np ( s ) + Z np ( s ) = − 2 m m s ( s + ωB 2 )
Steady State Motion of Nanoparticle (Figure 2-5) Tissue Surface Displacement in Elastic Media Using Galerkin Vector ⎡ ⎤ ⎧ 3 − 4v 8v 2 − 12v + 5 ( z − c) 2 (3 − 4v)( z + c) 2 − 2cz 6cz ( z + c) 2 ⎫ P W =⎢ + + + ⎬ ⎥⎨ R + π 16 G (1 v ) R2 R13 R23 R25 − ⎣ ⎦⎩ 1 ⎭
Tissue Surface Displacement in Elastic Media (Figure 2-7)
⎧ 3 − 4v 8v 2 − 12v + 5 ( z − c)2 + + ⎪ m z np R2 R 13 ⎡ ⎤ ⎪ R1 W = ⎢ ⎥⎨ 2 2 ⎣ 1 6 π G (1 − v ) ⎦ ⎪ + ( 3 − 4 v )( z + c ) − 2 c z + 6 c z ( z + c ) 3 5 ⎪ R2 R2 ⎩
Figure 2-1
⎫ ⎪ ⎪ ⎬ ⎪ ⎪ ⎭
Outline of theoretical model of magnetic force acting on magnetic nanoparticles in elastic media.
13
2.1.1
Magnetic field effect on magnetic nanoparticles To evaluate force acting on magnetic nanoparticles, magnetic energy [22],
U, is
1 U = − m•B 2
(2.1)
If a magnetic material is exposed to an external magnetic flux density, B, individual nanoparticles have an overall response determined by the magnetic moment, m and viscoelastic properties of the surrounding material, including tissue and cells. The magnetic flux density on magnetic nanoparticles may be written: B = μ0 ( H + M ) ,
(2.2)
where μ0 (4π × 10−7 H/m) is permeability of free space (SI unit: 4π ×10−7 N/A2), M is the magnetic moment per unit volume and H is magnetic field strength. The
magnetic moment, m, within volume, V is given by m=MV. Magnetization of magnetic particles can be classified in terms of the standard relation, M = χH. Magnetic susceptibility is proportional to the number of magnetic particle atoms in tissue and the square of the magnetic moment. In practice, magnetization (M) is not linearly proportional to magnetic field strength (H) after saturation of the magnetic field (usually over 2-3 Tesla). This nonlinear relationship between induced magnetization on paramagnetic material and applied magnetic field strength is represented by the Langevin function [23, 24]:
14
⎡ ⎛ μ mH ⎞ ⎛ kT ⎞ ⎤ M (H ) = Nm ⎢coth ⎜ 0 ⎟⎥ ⎟−⎜ kT ⎝ ⎠ ⎝ μ0 mH ⎠ ⎦ ⎣ 5 ⎡ 1 μ0 mH 1 ⎛ μ0 mH ⎞3 ⎤ 2 ⎛ μ0 mH ⎞ ≅ Nm ⎢ − ⎜ ⎟ + ⎜ ⎟ + …⎥ 45 ⎝ kT ⎠ 945 ⎝ kT ⎠ ⎣⎢ 3 kT ⎦⎥
Where
≅
⎤ Nm μ0 H ⎡ 1 ⎛ μ0 mH ⎞ 2 ⎛ μ0 mH ⎞ ⎢1 − ⎜ ⎟ + ⎜ ⎟ + …⎥ 3kT ⎢⎣ 15 ⎝ kT ⎠ 315 ⎝ kT ⎠ ⎥⎦
≅
Nm 2 μ0 H 3kT
2
2
(2.3)
4
Langevin function 2 ( L( x) = coth( x) − 1/ x ) N = the number of atoms per unit volume
m = the magnetic moment per atom (4.47 x 10-8 erg/G) k = Boltzmann’s constant ( 1.3807 × 10−16 (erg K −1 ) = 1.3807 ×10−23 (J K −1 ) )
μ0 = Permeability of free space (4π x 10-7) T = Temperature (300 K) BM = Bohr magneton3
Once the constants, m, k, μ0, and T have been determined, total number of Fe atoms (N= 1.4076 x 109) is calculated by Langevin nonlinear fitting (Figure 22) of MION magnetization data recorded by Weissleder et al., [25]. Langevin
function is clearly represented nonlinear magnetization curve relationship between magnetization versus magnetic field strength for MION nanoparticles
1 1 1 2 5 + x − x3 + x … 45 945 x 3
2
coth( x ) ≅
3
Physical constant of magnetic moment = 9.27 x 10-24 A m2= 9.27 x 10-24 J/T= 9.27 x 10-21 erg/G
15
entire magnetic field range (0-5 Tesla) in Figure 2-2 (a). At low field (0-1 Tesla), magnetization curve for MION nanoparticles is proportional to magnetic field strength from fitting data (Figure 2-2 (b)).
(a) Figure 2-2
(b)
Magnetization as a function of magnetization versus magnetic field
for MION nanoparticles at room temperature. The solid line represents fitting data using Langevin nonlinear function at magnetic field (0-5 Tesla) (a), and magnetic field (0-1 Tesla) (b). [25] After magnetic field strength (H) reaches a value of 1.5 Tesla, the magnetization increased very slowly and saturated when H is near or over 2 Tesla. In clinical MRI, detectable sensitivity of iron nanoparticles was reported at 50 nmol Fe/g tissue (corresponding to 1013-14 iron oxide nanoparticles/g tissue or 510 μmol Fe/kg I.V.) [20]. In preliminary experiments, MION was used to demonstrate cellular uptake of nanoparticles by macrophages (1 mg Fe/106 cells)
16
with 1.5 x 106 MION particles/cell [26]. Table 2.2 shows magnetic susceptibility of SPIO and MION nanoparticles with CGS units [27]. Magnetic susceptibility of SPIO and MION SPIO
Table 2-3
CGS UNIT (Dimensionless) 0.89 x 10-2
CGS UNIT (Dimensionless) 1.58 x 10-2
χ ρ
cm3 /g 7.16 x 10-3
cm3 /g 2 x 10-3
χWiron ρ
cm3/mol Fe
cm3/mol
0.4 ± 0.02
0.112±0.008
χ
χg = χM =
MION
Volume susceptibility χ , Mass susceptibility χ g , Molar susceptibility χ M
Magnetization of magnetic particles can be classified in terms of the standard relation, M = χH. Therefore, induced magnetic moment m becomes: m = MV = χVH = χVB / μ0
(2.4)
B = μ0 ( H + χ H ) = μ 0 μ R H = μ H ,
(2.5)
where μ R is defined as relative permeability giving a simple relationship (equation (2.5) ) between B and H ( B = μ H ). Susceptibility of the magnetic nanoparticles, χ, is dimensionless and given by magnetic dipole density for each paramagnetic material and is essential for characterizing magnetic properties of magnetic nanoparticles. From equation (2.1), magnetic energy, U, of a SPIO nanoparticle in an external magnetic field is given by:
17
χV 2 1 U = − m•B = − s B 2 2u0
(2.6)
Magnetic force acting on SPIO nanoparticles becomes4:
χ sV
2
B 1 ) = χ sV ∇( B ⋅ H ) F = −∇U = ∇( B ) = χ sV ∇( 2u0 2u0 2 Where
2
(2.7)
1 B ⋅ H is the magnetic static field energy density [28]. We assume in our 2
analysis a sinusoidal magnetic flux density is principally along z-direction. Hence, →
we write B ( x , y , z ; t ) = sin (2 π f n t ) B z ( z ) k and the magnetic force Fm acting on nanoparticles as, Fm =
χ sVs ∂B [1 − cos(4π f nt )]B z ( z ) z , 2μ0 ∂z
(2.8)
where fn is the modulation frequency of the applied sinusoidal magnetic field. Magnetic force on a single nanoparticle can be calculated by equation (2.7) and magnetic susceptibility data from Table 2.2. Mass density of iron,
ρ spio = 5.18(
g g ) and molar mass of iron, MWSPIO = 231.55( ) were used to 3 mol cm
calculate magnetic force on each nanoparticle. Magnetization of MION (2.8 nm ± 0.9 ~ 4.6 nm ± 1.2) [25] and SPIO nanoparticles was 38.9 emu/g iron at 2 Tesla and 63.7 emu/g iron at 1.5 Tesla [29] was reported. To calculate magnetic force acting on magnetic nanoparticle, mean molecular weight of SPIO (2000 kDa) and 4
∇(B ⋅ B) = 2B × (∇ × B) + 2(B ⋅∇)B = 2(B ⋅∇)B
18
MION (38.9 kDa5) was used. Figure 2.3 shows maximum magnetic force acting on SPIO (2.6283 x 10-15 (N)) and MION (2.263 x 10-17 (N)) nanoparticles, respectively.
Figure 2-3
Magnetic force acting on SPIO and MION nanoparticles.
2.2.
Motion of magnetic nanoparticle dynamics
2.2.1
Motion of magnetic nanoparticle dynamics; steady state
The total force acting on a nanoparticle in the z-direction is written
∑ Fz = m 5
∂z ∂ 2 z (t ) = Fm − kznp (t ) − r np , 2 ∂t ∂t
Dalton= 1/Na (Na is the Avogadro’s number: 6.0221415×1023 atoms/mole) ≈ (1.66053886 × 10−24 kg).
19
(2.9)
where kznp(t) is an elastic restoring force, and r
∂ z np ∂t
is a drag force that accounts
for the viscous properties of the local tissue environment. The negative sign of viscous drag and restoring forces indicates that these forces are in opposite direction to nanoparticle movement, znp(t). We can write second-order differential equations of motion by dividing by the mass, m, ∂ 2 znp (t ) ∂t
2
+
∂B ( z ) r ∂znp kznp (t ) χV + = [1 − cos(4π f n t )]B z ( z ) z . m ∂t m 2mμ 0 ∂z
(2.10)
Equation (2.10) can be approximated using the first terms in the Maclarin series for the magnetic field and its gradient, ∂ 2 znp (t ) ∂t Letting a =
2
+
∂B (0) r ∂znp kznp (t ) χV + ≅ [1 − cos(4π f n t )]B z (0) z . m ∂t m 2mμ 0 ∂z
(2.11)
χ sVs ∂B (0) B z (0) z , ωB = 4π f n , k / m = ω0 2 , and r / m = γ , the second 2mμ 0 ∂z
order differential equation (2.11) may be written ∂ 2 znp (t ) ∂t
2
+γ
∂znp (t ) ∂t
+ ω0 2 znp (t ) = a[1 − cos(ωB t )] .
(2.12)
To analyze steady state motion, the phase znp (t ) = z0, ss eiωBt is introduced to obtain time-dependent oscillating displacement of nanoparticles. z0,ss is displacement amplitude of magnetic nanoparticles in the steady state, and induced displacement of nanoparticles may be written
20
∂ 2 z0, ss ei (iωB ) t ∂t 2
+γ
∂z0, ss ei (ωB ) t ∂t
+ ω0 2 z0, ss ei (iωB ) t = − aei ( iωB )t
(2.13)
Thus, equation (2.13) becomes
⎡⎣ (iωB ) 2 + γ (iωB ) + ω02 ⎤⎦ z0, ss = − a znp (t ) = z0, ss e
iωB t
−aeiωBt = 2 ⎡⎣ωB + iγωB + ω02 ⎤⎦
(2.14) (2.15)
From equation (2.15), znp (t ) represents nanoparticle movement in steady state and corresponding movement of nanoparticle at 2 Tesla, 1 Hz magnetic field is shown in Figure 2-4.
Figure 2-4
Simulated results SPIO nanoparticles motion with a 1 Hz, 2 Tesla
magnetic force applied to SPIO nanoparticles.
21
2.2.2
Motion of magnetic nanoparticle dynamics; transient and steady state
To analyze transient and steady state nanoparticle displacement, the Laplace transform may be used to solve the second-order differential equation(2.12). We assume zero initial displacement and velocity to find; s 2 Z np ( s ) +
r k a as sZ np ( s ) + Z np ( s ) = − 2 m m s ( s + ωB 2 )
a as (2.16) − 2 2 ⎛ ⎞ s ( s + ωB ) s 1 ⎟ Z np ( s ) = 2 = a⎜ 2 − 2 2 2 ( s + γ s + ω0 ) ⎜⎝ ( s + γ s + ω0 ) s ( s + γ s + ω02 ) (s 2 + ωB 2 ) ⎟⎠ If 4ω0 2 − γ 2 > 0 , we can write nanoparticle movement (znp(t)) by computing the sum of transforms. ⎡ −γωBω0 2 sin(ωB t ) ⎤ ⎥ ⎢ 2 2 2 2 4 4 ⎥ ⎢ + (γ ωB − 2ωB ω0 + ωB + ω0 ) ⎥ ⎢ −ω 4 cos(ω t ) + (ω 2ω 2 ) cos(ω t ) + B B B 0 ⎥ ⎢ 0 1 ⎢ ⎛ ⎞⎥ 1 2 2 2 2 2 2 2 a⎢ ⎜ −ωB (γ + ωB − ω0 ) cos( t (4ω0 − γ ) ) − ⎟ ⎥ 2 ⎢ ⎜ ⎟⎥ 1 ⎥ ⎢exp(− 1 γ t ) ⎜ 2 1 2 2 2 2 2 2 ⎟ ω γ ( 3 ω ω γ ) sin( t (4 ω γ ) ) − + + − ⎢ 2 ⎜ B B ⎟⎥ 0 0 2 ⎢ ⎜ ⎟⎥ 1 ⎢ 2 2 ⎜ ⎟⎥ (4ω0 − γ ) 2 ⎝ ⎠⎦ ⎣ (2.17) znp (t ) = (ω0 2 (γ 2ωB 2 − 2ωB 2ω0 2 + ωB 4 + ω0 4 ))
We find the time-dependent displacement (znp(t)) of nanoparticles by using an inverse Laplace transform; the solution includes transient and steady state terms. The initial motion of magnetic nanoparticles is driven by a constant
22
magnetic force and displays a damped transient motion before steady state motion dominates at twice the modulation frequency of the applied sinusoidal magnetic field. Motion of the nanoparticles at double the modulation frequency originates from the magnetic force being proportional to the product of magnetic flux density and the gradient (equation(2.8)).
Figure 2-5
Simulation results nanoparticle displacement driven by an external
magnetic field; (a) external magnetic flux density, (b) transient, and (c) steady state movement
Figure 2-5 is a simulation result of nanoparticle displacement driven by an external magnetic field (a), giving transient (b), and steady state (c) motions.
23
Frequency response is given by fT = (4ω0 2 − γ 2 )1/ 2 and the selected values are larger than that of the steady state motion. Larger displacements at initial times are due to a transient effect; steady-state displacements are seen to be twice frequency of the externally applied magnetic field. To understand how the magnetic force acts on paramagnetic materials and moves nanoparticles in the zdirection, it is important to understand that the square of the magnetic field gradient is proportional to the magnetic force. Therefore, movement of magnetic nanoparticles at a given distance is determined by the strength of the magnetic field.
2.3
Tissue surface displacement in an elastic media
The purpose of this section is to derive the force-displacement relationship using theory of elasticity for a nanoparticle embedded in the elastic half space. Force on the nanoparticle is applied normal to the boundary of a semi-infinite elastic media and solutions were obtained using Galerkin’s vector and Mindlin’s theory for a point force in the semi-infinite media [30]. Analysis of surface displacement of iron-laden tissue is required for quantitative analysis of the response of an elastic media to an externally applied magnetic force.
2.3.1
Galerkin’s vector for elasticity analysis [30]
The well known basic elastic equation is given by [31],
24
G (∇ 2 +
1 ∇div)ρ + K = 0 1 − 2v
(2.18)
Where K is body force, G is the modulus of rigidity (shear modulus), ρ is the displacement vector, and ν is Poisson’s ratio for the elastic media. The displacement using Westergaard’s form of the Galerkin vector, F, is given by 2Gρ = (c∇ 2 − ∇div)F ρ=
(c∇ 2 − ∇div)F 2G
(2.19) ,
F is a vector function that can be expressed as F = iX + jY + kZ , where i, j, k are
unit vectors in the x, y, z directions, respectively. The displacement equation with Galerkin vector components becomes; (∇2 +
1 ∇div)(c∇2 − ∇div)F + 2K = 0 1 − 2v
(2.20)
Equation (2.20) can be expressed as,
(c∇ 4 − ∇ 2∇div+
c 1 ∇div∇ 2 − ∇div∇div)F + 2K = 0 1 − 2v 1 − 2v
(2.21)
with ∇ 4 = ∇ 2∇div=∇div∇div . The reduced displacement equation (2.22) will be satisfied by the relation (−1+
c 1 − ) = 0 and becomes 1 − 2v 1 − 2v
c 1 ⎤ ⎡ 4 2 ⎢⎣ c∇ + ∇ ∇div(-1+ 1 − 2v − 1 − 2v ) ⎥⎦ F + 2K = 0
(2.22)
Therefore, the basic displacement equation (2.19) in elastic media using
c = 2(1 − v) can be expressed as follows,
25
2Gρ = ⎡⎣ 2(1 − v)∇ 2 − ∇div ⎤⎦ F , In equation (2.22), we may obtain 2(1 − v)∇ 4 F = −2K and ∇ 4 F = −
(2.23) K (1 − v) .
K is defined as the body force on elastic media, and this can be restated as 2G u = 2(1 − v)∇ 2 X − ∇divF = 2(1 − v)∇ 2 X − ∇∇ ⋅ F 2G v = 2(1 − v)∇ 2 Y − ∇divF = 2(1 − v)∇ 2 Y − ∇∇ ⋅ F
(2.24)
2G w = 2(1 − v)∇ Z − ∇divF = 2(1 − v)∇ Z − ∇∇ ⋅ F 2
2
Equation (2.24) also gives another representation,
2G divρ = div[2(1 − v)∇ 2 -∇div]F = [2(1 − v)∇ 2 div − ∇ 2 div]F
(2.25)
= (1 − 2v)∇ divF 2
2.3.2
Force at a point in a semi infinite elastic media
A vertical force, P, applied at a distance below the planar surface z = 0 in the elastic media is illustrated in Figure 2-6 [30].
26
Z
(0, 0, -c)
Plane z=0 X Y
R2 (0, 0, c)
P
z
R1
r (x, y, z)
Figure 2-6
Cylindrical coordinates for a semi-infinite elastic media. Vertical
force (P) is applied at point (0, 0, c) in the positive z-direction [30].
By combining a sequence of Galerkin vectors defining a nucleus of stress and strain [32] produces seven components z1,…z7., which are defined as
27
P P R1 , z2 = − R2 , 8π (1 − v) 8π (1 − v) ( z + c) Pc P , z4 = z3 = − R2 , 4π (1 − v ) R2 2π z1 =
(1 − 2v ) P [( z + c) log( R2 + z + c) − R2 ] , 2π (1 − 2v ) Pc z6 = − [log( R2 + z + c)] , 2π (1 − v) z5 =
(2.26)
1 Pc 2 , z7 = 4π (1 − v) R2 F = z1 + z2 + z3 + z4 + z5 + z6 + z7 .
If point source position, c, is approaches zero corresponding to a single force applied at the surface of the boundary, the solution becomes Boussineq’s equation [30], FB, using the Galerkin vector, F,
FB =
P [ 2vR + (1 − 2v) z log( R + z )] 2π
(2.27)
In equation (2.26), z1 component represents the well known Kevin’s single force solution in a elastic media with infinite extent, c → ∞ , and the corresponding Galerkin vecor, F, for Kelvin solution Fk become [30], Fk = k[
PR1 ] 8π (1 − v )
(2.28)
As a result, the solution for vertical displacement and normal to the boundary in elastic media obtained by combining seven nuclei of stress and strain (2.26) has the following expression:
28
⎧ R1 + ( 8v (1 − v ) − 1) R2 + ⎫ ⎡ Pk ⎤ ⎪ ⎪ F=⎢ 2cz ⎬ ⎨ ⎥ ⎣ 8π (1 − v ) ⎦ ⎪ 4(1 − 2v )[(1 − v ) z − vc ]log( R2 + z + c ) − R2 ⎪⎭ ⎩
(2.29)
Transforming to cylindrical coordinates from(2.24), the displacement will be confined to the z-direction and may be written, ∂2Z 1 1 2 W = ( )[2(1 − v)∇ Z − ∇divF ] = ( )[2(1 − v)ΔZ − 2 ] (2.30) ∂z 2G 2G
The displacement in an elastic media in cylindrical coordinates becomes, ⎡ 3 − 4v 8v 2 − 12v + 5 ( z − c) 2 ⎤ + ⎢ R + ⎥ 3 R2 R1 ⎡ ⎤⎢ 1 P ⎥ W =⎢ ⎥⎢ 2 2⎥ − 16 G (1 v ) π ⎣ ⎦ (3 − 4v)( z + c) − 2cz 6cz ( z + c) + ⎢+ ⎥ 3 R R25 2 ⎣ ⎦
(2.31)
In the deviation of displacement defined by (2.31), it is useful to analyze ironladen tissue surface displacement applied by magnetic force, which acts on superficial samples embedded in magnetic nanoparticles.
29
⎡ωB3 γ sin(ωB t )ω0 2 + cos(ωB t )ωB 2ω0 4 − cos(ωB t )ωB 4ω0 2 + ⎢ 1 ⎛ ⎞ 1 2 ⎢ 2 2 2 2 2 2 ω ( γ ω ω ) cosh( t ( γ 4 ω ) )− ⎟ − + − − ⎜ B 0 0 B ⎢ 2 ⎜ ⎟ ⎢1 2 1 1 ⎢ γ exp(− tγ ) ⎜ ω 2γ (−3ω 2 + ω 2 + γ 2 ) sinh( 1 t (γ 2 − 4ω 2 ) 2 ) ⎟ − 2 ⎜ B 0 0 B ⎟ ⎢4 2 ⎜ ⎟ 1 ⎢ 2 2 2 ⎜ ⎟ ⎢ (γ − 4ω0 ) ⎝ ⎠ ⎢ 1 1 a⎢ 1 1 2 2 1 2 2 2 2 2 2 2 2 γ exp( t γ )( ω ( γ ω ω t γ − ω γ − ω ) sinh( ( 4 ) )( 4 ) − − + − 0 0 0 B B ⎢ 2 2 2 ⎢ 1 1 2 ⎢1 2 2 2 2 2 2 ⎢ 2 ωB γ (−3ω0 + ωB + γ ) cosh( 2 t (γ − 4ω0 ) ) + ⎢ 1 1 1 2 2 1 2 ⎢ 2 2 2 2 t γ ω γ ω ω t γ ω − − + − − exp( )( ( ) cosh( ( 4 ) )(γ 2 − 4ω0 2 ) − 0 0 B B ⎢ 2 4 2 ⎢ 1 1 ⎢ 1 ω 2γ (−3ω 2 + ω 2 + γ 2 ) sinh( 1 t (γ 2 − 4ω 2 ) 2 )(γ 2 − 4ω 2 ) 2 0 0 0 B ⎢ B 2 znp (t ) = ⎣ 4 (ω0 2 (γ 2ωB 2 − 2ωB 2ω0 2 + ωB 4 + ω0 4 )) (2.32)
⎤ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ −⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥⎦
Finally, tissue surface displacement (zs(t)) due to nanoparticles embedded in an elastic media is obtained by combining F = ma = mznp with (2.17) and (2.32); ⎡ 3 − 4v 8v 2 − 12v + 5 ( z − c) 2 ⎤ + + ⎢ ⎥ 3 mznp R2 R1 ⎡ ⎤ ⎢ R1 ⎥ (2.33) zs (t ) = ⎢ ⎥⎢ 2 2⎥ − 16 G (1 v ) π ⎣ ⎦ + (3 − 4v)( z + c) − 2cz + 6cz ( z + c) ⎢ ⎥ R23 R25 ⎣ ⎦
Figure 2-7 shows the simulation result of tissue surface displacement in ironladen elastic media using equation (2.33) with 2 Hz input magnetic field (1 Tesla) for the case of force normal to the boundary (c= 0.5 mm, ν= 0.4, and G=100)
30
OFF
Figure 2-7
ON
Simulation result of iron-laden tissue surface displacement due to
nanoparticle movement.
In summary, magneto-motive tissue surface displacement by an externally applied magnetic field consists of two motions; transient with the initiation of the magnetic force, and steady state. After the transient response, physical displacement approaches a steady state response, which resembles the input sinusoidal signal. Analysis of surface displacement of iron-laden tissue is important to analyze quantitatively tissue response in elastic media including tissue and cell as externally applied magnetic force.
31
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Pouliquen, D., et al., Investigation of the Magnetic-Properties of IronOxide Nanoparticles Used as Contrast Agent for Mri. Magnetic Resonance in Medicine, 1992. 24(1): p. 75-84.
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Frank, J.A., et al., Clinically applicable labeling of mammalian and stem cells by combining superparamagnetic iron oxides and transfection agents. Radiology, 2003. 228(2): p. 480-7.
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Wang, Y.X., S.M. Hussain, and G.P. Krestin, Superparamagnetic iron oxide contrast agents: physicochemical characteristics and applications in MR imaging. Eur Radiol, 2001. 11(11): p. 2319-31.
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Mayo-Smith, W.W., et al., MR contrast material for vascular enhancement: value of superparamagnetic iron oxide. AJR Am J Roentgenol, 1996. 166(1): p. 73-7.
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Simonsen, C.Z., et al., CBF and CBV measurements by USPIO bolus tracking: reproducibility and comparison with Gd-based values. J Magn Reson Imaging, 1999. 9(2): p. 342-7.
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Guimaraes, R., et al., MR lymphography with superparamagnetic iron nanoparticles in rats: pathologic basis for contrast enhancement. AJR Am J Roentgenol, 1994. 162(1): p. 201-7.
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Schenck, J.F., Safety of strong, static magnetic fields. Journal of Magnetic Resonance Imaging, 2000. 12(1): p. 2-19.
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Bulte, J.W., et al., Relaxometry and magnetometry of the MR contrast agent MION-46L. Magn Reson Med, 1999. 42(2): p. 379-84.
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Kellar, K.E., et al., NC100150 Injection, a preparation of optimized iron oxide nanoparticles for positive-contrast MR angiography. J Magn Reson Imaging, 2000. 11(5): p. 488-94.
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Weissleder, R., et al., Antimyosin-labeled monocrystalline iron oxide allows detection of myocardial infarct: MR antibody imaging. Radiology, 1992. 182(2): p. 381-5.
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Moore, A., R. Weissleder, and A. Bogdanov, Jr., Uptake of dextran-coated monocrystalline iron oxides in tumor cells and macrophages. J Magn Reson Imaging, 1997. 7(6): p. 1140-5.
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36
Chapter 3 Detection of atherosclerotic vulnerable plaque using optical coherence tomography 6 3.1
Introduction Atherosclerotic lesions, characterized by the accumulation of a lipid
necrotic core and fibrous components in the artery walls, have been studied extensively with the growth of vascular biology [1, 2]. Atherosclerotic vulnerable plaque is the leading cause of acute coronary artery disease and sudden death in western societies [3, 4]. Several imaging modalities such as high frequency intravascular ultrasound (IVUS) and elastography [5], multi-sliced computerized tomography [4], and magnetic resonance imaging [6] are being used to identify features of vulnerable plaque for early diagnosis of lesions. Unfortunately, these imaging modalities have limitations of low resolution and inability to detect thinning of the fibrous cap, or identify the lipid core at an early stage of vulnerable plaque. For example, intravascular ultrasound (IVUS) may be useful in detecting advanced or complicated lesions progression slowly, but in a vulnerable plaque lesion, discrimination of the atheroma from the arterial wall may not be possible limited imaging resolution.
6
Portions of this chapter have been published in Journal of Catheterization and Cardiovascular Interventions Volume 67, issues 6, pp.915-923. Title: Detection of Vulnerable Plaque in a Murine Model of Atherosclerosis with Optical Coherence Tomography.
37
Optical coherence tomography (OCT) is a recently developed and rapidly emerging imaging technology with considerable potential for many biomedical applications requiring higher resolution (< 10 μm) [7]. Purpose of this chapter is to establish the criteria in OCT images for identification of vulnerable plaque in the apoE-/- murine model. Specifically, we determine the fibrous cap thickness, lipid core size, and percent lipid content of plaque from OCT and histology images.
3.2
Animal model and experiment setup The experimental protocol was approved by the Institutional Animal Care
and Use Committee at the University of Texas at Austin and conformed to “Guidelines for the Care and Use of Laboratory Animals” (NIH publication No. 86-23) and “Principals of Laboratory Animal Care” (published by the National Society for Medical Research). The apoE-/- knockout murine model of atherosclerosis is well established and mimics many features of human coronary plaque progression [8, 9]. These gene altered mice contain the entire spectrum of lesions observed during the progression of human atherosclerosis. The apoE-/- mouse is the only animal model that develops spontaneous plaque rupture and thus for some studies may be a superior model than a larger mammal. C57BL/6J strain male and female apoE-/-
38
mice were obtained (Jackson Laboratory, Bar Harbor, ME, USA) as retired breeders (ApoE tm1Unc). We performed the experiments on a total of 19 apoE-/- mice (n= 7 for in vivo and n= 12 for ex vivo experiments) between ages 5 to 9 months that were fed a standard rodent chow diet. The OCT instrument utilized a mode-locked Ti:Al2O3 laser source operating at λ0 = 830 nm with FWHM = 55 nm. Light injected into a Michelson interferometer was linearly polarized at 45º and divided into reference and sample paths with a non-polarizing 50/50 beam splitter [10, 11]. A mirror mounted to a loudspeaker diaphragm in the reference path varied optical path-length in the longitudinal direction with a 15 Hz sinusoid. Figure 3-1 shows schematic diagram of OCT image setup.
39
Figure 3-1 Experimental setup for imaging mouse artery using optical coherence tomography (OCT). 3.3
Results Figure 3-2 shows an example of the analysis technique of an ex vivo OCT
image (a), and histology image (b). Two lipid areas were measured, five measurement locations of the fibrous cap thickness (F1-F5), and vessel area analyzed was defined by the visualizing OCT area. In this example, the thinnest
40
fibrous cap thickness was 21 μm by OCT and 11 μm by histology, the largest lipid core was 43,267 μm2 by OCT and 21,952 μm2 by histology, and percentage of the plaque composed of lipid was 21.4 % by OCT and 19.7 % by histology.
(a)
(b)
Figure 3-2
Comparison of vulnerable plaque by optical coherence tomography
and histology: histology (a) and OCT image (b).
Figure 3-3 b shows an example of a raw OCT image without overlay of the measurement tool. The measurement tool for the histology is shown below. The mean fibrous cap thickness was 96 μm by OCT and 47 μm by histology, the lipid core size was 10,849 μm2 by OCT and 5,393 μm2 by histology, and the percentage of plaque composed of lipid was 23.8 % by OCT and 25.6 % by histology.
41
(a)
(b) (b)
Figure 3-3
Comparison of stable plaque by optical coherence tomography and
histology: histology (a) and OCT image (b).
Figure 3-4 shows full reconstructions containing 67 cross-sectional images along a 1mm length of murine innominate artery (only six evenly spaced histology and OCT images are shown) using Amira 3D software. A large lipid core of 70,522 μm2 as measured by OCT is protected by a thick fibrous cap of 84 μm measured by OCT. Identification of vulnerable features of an atherosclerotic plaque has importance for better risk stratification of patients.
42
Figure 3-4
Three-dimensional reconstruction of innominate arteries.
Table 3-1
Lipid core area measurement by OCT and histology (μm2) 7.
Specimens
Lipid core by OCT
Lipid core by histology
Mouse 1
7,417
3,383
Mouse 2
30,780
16,222
Mouse 3
15,390
7,708
Mouse 4
70,521
37,772
Mouse 5
43,267
28,148
Mouse 6
15,853
7,646
Lipid core size and percent lipid content were measured in matching OCT and histology images (n = 6). The results are shown in table 3-1. The lipid cores
7
Corresponding measurements demonstrate a consistent shrinkage of histology compared to OCT
43
ranged in size from 7,417 to 70,521 μm2 by OCT and 3,383 to 37,772 μm2 by histology. One of the major limitations of IVUS is an inability to image structures that lie behind calcium. Unlike ultrasound, OCT can penetrate calcified structures. During in vivo studies, OCT B-scan images demonstrated that the brightest light reflection occurred in arteries with calcium hydroxy-apatite and cholesterol esters mixed together. This result was anticipated because calcium mixed with lipid has a large index of refraction gradient, and therefore would appear as bright features in the OCT B-scan images. The pixel brightness of calcium mixed with lipid, fibrous tissue, and pure lipid all differed and were 177 ± 15, 69 ± 6, and 32 ± 7 gray scale arbitrary units, respectively (one-way-ANOVA, p < 0.001). An example of the bright features in OCT B-scans and the corresponding histological images are shown in Figure 3-5. Von Kossa stain was used to confirm that the bright speckles (Figure 3-5 (a)) and bright linear regions (Figure 3-5 (b)) correspond to areas of calcium hydroxy-apatite.
44
Figure 3-5
Calcification of plaque. The upper panel is the Von Kossa stain
demonstrating the presence of calcium in atherosclerotic plaque by the speckled black staining. The lower panel is the corresponding OCT image showing only a portion of the plaque which contains the speckled calcium.
45
3.4
Discussion and Conclusions The identification of vulnerable features of an atherosclerotic plaque has
critical importance for better risk stratification of patients. Results of this study illustrate that OCT has the ability to measure the fibrous cap thickness, size of the lipid core beneath the cap, and percent lipid content of the plaque. The unique capability of OCT to characterize plaque features associated with vulnerability holds promise for identification of vulnerable plaque in patients as this imaging technology is moved to the cardiac catheterization laboratory. However, use of conventional OCT may be difficult to image macrophages, which are another important feature of inflammatory disease at early stages. An early study to quantify macrophages in human cadavers was performed by Tearney et al. [12] using OCT. This result showed that the OCT technique was capable of detecting macrophages by registration between OCT and histology images with post processing. However, resolution of conventional OCT technique could not be used to provide a clear visualization of monocyte derived macrophage density in the plaque wall and evaluate macrophage content. In chapter 6, magneto-motive OCT (MM-OCT) using nanoparticles is presented and may be a candidate technique for detection of macrophages in atherosclerotic vulnerable plaque caused by an inflammatory process.
46
Acronyms (Chapter 3) OCT
Optical coherence tomography
Apo E-/-
Apolipoprotein E knockout mouse
IVUS
Intravascular ultrasound
MRI
Magnetic resonance imaging
H&E
Hematoxlysin and eosin staining
IR
Index of refraction
FWHM
Full width half maximum
47
Table 3-2
Preparation for histology slides (Artery) •
The vessel close to the scan site was indicated by the black square [A].
• A
After perfusing the blood vessels in site through the left ventricle with formalin, pour formalin into the neck wound and wait for 10 minutes to further fix the vessels.
B
•
Put this segment into a small glass vial filled with 10% formalin and fix for at least 24 hours. [B]
•
Trim the tissue to the length that will allow paraffin embedding placing the segment on
C
end cutting from the ends to the transverse planes indicated by the dotted lines in B to make the smaller 3 mm long segment to be D
submitted for histological processing [C]. •
The 3 mm segment will not bend over when being embedded on end in the paraffin filled embedding container. [D]
48
1.
Fuster, V., et al., Integration of vascular biology and magnetic resonance imaging in the understanding of atherothrombosis and acute coronary syndromes. J Thromb Haemost, 2003. 1(7): p. 1410-21.
2.
Alexander, R.W. and V.J. Dzau, Vascular biology - The past 50 years. Circulation, 2000. 102(20): p. 112-116.
3.
Naghavi, M., et al., From vulnerable plaque to vulnerable patient - A call for new definitions and risk assessment strategies: Part II. Circulation, 2003. 108(15): p. 1772-1778.
4.
Naghavi, M., et al., From vulnerable plaque to vulnerable patient - A call for new definitions and risk assessment strategies: Part I. Circulation, 2003. 108(14): p. 1664-1672.
5.
de Korte, C.L., et al., Characterization of plaque components and vulnerability with intravascular ultrasound elastography. Physics in Medicine and Biology, 2000. 45(6): p. 1465-1475.
6.
Kramer, C.M., et al., Magnetic resonance imaging identifies the fibrous cap in atherosclerotic abdominal aortic aneurysm. Circulation, 2004. 109(8): p. 1016-1021.
7.
Cilingiroglu, M., et al., Detection of vulnerable plaque in a murine model of atherosclerosis with optical coherence tomography. Catheterization and Cardiovascular Interventions, 2006. 67(6): p. 915-923.
49
8.
Zhang, S.H., et al., Spontaneous Hypercholesterolemia and Arterial Lesions in Mice Lacking Apolipoprotein-E. Science, 1992. 258(5081): p. 468-471.
9.
Nakashima, Y., et al., Apoe-Deficient Mice Develop Lesions of All Phases of Atherosclerosis Throughout the Arterial Tree. Arteriosclerosis and Thrombosis, 1994. 14(1): p. 133-140.
10.
Kemp, N.J., et al., High-sensitivity determination of birefringence in turbid media with enhanced polarization-sensitive optical coherence tomography. J Opt Soc Am A Opt Image Sci Vis, 2005. 22(3): p. 552-60.
11.
Kemp, N.J., et al., Form-biattenuance in fibrous tissues measured with polarization-sensitive optical coherence tomography (PS-OCT). Optics Express, 2005. 13(12): p. 4611-4628.
12.
Tearney, G.J., et al., Quantification of macrophage content in atherosclerotic plaques by optical coherence tomography. Circulation, 2003. 107(1): p. 113-119.
50
Chapter 4 Magneto-motive detection of magnetic nanoparticles in tissue using DP-OCT 4.1
Introduction Optical coherence tomography (OCT) [1] is a rapidly emerging imaging
modality demonstrating improved resolution (< 10µm) over competing techniques such as ultrasound, magnetic resonance imaging (MRI), and multi-sliced computed tomography (CT). Differential-phase optical coherence tomography (DP-OCT) is capable of high path length sensitivity and able to detect a 1 nm optical path length change (Δp) between discrete reflecting surfaces [2]. DP-OCT has been used to measure displacement of nanometer-scale changes corresponding to neuron activity [3], electro kinetic response of cartilage [4], photo-thermal response of tissue [5], and phase contrast imaging of cells [6]. Use of superparamagnetic iron oxide (SPIO) nanoparticles as a tissue specific contrast agent provides a variety of potential applications in biology and medicine. A common application of SPIO nanoparticles is as a liver-specific MRI contrast agent to detect macrophages and other phagocytic cells in the reticuloendothelial system (RES) [7]. Macrophages in cardiovascular disease are considered an important marker of vulnerable fibrous caps and a risk factor in subsequent inflammatory mediated plaque rupture [8]. Detection of macrophages may also have utility for diagnosis of early stage cancer due to phagocytosis of
51
malignant cells [9]. In the current study we hypothesized that tissue based macrophages could be detected by placing engulfed SPIO nanoparticles in motion with an externally applied oscillating magnetic field. Since the ensuing motion of SPIO nanoparticles was anticipated to be on the order of nanometers, we used DP-OCT to detect tissue surface displacement in response to an applied magnetic field. We tested this hypothesis in ApoE
-/-
mice since tissue based macrophages
in the liver, Kupffer cells, were found previously to take up SPIO nanoparticles in a robust fashion [7].
4.2
Materials and methods
4.2.1 Superparamagnetic iron oxide (SPIO) nanoparticles
Colloidal suspensions of SPIO nanoparticles are tissue-specific MRI contrast agents approved in 1996 by the United States Food and Drug Administration (FDA) for human use. SPIO nanoparticles are also known as Ferumoxides or AMI-25 and their trade name is Feridex I.V. (USA) and Endorem (EU) [10]. Mean core diameter of these particles is 20 nm and total aggregation diameter is about 100 nm [11]. SPIO nanoparticles consist of nonstoichiometric magnetite crystalline cores, iron, and a dextran T-10 coating that is used to prevent aggregation and provide stabilization in the liver. Following injection of SPIO nanoparticles into rats, 80% of injected nanoparticles accumulate in tissuebased macrophages (Kupffer cells) in the liver due to the relatively short blood
52
half life [7] compared to ultrasmall SPIO nanoparticles. Uptake of SPIO nanoparticles by macrophage cells is directly dependent on concentration of intravenous (IV) injection, blood half life, and core size [12].
4.2.2 Magnetic force on superparamagnetic iron oxide (SPIO) nanoparticles
To evaluate magnetic force on superparamagnetic (SPIO) nanoparticles, magnetic potential energy, U, can be used to calculate force due to application of an external magnetic flux density (B) [13]. 1 U = − m•B 2
(4.1)
If a magnetic material is exposed to an external magnetic flux density, B, individual nanoparticles have an overall response determined by the magnetic moment, m and viscoelastic properties of the surrounding material. The magnetic flux density on magnetic nanoparticles may be written: B = μ0 ( H + M )
(4.2)
where μ0 ( 4π × 10−7 H/m) is permeability of free space, M is the magnetic moment per unit volume and H is magnetic field strength. The magnetic moment, m, acting on magnetic volume, V is given by, m=MV. Magnetization of magnetic
particles in the linear range can be classified in terms of the standard relation, M = χH. Therefore, induced magnetic moment m becomes: m = MV = χ sVH = χ sVB / u0
53
(4.3)
In equation (4.3), susceptibility of the SPIO nanoparticles, χs is dimensionless in SI units and given by dipole density for each paramagnetic material and is an important parameter characterizing magnetic properties of SPIO nanoparticles. From equation (4.1), magnetic energy, U, of a SPIO nanoparticle in an external magnetic field is given by,
χV 2 1 U = − m•B = − s B . 2 2u0
(4.4)
Magnetic force acting on SPIO nanoparticles becomes:
χ sV
2
B F = −∇U = ∇( B ) = χ sV ∇( ). 2u0 2u0 2
(4.5)
We assume a sinusoidal magnetic flux density that is directed principally along →
the z-direction. Hence, we write B ( x , y , z ; t ) = sin(2 π f n t )B z ( z ) k and the
magnetic force Fm acting on nanoparticles, Fm =
χ sVs ∂B [1 − cos(4π f nt )]B z ( z ) z ∂z 2μ0
(4.6)
Where fn is the modulation frequency of the applied sinusoidal magnetic field. The total force acting on nanoparticles in the z-direction is written
∑ Fz = m
∂ 2 z (t ) ∂z = Fm − kznp (t ) − r 2 ∂t ∂t
Where kznp(t) is an elastic restoring force, and r
∂znp ∂t
(4.7)
is a drag force that accounts
for the viscos properties of the local tissue environment. The negative sign of
54
viscous drag and restoring forces indicates that these forces are in opposite direction to nanoparticle movement, znp(t). The initial motion of magnetic nanoparticles is driven by a constant magnetic force and displays a damped transient motion before steady state motion dominates at twice the modulation frequency of the applied sinusoidal magnetic field. Motion of the nanoparticles at double the modulation frequency originates from the magnetic force being proportional to the product of magnetic flux density and the gradient (equation (4-6)).
4.2.3 Magnetic field generator
Finite element method (FEM) was used to design the magnetic field generator and evaluate space-time magnetic flux density. Figure 4-1 illustrates a cross-sectional view of the magnetic field generator using a low profile solenoid with cylindrical coordinates (axial symmetry) and computed magnetic flux density (B). The magnetic field generator consists of a solenoid (Ledex 6EC, Saia-Burgess Inc., USA), a function generator (HP 33120A, Hewlett Packard Inc., USA), a current amplifier and a power supply. FEM calculations (Maxwell SV, Ansoft Inc., USA) and Teslameter (Magnetometer, AlphaLab Inc., USA) measurement indicated that maximum magnetic flux density at a distance of 1.5 mm from the tip of the iron core was approximately 2 Tesla. The FEM simulation demonstrated that an iron core positioned along the centerline of the solenoid
55
dramatically increased magnetic flux density at the target specimen. Magnetic field distributions from the FEM simulation showed the maximal and principal direction of the magnetic field strength was along the z-direction. The conical iron core provided focusing and substantially increased the magnetic field strength. Magnetic flux density at the sample with an iron core positioned in the solenoid was about ten times greater than that without a core (Figure 4-1 (a), arrows).
56
(a)
(b)
(c)
Figure 4-1
Computed magnetic flux density distributions surrounding the
magnetic field generator using finite element method (FEM) in the twodimensional axisymmetric R-Z plane. Magnetic field with (a) and without (b) iron core inside solenoid are shown in top panel and illustration of the magnetic field generator with an iron core in the center of the solenoid (c). Magnetic flux density with an iron core positioned in the solenoid was about ten times greater than that without a core.
57
4.2.4
Animal model and histology
Liver tissues from 12 week old ApoE-/- high fat fed mice were utilized in this study because they contain tissue based macrophages cells. All experimental procedures were performed in accordance with protocols approved by the University of Texas Institutional Animal Care and Use Committee. The mice were injected via the jugular vein with either Feridex I.V. (Ferumoxides injectable solutions; Berelex Laboratories, USA) for IV administration (1.0, 0.1, and 0.01 mmol Fe/kg body weight) or saline and sacrificed 2 days post intravenous injection. The mice were euthanized with a lethal dose of ketamine and xylazine. After euthanizing, abdominal incisions were made to remove the entire liver from the mouse. Physical thickness of the liver samples was fixed at 1 mm and 0.5 cm x 0.5 cm in lateral dimensions. After completion of DP-OCT measurements, the mouse livers were embedded in 10% formalin acid and processed for histology. 5 μm thick sections were cut and stained with Prussian blue to identify iron deposition in liver Kupffer cells. To verify SPIO uptake by macrophage cells from histology slides, Image Pro Plus (Mediacynernetics Inc., USA) software was used to measure the total area of liver and accumulated area of SPIO aggregation that is Prussian blue positive.
58
4.2.5 DP-OCT measurements
Figure 4-2 shows a schematic diagram of a fiber-based dual channel differential-phase optical coherence tomography (DP-OCT) system (a), and sample path configuration with magnetic field generator (b). Partially polarized light from an optical semiconductor amplifier (AFC Technologies, central wavelength λ0= 1.31 μm, FWHM = 60 nm, optical coherence length, lc = 22 μm) is polarized and coupled into fast and slow axes of a polarization-maintaining (PM) fiber. The magnetic field generator consists of a solenoid, signal generator and current amplifier. The dual-channel Michelson interferometer was used to measure differential phase between light backscattered from a glass reference surface and liver surface when applying a sinusoidal focused magnetic field. Detected fringe signals may be written, Ich1 ( z ) = 2 I 0 Rref Rsamp ( z ) {exp[−Δz / lc ]2 }{cos(2π f 0t + ϕch1 + ϕnoise )}
(4.8)
Ich 2 ( z ) = 2 I 0 Rref Rsamp ( z ) {exp[−Δz / lc ]2 }{cos(2π f 0t + ϕch 2 + ϕnoise )}
(4.9)
Where, I0 is a scale factor, lc is source coherence length, Rref and Rsamp is reflectivity from reference and sample, f0 is the modulation frequency of the phase modulator, ϕnoise is the phase noise in the interferometer due to environmental perturbation, and ϕch1 and ϕch2 are the phase of fringes in reference and sample paths.
59
(a) SAMPLE BEAM
BIREFRINGENT WEDGES MICROSCOPE OBJECTIVE CH1
GLASS
CH2
GLASS
LIVER
C O R E
SOLENOID
(b)
Figure 4-2
Schematic diagram of a differential phase optical coherence
tomography (DP-OCT) system combined with a magnetic field generator: (a) DPOCT system, (b) collinear configurations of the DP-OCT sample path and design of the magnetic field generator containing a conical iron core.
60
Optical path length change measured in this study corresponds to tissue surface displacement zs(t) in response to a high-strength magnetic field applied to iron-laden tissue and can be calculated from the differential phase (Δϕ) and central wavelength of source light (λ0 = 1310 nm), zs (t ) =
λ0 λ (ϕch1 − ϕch 2 ) = 0 Δϕ 4π 4π
(4.10)
The two signals recorded from Channel 1 and 2 by the DP-OCT system were used to measure tissue surface displacement zs(t) due to movement of the SPIO nanoparticles.
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4.3.
Results DP-OCT measurements were performed on isolated liver specimens taken
from ApoE-/- mice administrated different SPIO doses (1.0, 0.1 and 0.01 mmol Fe/kg body weight) and saline control samples. Figure 4-3 demonstrates measurements of tissue surface displacement (zs(t)) in liver specimens at different SPIO doses (1.0 and 0.1 mmol Fe/kg body weight) and saline control samples, in response to application of a sinusoidal varying high-intensity focused magnetic field. Measurement of tissue surface displacement (zs(t)) was begun after transient response was negligible and steady state motion persisted. Figure 4-3 (a) shows a magnetic field input (fn= 2 Hz), peak-to-peak voltage (Vpp= 4) over a 1 second time period. Maximum magnetic flux density was 0.47 Tesla and maximal tissue surface displacement (zs(t)) was 2,273 nm in the 1.0 mmol Fe/kg iron-laden liver. Compared to high dose specimens, 0.1 mmol Fe/kg iron-laden liver showed a maximum tissue surface displacement (zs(t)) of 127 nm with additive noise visible in recorded signals. Frequency response (4 Hz) of iron-laden livers (Figure 4-3 (b) and (c)) was exactly twice the modulation frequency (2 Hz) as noted earlier. No significant tissue surface displacement (zs(t)) was observed in either saline control liver specimens (Figure 4-3 (d)) or the 0.01 mmol Fe/kg dose specimen.
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Figure 4-3
Tissue surface displacement (Δzs) in livers with different SPIO
doses (1.0, 0.1 mmol Fe/kg and saline control) using focused magnetic field excitation (2 Hz, 4 Vpp) (a). Tissue surface displacement (Δzs) in specimens with doses 1.0 mmol Fe/kg SPIO (b), 0.1 mmol Fe/kg SPIO, and a saline control liver. The applied magnetic flux density is Bmax= 0.47 Tesla at the liver specimen.
63
Figure 4-4
Maximum tissue surface displacement (Δzs) in iron-laden liver
specimens due to nanoparticle movement in response to a focused magnetic field for miceinjected withvarious SPIO doses (1.0 and 0.1 mmol Fe/kg body weight). The input frequency is 2 Hz with applied voltage ranging from 2 to 8 Vpp (a) and magnetic field strength at each input voltage (b).
SPIO nanoparticle movement in iron laden livers (0.1, and 1.0 mmol Fe/kg) was used to observe quantitatively the relationship between tissue surface
64
displacement (zs(t)) versus different applied magnetic field strengths (Figure 4-4 (a)). Solenoid input frequency in this experiment was 2 Hz with amplitude ranging from 2 to 8 Vpp. Figure 4-4 (b) shows magnetic flux density at the same voltages as in Figure 4-4 (a). Magnitude of tissue surface displacement (zs(t)) of iron-laden liver specimens depended directly on SPIO dose and strength of the external magnetic field. Tissue surface displacement (zs(t)) at high frequency modulation (over 100 Hz) was negligible. Tissue surface displacement (zs(t)) in iron-laden liver specimens (0.1 and 1.0 mmol Fe/kg) can be measured using a swept input frequency. Figure 4-5 (a) shows the magnetic field input with a swept frequency increasing from 1 to 10 Hz over a 2 second time-period. Magnitude of tissue surface displacement (zs(t)) was 2,318 nm in a high dose liver (1.0 mmol Fe/kg) and 177 nm in a low dose specimen (0.1 mmol Fe/kg), and magnetic field intensity was 1.3 Tesla. Frequency response of the force acting on iron-laden liver specimens is exactly twice the externally applied modulation frequency in Figure 4-5 (b) and (c). No significant tissue surface displacement was observed in saline control liver specimens shown in Figure 4-5 (d) and 0.01 mmol Fe/kg liver specimens.
65
Figure 4-5
Tissue surface displacement (Δzs) in iron-laden liver specimens
due to nanoparticle movement in response to a focused magnetic field with a swept frequency (1-10 Hz) input for mice injected with various SPIO doses (1.0 and 0.1 mmol Fe/kg). (a). Tissue surface displacement (Δzs) at 1.0 mmol Fe/kg SPIOdose (b), 0.1 mmol Fe/kg SPIO dose (c), and a saline control liver (d). The applied focused magnetic flux density is 1.3 Tesla at the specimen.
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Figure 4-6 illustrates tissue surface displacement (zs(t)) in a iron-laden mouse liver to observe quantitatively the relationship between magnetic response in tissue versus different applied magnetic field strengths with a swept-source frequency ranging from 1-10 Hz over a 2 second time-period. Magnitude of tissue surface displacement (zs(t)) was larger when input voltage was gradually increased from 2 to 10 Vpp during a frequency sweep. Corresponding magnetic field strength at these voltages was 1.24 (2 Vpp), 1.58 (4 Vpp), 1.71 (6 Vpp), 1.75 (8 Vpp) and 1.84 Tesla (10 Vpp), respectively. For a given frequency sweep, maximum tissue surface displacement (zs(t)) for 0.1 and 1.0 mmol Fe/kg ironladen liver specimens was 3,700 nm and 750 nm at 10 Vpp and magnetic field strength of 1.84 Tesla , respectively. SPIO nanoparticles are identified in histological sections as blue granules from the Prussian blue stain of iron laden mouse livers (Figure 4-7). Compared to controls, iron laden specimens show significant discrete granular iron accumulations evenly distributed in observed areas. Although intracellular iron was also observed in control specimens, this natural iron was uniform and homogeneous rather than appearing in discrete granular shapes. Total SPIO iron area was 5.45% of the histology image as calculated by Image-Pro PLUS 5.1 software.
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Figure 4-6
Maximum tissue surface displacement (Δzs) in iron-laden liver
specimens due to nanoparticle movement in response to a focused magnetic field with a swept frequency (1-10 Hz) input for mice injected with various SPIO doses (1.0 and 0.1 mmol Fe/kg). Input swept frequency ranged from 1-10 Hz over 2 seconds with input voltages increasing from 2 to 10 Vpp (a) and magnetic field strength at each input voltage (b).
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Figure 4-7
Histological cross-section of iron laden liver specimen with
Prussian blue stain. A high concentration of iron is observed (magnification: 20 X). Blue colored regions are iron nanoparticles engulfed by liver based macrophage Kupffer cells (a), and iron-laden macrophages by image processing (b).
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4.4
Discussion In this study, we have demonstrated a novel quantitative diagnostic imaging
modality, using DP-OCT and a high-intensity focused magnetic field, to specifically detect tissue-based macrophages that have taken up iron nanoparticles. Magnetic force acting on the nanoparticles was varied by applying a sinusoidal current (2 Hz and a swept frequency (1-10 Hz)) to a solenoid containing a conical iron core that substantially increased and focused the magnetic field strength (Bmax = 2 Tesla). Frequency response of tissue surface displacement from iron-laden macrophages was exactly twice the exciting frequency of the input magnetic field in Figure 4-3 and 4-5. At excitation frequencies over 100Hz, tissue surface displacement (zs(t)) was too small to measure and evaluate because SPIO nanoparticles and surrounding material did not respond to the applied magnetic field. Our results suggest that DP-OCT may allow detection of liver-based macrophages at relatively low dose of SPIO nanoparticles (0.1 mmol Fe/kg). SPIO nanoparticles, composed of dextran T-10 (Ferumoxides) coated iron oxide, were some of the first materials investigated as MRI contrast agents [14], and more recently used to image focal hepatic lesions in patients using MRI [15]. It is notable that SPIO nanoparticles have been explored for other imaging applications such as detection of malignant lymph nodes [16], brain tumors [17]
70
and bone marrow [18] using contrast enhanced MRI. These particles have also been investigated for use to identify early stages of atherosclerotic vulnerable plaque to image macrophage cells that selectively take up these nanoparticles [19, 20]. More recently, SPIO agent applications have been extended to magnetic separation and sorting of biological molecules [21], targeted drug delivery [22], and magnetic therapeutic hyperthermia using a high frequency magnetic field [23]. Preliminary experiments to quantify macrophages in coronary arteries of patients were performed [24] using intravascular OCT. However, lack of specificity of this approach is noted; for instance, darker OCT images with 10 μm resolution correlated with macrophage presence in histology, but could not rule out contributions from other tissue components. Use of conventional OCT to measure macrophage density in the plaque wall and thereby evaluate macrophage content in vivo may be problematic due to confounding contributions from other tissue components. In conclusion, frequency response of tissue movement in response to an externally applied magnetic field was twice the stimulus frequency and is consistent with established magnetodynamic principles. Increasing the magnetic field strength increased surface displacement of liver specimens. In saline control and 0.01mmol Fe/kg dose liver specimens, no significant tissue surface displacement (zs(t)) was observed in response to an externally applied magnetic
71
field.
Results of our experiments suggest DP-OCT in combination with an
externally applied magnetic field is a candidate methodology to identify tissue macrophages containing SPIO nanoparticles.
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Weisskoff, R.M. and S. Kiihne, Mri Susceptometry - Image-Based Measurement of Absolute Susceptibility of Mr Contrast Agents and Human Blood. Magnetic Resonance in Medicine, 1992. 24(2): p. 375-383.
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Wang, Y.X., S.M. Hussain, and G.P. Krestin, Superparamagnetic iron oxide contrast agents: physicochemical characteristics and applications in MR imaging. Eur Radiol, 2001. 11(11): p. 2319-31.
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Marchal, G., et al., Detection of Liver Metastases with Superparamagnetic Iron-Oxide in 15 Patients - Results of Mr Imaging at 1.5-T. American Journal of Roentgenology, 1989. 152(4): p. 771-775.
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Reimer, P., et al., Hepatic lesion detection and characterization: value of nonenhanced MR imaging, superparamagnetic iron oxide-enhanced MR imaging, and spiral CT-ROC analysis. Radiology, 2000. 217(1): p. 152-8.
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Tsushima, K., et al., Liver metastasis with apparent intratumoral superparamagnetic iron oxide uptake. Eur Radiol, 2005. 15(10): p. 2203-4.
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Reddick, R.L., S.H. Zhang, and N. Maeda, Atherosclerosis in Mice Lacking Apo-E - Evaluation of Lesional Development and Progression (Vol 14, Pg 141, 1994). Arteriosclerosis and Thrombosis, 1994. 14(5): p. 839-839.
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Hundt, W., et al., Effect of superparamagnetic iron oxide on bone marrow. European Radiology, 2000. 10(9): p. 1495-1500.
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Cherukuri, P., et al., Contrast-enhanced intravascular detection of vulnerable plaque using superparamagnetic iron oxide and a novel magnetic resonance imaging catheter. American Journal of Cardiology, 2002. 90(6A): p. 23h-24h.
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Schmitz, S.A., et al., Superparamagnetic iron oxide-enhanced MRI of atherosclerotic plaques in Watanabe hereditable hyperlipidemic rabbits. Investigative Radiology, 2000. 35(8): p. 460-471.
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Said, T.M., et al., Effects of magnetic-activated cell sorting on sperm motility and cryosurvival rates. Fertility and Sterility, 2005. 83(5): p. 1442-1446.
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Neuberger, T., et al., Superparamagnetic nanoparticles for biomedical applications: Possibilities and limitations of a new drug delivery system. Journal of Magnetism and Magnetic Materials, 2005. 293(1): p. 483-496.
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Chapter 5 Detection of magnetic nanoparticles in tissue using magneto-motive ultrasound 8 5.1
Abstract The purpose of this study was to demonstrate magneto-motive ultrasonic
detection of superparamagnetic iron oxide (SPIO) nanoparticles as marker of macrophage recruitment in tissue. Capability of ultrasound to detect SPIO nanoparticles (core diameter ~ 20 nm) taken up by murine liver macrophages was investigated. Eight mice were sacrificed 2 days after intravenous administration of four SPIO doses (1.5, 1.0, 0.5, and 0.1 mmol Fe/kg body weight). In iron-laden livers, ultrasound Doppler measurements showed a frequency shift in response to an applied time varying magnetic field. M-mode scan and color power Doppler images of iron-laden livers also demonstrated nanoparticle movement under focused magnetic field excitation. In livers of saline injected two control mice, no movement was observed using any ultrasound imaging modes. Results of our experiments indicate that ultrasound imaging of magneto-motive excitation is a candidate imaging modality to identify tissuebased macrophages containing SPIO nanoparticles.
8
Portions of this chapter have been published in Nanotechnology 17 (2006), 4183-4190, Title: Detection of magnetic nanoparticles in tissue using magneto-motive ultrasound
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5.2
Introduction Ultrasound is a broadly used tool in medical imaging and has several
advantages over other imaging techniques such as MRI and computed tomography (CT). Ultrasound is a real-time, nonionizing, cost effective, portable, and widely available imaging modality. Ultrasound contrast agents have enabled researchers to expand their investigations into molecular scales, contributing to increased contrast enhancement and also contrast-specific imaging [1]. The most common ultrasound contrast agents, composed of specific gaseous microbubbles in a core shell, have been investigated to enhance contrast in ultrasound medicine [2]. Compared to surrounding tissue, microbubbles present a large acoustic impedance mismatch in tissues and thus produce a strong backscattered sound signal. In addition, microbubbles are used in harmonic [3] and subharmonic imaging [4] to improve subjective image quality. Although microbubbles play an important role in increasing enhancement of diagnostic potential of ultrasound imaging, the micron-sized bubbles have limited use in molecular imaging because these agents are too large to pass through the pulmonary and systemic capillary bed. Moreover, microbubbles are unstable, have a short blood half-life and a propensity to fracture and collapse when exposed to ultrasound waves. Furthermore, microbubbles need sufficient acoustic pressure to increase contrast. These features have limited the use of microbubbles in ultrasound molecular imaging.
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To overcome the size effects and increase the efficacy of enhancement imaging, perfluorocarbon emulsion nanoparticles (PFC), approximately 250 nm in diameter, were reported as an alternative ultrasound contrast agent [5]. Nanometer-sized ultrasound contrast agents may penetrate the large capillary bed, but penetration to vasculature targets and extravasations through tight capillary pores could be inhibited due to their relatively large size [6, 7]. Unfortunately, PFC ultrasound contrast agents produce present a smaller acoustic impedance mismatch, a weaker ultrasound reflected signal, and create less contrast enhancement of echogenic images than gaseous microbubbles. Superparamagnetic iron oxide (SPIO) nanoparticles have been well established over the past decade as a contrast enhancement for MRI imaging. Early studies demonstrated that SPIO nanoparticles can improve detection of liver metastases in patients [8]. After SPIO nanoparticles have been administrated intravenously, tissue-based macrophages (Kupffer cells) in the body take up SPIO nanoparticles through reticuloendothelial system (RES) including bone marrow [9], hepatic lesions [10], lymph nodes metastases in cancer [11, 12], and spleen [13]. Compared to conventional ultrasound contrast agents, magnetically activated SPIO nanoparticles have several advantages including small size, strong magnetic susceptibility, and bio-safety. These nanoparticles (~ 20 nm core size) allow transport through the microvasculature and enable passage through the
79
endothelium
while
retaining
superparamagnetic
properties.
Since
SPIO
nanoparticles for tissue-specific MRI contrast agents were approved by the FDA in 1996, to date, these magnetic nanoparticles have been used in various clinical applications without safety concerns associated with alternative contrast agents. Herein, we demonstrated detection of tissue-based macrophage cells containing SPIO nanoparticles by combining a high strength focused magnetic field to excite iron-laden tissue and then use Doppler ultrasound to detect induced tissue motion. Magnetic force on SPIO nanoparticles was varied by applying a sinusoidal current to a solenoid containing a conical iron core that substantially increased and focused the magnetic field strength (Bmax = 2 Tesla). We hypothesized that since tissue-based macrophages in the RES are known to engulf SPIO nanoparticles, we could use them to identify targeted cells in intact organs such as the liver. The purpose of this study is to detect tissuebased macrophages using magneto-motive ultrasound (MM-US) – a technique where SPIO nanoparticles are excited using an externally-applied magnetic field and then detected and imaged using ultrasound.
5.3
Material and methods
5.3.1
Superparamagnetic iron oxide (SPIO) nanoparticles
SPIO nanoparticles, called Ferumoxides or AMI-25 with trade name of Feridex I.V. (Advanced Magnetics, Cambridge, MA, USA) were used in our
80
experiments. SPIO nanoparticles consisted of nonstoichiometric magnetite cores, iron, and a dextran T-10 coating added to prevent aggregation and facilitate stabilization in the liver. The mean core diameter and volume mean diameter measured by laser light scattering of these nanoparticles were 20 nm, and 80 nm, respectively [14]. Peak concentration of SPIO nanoparticles in the liver were observed 1 hours after an intravenous injection (18 μmol Fe/kg body weight) and slowly cleared in rat model [14]. Uptake of SPIO nanoparticles by macrophage cells is directly proportional to IV concentration, blood half life, and their core size [15].
5.3.2
Animal preparation
Magneto-motive ultrasound (MM-US) imaging studies were conducted using ex-vivo livers obtained from C57BLKS mice (N= 10). All experimental procedures were performed in accordance with protocols approved by the University of Texas Institutional Animal Care and Use Committee. The animals were four months old with an average body weight of 25 g. Eight mice were administered different doses (1.5, 1.0, 0.5, and 0.1 mmol Fe/kg body weight) of SPIO nanoparticles, and two control mice were injected with saline to serve as control group. Feridex I.V. was used for intravenous injections. 48 hours following injections, mice were first euthanized with a lethal dose of Ketamine and Xylazine and the livers were isolated for each ultrasound imaging mode.
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Physical thickness of murine livers was approximately 2.5 cm and 2 cm x 2 cm in lateral dimension.
5.3.3
Experimental preparation
A schematic diagram of the experimental apparatus is shown in Figure 51. A liver sample was placed into small rectangular plastic container (10 cm x 10 cm) filled with water to provide acoustic coupling between ultrasonic transducer and specimen. The sample was imaged from the top using a linear array transducer (128 Channel). Magnetic excitation of the sample was provided by the solenoid positioned below at the bottom surface of the water tank. Distance between the liver specimens and iron core tip was about 1.5 mm, and magnetic field strength at this distance was measured using a teslameter to observe correlation between magnetic field strength and ultrasound measurement. The magnetic generator consisted of a solenoid (Ledex 6EC, SaiaBurgess Inc., USA), a function generator (HP 33120A, Hewlett Packard Inc., USA), a current amplifier, and a regulated D.C power supply. Finite element method (FEM, Maxwell SV, Ansoft Inc., USA) was used to design the magnetic field generator and evaluate magnetic flux density in response to a time-varying input sinusoidal current signal. To maximize magnetic field strength applied to liver specimens, the conical iron core was positioned as close to the bottom surface of the water tank as possible while ensuring no physical contact. FEM
82
calculations and teslameter measurements were consistent and indicated that the maximum magnetic field strength used in this experiment was approximately 2 (Tesla) at a distance of 1.5 mm from the tip of the iron core. The FEM calculation also demonstrated that an iron core inserted in the center of solenoid dramatically increased and better localized magnetic field strength at the liver specimens. Magnetic field distributions from the FEM simulation showed that the maximal and principal direction of magnetic field strength at the liver specimen was along the z-direction due to the conical iron core. Ultrasound experiments were performed ex-vivo using an ultrasound imaging system (Sonosite 180 Plus, Sonosite Inc., USA) equipped with a 38 mm aperture, broadband (10-5 MHz) linear array transducer. Liver specimens were imaged in color power Doppler, power Doppler, M-mode and B-scan modes. Bscan sonogram images, also called gray-scale mode, is the typical ultrasound method to monitor or examine the human body using backscattering of acoustic waves. M-mode ultrasound employs a sequence of scans at a fixed ultrasound beam over a given time period. M-mode is used for visualizing rapidly moving subjects such as heart valves. Compared to conventional B-scan images, Doppler ultrasound is used to assess changes in the frequency of reflected acoustic waves. Color power Doppler converts reflected acoustic waves that are Doppler shifted into colors that overlay the conventional B-scan images and can indicate speed and direction of moving objects. Power Doppler ultrasound is most commonly
83
used to evaluate moving objects and has higher sensitivity than color power Doppler mode. Gain of the color power and Doppler imaging mode was manually adjusted to suppress the background noise. To make objective comparisons, experimental settings of ultrasound instrumentation were unchanged for all specimens imaged.
Figure 5-1
Schematic diagram of experimental setup with magnetic field
generator and conical iron core inside solenoid.
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5.4
Results Leftmost vertical column (Figure 5-2 (a) through (e)) depicts the
conventional B-scan images of intact livers from mice administered 1.5, 1.0, 0.5, and 0.1 (mmol Fe/kg body weight) of SPIO nanoparticles, and control specimen, respectively. These images do not indicate any significant differences between iron-laden and control livers. In these and all other images, the ultrasound probe was positioned near the top of the liver specimens. The middle vertical column (Figure 5-2 (f)-(j)) shows color power Doppler images obtained from the same livers as depicted in Figure 5-2 ((a)-(e)), correspondingly. These color power Doppler images were obtained while a 40Hz, 20 peak-to-peak volts (Vpp) sinusoidal input was applied using a solenoid positioned below the surface of the water tank. Peak magnetic field strength was about 2 Tesla at the specimen as measured by a teslameter. The field of view in color power Doppler images (a rectangular window in Figure 5-2 (a)-(e)) was centered relative to both tip of the solenoid iron core and liver specimens. Compared to lower dose liver specimens, the high dose (1.5 mmol Fe/kg body weight) specimen shows progressively larger areas of Doppler signal, thus allowing detection of tissue-based macrophages. No significant Doppler signal was observed in the control liver specimen (Figure 5-2 (j)). Rightmost vertical column (Figure 5-2 (k)-(o)) displays M-mode measurements obtained from the corresponding liver specimens. The horizontal
85
X-axis in these images represents total running time (5 seconds) with an “on-andoff” applied sinusoidal magnetic field (1 Hz, 20 Vpp; Bmax= 1.5 Tesla) while the Y-axis shows vertical displacement in liver specimens, respectively. M-mode signal intensity and displacement at the center position of the liver specimens increased with SPIO concentration in liver specimens. A high dose specimen (k) in the M-mode signal, for instance, clearly displays movement at twice the frequency of the applied magnetic field; no significant displacement was observed in the control liver specimen (Figure 5-2 (o))
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87
Figure 5-2
Ultrasound grayscale (a-e), color power Doppler (f-j) and M-mode (k-o) images of livers with different
SPIO doses (1.5, 1.0, 0.5, and 0.1 mmol Fe/kg body weight and control liver). Conventional B-scan images were obtained prior to applying magnetic field. In color power Doppler, a focused magnetic field (2 Tesla) was applied. Liver with high dose administration of SPIO (f) shows significant increasing color Doppler signal while normal liver (j) does not exhibit any appreciable color Doppler signal. M-mode signal intensity and displacement is proportional to concentration of SPIO dose. M-mode signal obtained from a high dose specimen (k) clearly demonstrates sinusoidal pattern of the displacement once the magnetic field is turned on.
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Figure 5-3 shows the Doppler shift from livers with different SPIO IV doses; 1.5, 1.0, 0.5, and 0.1 (mmol Fe/kg body weight) and a control liver, respectively. Figure 5-3 (a) shows a Doppler shift while input signal to solenoid is a swept frequency ranging from 1 to 10 Hz over 1 second. Figure 5-3 ((b)-(e)) indicates a slight decrease in Doppler frequency shift with decreasing concentration of SPIO doses in liver specimens when a swept frequency input signal is applied. Figure 5-3 (f) is the input signal of a sinusoidal magnetic field at 1 Hz, 20 Vpp over 5 seconds. The frequency response of different liver specimens was twice that of the applied signal; this result agrees with equation (5-3) and can also be observed in M-mode measurements (Figure 5-2 (k)-(o)). When a 1 Hz sinusoidal frequency input signal is applied over a 5 second period, 10 peak Doppler frequency shifts are observed over 5 seconds. Magnitude of peak frequency shift scales with SPIO dose. No significant displacement of SPIO nanoparticles was observed in salineinjected control specimens.
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Figure 5-3
Doppler shift measured in liver specimens with different SPIO
doses (1.5, 1.0, 0.5, and 0.1 mmol Fe/kg body weight) using swept frequency input ((a)-(e)) and 1 Hz sinusoidal input ((f)-(j)).
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Figure 5-4 demonstrates Doppler shift in response to an applied magnetic field in a liver specimen with a 1 mmol Fe/kg dose. Doppler shift measurement used in this study was measured by the positive maximum frequency using Matlab software (MathWorks, USA). Frequency of the Doppler shift was exactly twice that of the modulated frequency in all data.
Figure 5-4
Doppler shift from liver specimens (1.0 mmol Fe/kg body weight)
with constant (8 Vpp) amplitude sinusoidal input. In all experiments, the peak Doppler shift pattern exhibits a periodicity at exactly twice the frequency of the applied signal.
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Figure 5-5 shows the peak Doppler frequency shift in response to a swept frequency input (1-10 Hz) in liver specimens with various SPIO dose. The inset plot (Figure 5-5(b)) shows peak magnetic flux density vs. voltage (Vpp: peak-topeak volts) of the input signal. Movement of iron-laden tissues depends directly upon SPIO dose and strength of the applied magnetic field. Maximum frequency shift in all specimens was observed when magnetic field strength was 1.85 Tesla. No significant displacement was observed in control liver specimens.
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Figure 5-5
Peak frequency shift in livers with different SPIO doses (1.5, 1.0,
0.5, and 0.1 mmol Fe/kg and control) when applying a swept frequency input (110 Hz) with different input voltages (2 to 10 Vpp). Insert graph (b) shows magnetic flux density of the swept frequency input signal vs. input peak-to-peak voltage.
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SPIO nanoparticles are identified in histological sections as blue granules from the Prussian blue stain of control and iron-laden mouse livers (Figure 5-6). Compared to controls (Figure 5-6 (a)), iron-laden specimens (1.5 mmol Fe/kg body weight) show significant discrete granular iron accumulations evenly distributed in observed areas (Figure 5-6 (b)). Although intracellular iron was also observed in control specimens, this natural iron was homogeneous rather than appearing in discrete granular shapes.
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(a)
(b) Figure 5-6
Histological cross-section of iron-laden liver with Prussian blue
stain. Control specimen (a) and a high concentration of iron (1.5 mmol Fe /kg body weight) (b) are observed (magnification: 20 X). Blue colors regions are iron oxide nanoparticles engulfed by liver based macrophage Kupffer cells.
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5.5
Discussion Primary results of the present study show that SPIO nanoparticles taken
up by macrophages in liver that were detected by magneto-motive ultrasound (MM-US) and application of a time varying magnetic field produced micro-scale displacement of iron-laden macrophage cells. The authors believe this demonstration is the first report of detecting of macrophages in iron-laden tissue by combining an external high intensity focused magnetic field with Doppler ultrasound. To investigate statistical significance of physiological variation in measured Doppler shift, nanoparticle concentration, and other quantities of interest, further studies that incorporate larger numbers of animals will be required. In a previous study, Nolte et al [16] demonstrated detection of magnetic nanoparticles in brain tumors using high resolution intraoperative ultrasound, and improved tumor definition in recorded images. Recently, Liu et. al. (2006) reported use of a B-scan image analysis using a ‘mean grey scale’ to investigate contrast enhancement of silica nanospheres (100 nm) in mice liver. Although these results, which utilized B-mode images without an externally applied field, might hold potential for imaging brain cancer and liver, they may not provide sufficient contrast enhancement for molecular imaging.
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Figure 5-7
Average grey scale value of B-scan images with different SPIO
doses (1.5, 1.0, 0.5, 0.1 mmol Fe/kg and control) ((a)-(e)).
In our study, average grayscale values for B-scan image histograms of liver samples were 41, 38, 37, 35, and 31, respectively (Figure 5-7 (a)-(e)). Average brightness of the lower dose B-scan images decreased slightly with lower SPIO concentration. Conversely, the ultrasound reflective signal increased
97
slightly with higher SPIO doses. Since distinctions of grayscale values between iron-laden and control samples were not noteworthy and would depend on the clinician’s assessment, a better approach is sought after demonstrating contrast enhancement in conventional B-scan images. To evaluate magnetic force acting on SPIO nanoparticles causing displacement of iron-laden tissue becomes:
χ sV
2
B F = −∇U = ∇( B ) = χ sV ∇( ) 2u0 2u0 2
(5.1)
where χs, V are susceptibility and volume of magnetic nanoparticles and B, μ0 are magnetic field strength and permeability, respectively. In our study, we applied a sinusoidal magnetic field strength principally along the z-direction. →
Hence, we write B( x, y, z; t ) = sin(2π f n t )B z ( z )k and total force Fz acting on magnetic nanoparticles in the z-direction is given by ∂ 2 z (t ) ∂z (5.2) ∑ Fz = m ∂t 2 = Fm − kz (t ) − r ∂t χV ∂B ∂z (5.3) ∑ Fz = 2sμ s [1 − cos(4π f nt )]B z ( z ) ∂zz − kz (t ) − r ∂t 0 where Fm is magnetic force, fn is modulation frequency of the applied sinusoidal magnetic field, -kz(t) is an elastic restoring force, and r
∂z is a viscous drag ∂t
force. Equation (5-3) confirmed that the frequency response of the force acting on SPIO nanoparticles is exactly twice the externally applied modulation frequency,
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fn. Accordingly, the frequency response of the ultrasound Doppler shift from the iron-laden tissue was exactly twice the modulation frequency (Figure 5-3 and 54). The frequency doubling feature may be utilized to eliminate unwanted frequency components that arise due to environmental noise and biological motion artifacts. Doppler shift from tissue specimens was correlated with both concentration of SPIO nanoparticles and magnetic field strength. Concentration of SPIO nanoparticles was linearly proportional to the Doppler shift in iron-laden macrophage cells. Increasing the magnetic field strength increase the Doppler shift of iron-laden macrophage cells. In our experiment, SPIO nanoparticles taken up by macrophages were abundant and relatively evenly distributed in histological images.
5.4.1
Application to molecular imaging: MM-US
The role of SPIO nanoparticles as MRI contrast agents has recently expanded from diagnosis of hepatic metastases to agents that target an inflammatory response in several diseases, particularly in atherosclerosis [17, 18] and tumors [19]. Macrophages are cells associated with a response to inflammation and degenerative disorders with high phagocytic activity [20, 21]; therefore imaging of macrophages may be useful to characterize diseased tissue in clinical practice.
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The utilization of magneto-motive ultrasound will be applicable to intravascular ultrasound (IVUS) using high frequency transducer by injection of smaller nanoscale particles, such as ultrasmall SPIO (USPIO) or monocrystalline iron oxide nanoparticles (MION) [22], to identify macrophages as a marker of inflammation. The smaller USPIO and MION (hydrodynamic size: 15-30 nm) have a longer intravascular blood half-life, between 24 and 36 hours, and increased relative stability due to dextran coating; therefore, these nanoparticles can be taken up by macrophages in atherosclerotic vulnerable plaque [23] and malignant tumors[24]. Combining magneto-motive excitation with high frequency detection such as ultrasound biomicroscopy (UBM; 40 - 200 MHz operation frequency) [25] or scanning acoustic microscopy (SAM; ≥ 200 MHz operation frequency) [26] may be more attractive in ultrasound molecular imaging and provide a dramatic increase in resolution over conventional clinical diagnostic ultrasound scanners. Experiments to identify vulnerable plaque and cancer cells using magneto-motive techniques by injection of different diameter nanoparticles and dosages are underway in our laboratory.
5.4.2
Advantages of magneto-motive ultrasound (MM-US)
Magneto-motive ultrasound (MM-US) may provide several advantages over other imaging modalities. Since MRI utilizes a static magnetic field, direct
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application of this imaging approach cannot place magnetic nanoparticles in motion. Further, since MRI is an expensive technology, enhancing the diagnostic value of ultrasound may be cost effective for obtaining improved contrast. Second, macrophages are known to be associated with aggressive cancers of greater malignancy. Ultrasound evaluation of solid tumors is currently limited by a lack of sensitivity and specificity. Detection of magnetic nanoparticle-labeled macrophages associated with tumor cells may enhance the sensitivity and specificity of ultrasound diagnostics.
For instance, ultrasound screening for
prostate cancer via a rectal probe is currently a limited diagnostic modality. Addition of a magnetic probe to an ultrasound device placed over the prostate gland has the potential to improve the sensitivity and specificity of prostate cancer detection. Third, strong magnetic susceptibility of SPIO nanoparticles combined with an externally applied magnetic field offers attractive possibilities in biomedicine and research in targeted drug delivery [27], molecular imaging [28], magnetic bio-sensing [29], and magnetic separation [30]. Inasmuch as SPIO nanoparticles were approved by the FDA in 1996, and are already utilized in clinical applications; many safety concerns of MM-US method have been addressed previously. Finally, molecular imaging by magneto-motive ultrasound (MM-US) may also have value for therapy. A magnetic field, for example, might be used to
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induce magnetic hyperthermia to destroy cancer cells in surrounding tissues [31, 32]. In summary, I have demonstrated a novel diagnostic ultrasound imaging modality to detect SPIO nanoparticles taken up by tissue-based macrophages in a strong, high-intensity magnetic field. Frequency response of the ultrasound Doppler signal from the iron-laden tissue was exactly twice the exciting frequency of the input signal as predicted by magnetic force equations.
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Schmitz, S.A., et al., Magnetic resonance imaging of atherosclerotic plaques using superparamagnetic iron oxide particles. Journal of Magnetic Resonance Imaging, 2001. 14(4): p. 355-361.
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Chapter 6 Magneto-mechanical detection of atherosclerotic macrophages with optical coherence tomography 9 6.1
Abstract We demonstrate the detection of iron oxide nanoparticles taken up by liver
parenchymal Kupffer cells and macrophages in atherosclerotic plaque with differential-phase optical coherence tomography (DP-OCT). The nanoparticles taken up by macrophages were magneto-mechanically excited by an oscillating magnetic flux density and resulting nanometer tissue displacement was detected by DP-OCT. Magneto-mechanical detection of nanoparticles is demonstrated in (a) livers of ApoE-/- mice (4 months, n= 8) sacrificed 2 days post intravenous injection of superparamagnetic iron oxide (SPIO) nanoparticles (1.0, 0.1, 0.01 mmol Fe/kg body weight) or saline; and (b) hyperlipidemic Watanabe rabbits (n= 4) injected with monocrystalline iron oxide (MION) nanoparticles (0.2 mmol Fe/kg body weight) or saline. Histological analysis with Prussian blue stain for iron and RAM-11 for macrophage identification confirmed the presence of iron in macrophages
in
DP-OCT
magneto-mechanical
positive
aortic
regions.
Experimental data is supported with a magneto-mechanical Voigt model of nanoparticle movement in tissue.
9
A portion of this chapter was submitted to The Proceedings of the National Academy of Sciences USA in September 2006
108
6.2
Introduction Atherosclerosis leading to myocardial infarction, stroke, and peripheral
vascular disease is the leading cause of death worldwide. The histologic features characteristic of plaque rupture are well established by autopsy studies in humans. However, no in situ approaches are available to identify which atherosclerotic plaques are vulnerable and thus prone to rupture. Many inflammatory cells and molecules associated with plaque vulnerability have been identified, contributing to the hypothesis that inflammation plays a significant role in initiation, progression, mechanical instability and rupture of atherosclerotic plaque [1-3]. Several features of the inflammatory process have been identified that contribute to mechanical instability and increased risk of plaque rupture, these include: activation and recruitment of macrophages [4], over-expression of matrix metalloproteinases (MMP) [5], decreasing collagen synthesis [6], and thinning of the fibrous cap overlying a large lipid core [7, 8]. Activation and recruitment of macrophages can induce breakdown of a thin fibrous cap and increase mechanical instability and risk of plaque rupture by local production of MMPs.
Thus,
macrophages are an important cellular marker for the risk of plaque rupture in the coronary, cerebral, and peripheral circulations. Optical coherence tomography (OCT) [9] is a rapidly emerging imaging modality demonstrating improved resolution capable of performing cellular imaging (resolution of 3-4 µm) not available with other techniques such as
109
intravascular ultrasonography (IVUS) [10], multi-slice CT [11], and magnetic resonance imaging (MRI) [12]. More recently, OCT has been successfully applied to image quantitatively morphometric features of vulnerable plaque such as the large lipid core and thin fibrous cap associated with vulnerable plaques [7, 8, 1316]. Despite these promising results, no demonstration has been reported that OCT can perform cellular imaging of in situ mammalian tissues despite its anticipated cellular resolution. In fact, use of conventional OCT has not been able to distinguish macrophages from surrounding tissues with high confidence in the presence of atherosclerosis [13]. Investigators have demonstrated that phase sensitive microscopy based on spectral-domain OCT could be used for quantitative phase-contrast imaging with improved resolution [17-19]. Differential-phase optical coherence tomography (DP-OCT) is capable of high path length sensitivity and is able to detect a 1 nm optical path length change (Δp) between discrete reflecting surfaces [20]. DPOCT has been applied to phase contrast imaging of cells [19], used to measure nanometer-scale displacement changes corresponding to neuron activity [21], electro-kinetic response of cartilage [22], photo-thermal response of tissue [21], and changes in analyte concentration [23]. We hypothesized that macrophages in tissue taking up iron oxide nanoparticles could be detected by DP-OCT following magneto-mechanical excitation. In this approach, magneto-mechanical force on iron nanoparticles within macrophages produces an elastic displacement of the
110
atherosclerotic plaque that is detected with DP-OCT. Objective of the present study is to develop a method to detect macrophages with high confidence first in liver since they are abundant and homogenous, and to subsequently extend this approach to macrophages in atherosclerotic plaque. By applying a sinusoidal magnetic flux density, magneto-mechanical force on iron-laden macrophages produces an oscillating motion of the nanoparticles and a resulting tissue surface displacement. We demonstrate capability of DP-OCT to measure quantitatively the magneto-mechanical tissue surface displacement indicating presence of macrophages. These results are the first demonstration of in situ cellular identification with OCT.
6.3.
Material and methods
6.3.1 Iron oxide nanoparticles
Two types of magnetic nanoparticles, SPIO (Feridex I.V., Berelex Laboratories, USA) and MION (MION-47, Advanced Magnetics, Cambridge, MA, USA), were used to investigate detection of macrophages in murine liver and plaque in rabbit aorta, respectively. Colloidal suspensions of SPIO nanoparticles are tissue-specific MRI contrast agents and approved by the United States FDA for human use. Following injection of SPIO nanoparticles into rats, 80% of injected nanoparticles accumulate in tissue-based macrophages (Kupffer cells) in
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the liver due to the relatively short blood half life [24] compared to ultrasmall SPIO nanoparticles. MION composed of a monocrystalline iron core with a dextran coating was used as a magnetic label and were taken up by inflammatory macrophages in atherosclerotic lesions. The core diameter of these particles is approximately 5 nm [25] without the coating and due to their long circulation half-time, they can partially bypass the liver and spleen and be phagocyted by endothelial cells and macrophages in plaque. Based on these considerations, we chose MION for the atherosclerotic studies.
6.3.2
Experiment preparation
All experimental procedures were performed in accordance with protocols approved by the University of Texas Institutional Animal Care and Use Committee. Livers from 12 week old ApoE-/- high fat fed mice (n= 8) were used to demonstrate the magneto-mechanical detection technique. Liver was chosen to initially test our hypothesis since it contains diffusely distributed and large numbers of parenchymal Kupffer cells. Mice were injected via the jugular vein with either SPIO (Feridex I.V., Berelex Laboratories, USA) for IV administration (1.0, 0.1, and 0.01 mmol Fe/kg body weight), and then sacrificed 2 days post intravenous injection. The mice were euthanized with a lethal dose of Ketamine and Xylazine. After euthanizing, abdominal incisions were made to remove the
112
entire liver from the mouse. Livers were cut into 1 x 5 x 5 mm3 sections for DPOCT measurement of magneto-mechanical tissue surface displacement. Hyperlipidemic Watanabe rabbits (n= 4) were injected with 0.2 mmol Fe/kg body weight MION or saline. After 3 days, the animals were euthanized with a lethal dose of phenobarbitol and the aorta specimen was removed and cut into 2 x 3 mm2 sized specimens (n= 60/rabbit).
Histology Analysis After completion of DP-OCT measurements, the mouse livers and rabbit aorta were fixed with10% formalin acid and processed for histology. 5 μm thick sections were cut and stained with Prussian blue to identify iron deposition and RAM-11 for macrophage cell identification in the atherosclerotic lesions.
6.4
Results In hyperlipidemic Watanabe atherosclerotic rabbits, measurements of
peak-to-peak magneto-mechanical surface displacement (Δzs(t)) are illustrated (Figure 6-1 A and B) in an ex vivo aorta specimen with MION injection (0.2 mmol Fe/kg body weight) and a saline control. Peak-to-peak magneto-mechanical tissue surface displacement (Δzs(t)) while applying a 2 Hz, 0.25 Tesla input magnetic flux density to aorta specimens was 138 nm in Figure 6-1 A while no
113
significant peak-to-peak magneto-mechanical tissue surface displacement (Δzs(t)) was observed in saline control aorta specimens. Peak-to-peak magneto-mechanical tissue surface displacement (Δzs(t)) in rabbit aorta specimens (0.2 mmol Fe/kg body weight) was measured in response to one-second application of a swept frequency (1-10 Hz) high intensity focused magnetic flux density (Figure 6-1 B). Peak-to-peak magneto-mechanical tissue surface displacement (Δzs(t)) was 677 nm with maximum magnetic flux density of 1.7 Tesla. Frequency response of the magneto-mechanical tissue movement of MION aorta specimens was exactly twice the externally applied modulation frequency (Figure 6-1 A and B).
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A
B
Figure 6-1
Magneto-mechanical tissue surface displacement (Δzs(t)) in 0.2
mmol Fe/kg of MION-laden aorta specimens by applying 2 Hz 4 Vpp (Bmax = 0.25 Tesla) (A), and magneto-mechanical tissue surface displacement (Δzs(t)) in 0.2 mmol Fe/kg of MION-laden aorta specimens by applying a swept frequency excitation (1- 10 Hz) over a 1 second time-period (Bmax = 1.70 Tesla) (B).
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Peak-to-peak magneto-mechanical tissue surface displacement (Δzs(t)) in MION atherosclerotic aorta (0.2 mmol Fe/kg body weight) with frequency of the sinusoidal magnetic flux density increasing from 2 Hz to 5 Hz in 1 Hz increments is 123 nm (a), 156nm (b), 174 nm (c), and 177 nm (d), respectively (Figure 6-2). Increasing the modulation frequency of the magnetic flux density from 2 Hz to 4 Hz, increased peak-to-peak magneto-mechanical tissue surface displacement (Δzs(t)) by 30 nm/Hz. Further increases in frequency of the sinusoidal magnetic flux density did not substantially increase magneto-mechanical tissue surface displacement (Δzs(t)). The frequency response of magneto-mechanical tissue surface displacement (Δzs(t)) was twice the frequency of the sinusoidal magnetic flux density.
116
Figure 6-2
Magneto-mechanical tissue surface displacement (Δzs(t)) in
MION-laden aorta specimens with input frequency ranging from 2 Hz to 5 Hz in 1 Hz increments with MION dose (0.2 mmol Fe/kg body weight).
117
Quantitative analysis of experiments in MION aorta specimens using boxand-whisker
plots
of
peak-to-peak
magneto-mechanical
tissue
surface
displacement (Δzs(t)) vs. applied sinusoidal (2 Hz) input voltage (2-10 Vpp) with 0.2 mmol Fe/kg MION dose (a) and control specimens (b) are shown in Figure 63. Corresponding magnetic flux density for sinusoidal input voltages was 0.25, 0.47, 0.67, 0.87, and 1.10 Tesla, respectively. Compared to MION aorta specimens, magneto-mechanical tissue surface displacement of control specimens did not vary with increasing magnetic field, with maximum displacement less than 20 nm corresponding to the noise level for the measurement.
118
th
mean
min
Edges of rectangular box are the 25th percentile, 75th percentile, respectively. Central small box indicates the mean and whiskers show the minimum and maximum values.
th
75 percentile
25 percentile
max
median
Figure 6-3
Quantitative analysis of MION aorta specimens using box-and-
whisker plot of peak-to-peak magneto-mechanical tissue surface displacement (Δzs(t)) vs. sinusoidal (2 Hz) input voltage with 0.2 mmol Fe/kg MION dose (a) and control specimens (b).
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Histological images of an aorta tissue section of a WHHL rabbit injected with MION at a dose of 0.2 mmol Fe/kg body weight corresponding to a DP-OCT measurement (Δzs(t)= 80 nm with 2 Hz, 2 Vpp sinusoidal input) are shown in Figure 6-4. Prussian blue stain (a) demonstrates MION engulfed by a macrophage (a) which also stains positive with RAM-11 (b), confirming this cell is a macrophage in intimal hyperplasia.
(a) Figure 6-4
(b)
Histological images of atherosclerotic MION-laden aorta tissue
section where magneto-mechanical tissue surface displacement was measured with DP-OCT (Δzs= 80 nm with 2 Hz, 2 Vpp sinusoidal input). Prussian Blue (a) and RAM-11 stains (b) at a MION dose (0.2 mmol Fe/kg body weight) are shown. Adjacent histologic sections indicated in (a) and (b) are 5 μm apart and demonstrate presence of MION in macrophages.
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6.5
Discussion We have demonstrated a novel quantitative diagnostic imaging modality
that uses DP-OCT combined with a high-intensity focused magnetic flux density, to detect macrophages in intact tissues that have taken up magnetic nanoparticles. Magnetic force acting on the nanoparticles was varied by applying a sinusoidal or swept-frequency current to a solenoid containing a conical iron core that substantially increased and focused the magnetic flux density on the tissue. Frequency response of magneto-mechanical tissue surface displacement in ironladen liver and aorta specimens was twice the externally applied modulation frequency. Our results suggest that DP-OCT with nanometer sensitivity allows detection of iron-laden macrophages at relatively low doses (0.2 mmol Fe/kg body weight) and may be clinically relevant to detect atherosclerotic plaque in patients. Locations of magneto-mechanical tissue motion measured with DP-OCT were confirmed with histology to be areas positive for macrophages which had taken up iron nanoparticles. Preliminary experiments to identify macrophages in coronary arteries of patients have been reported [13, 26] using intravascular OCT. However, limitations in the specificity of this approach to identify macrophages is noted; for instance, although dark regions in OCT images correlated with macrophage presence in histology, contributions from other tissue components could not be ruled out. Use of conventional OCT to identify macrophages with high confidence
121
in plaque lesions and thereby evaluate macrophage density in vivo may be problematic due to confounding contributions from other tissue components. Magneto-motive OCT was recently demonstrated to enhance image contrast using magnetic particles in vivo in tadpoles by measuring optical scattering changes [27]. This approach did not provide a quantitative phase-based measurement of tissue displacement. Thus, our studies are the first to perform with high confidence cellular identification of tissue based macrophages and distinguish them from other competing plaque components. For all steady state experimental data, frequency response of magneto mechanical tissue surface displacement (zs(t)) from iron-laden macrophages was twice the excitation frequency of the input magnetic flux density. The frequency doubling effect is due to magnetic force being proportional to the product of magnetic flux density and the gradient. The magnetic flux density induces a magnetic moment in the iron nanoparticles which experience a force proportional to the gradient of the external field. When magnetic flux density reverses direction, the induced magnetic moment flips together with the gradient of the external field producing a force in the same direction. Reversing the magnetic flux density does not reverse the force on iron nanoparticles, but does give the displaced surrounding tissue time to generate elastic restoring forces. The result is an oscillatory motion of the tissue at twice the frequency of the applied field.
122
In a simple Voigt model of macrophages, peak-to-peak nanoparticle displacement in steady state occurs when ωB = ω0 − 2
2
γ2 2
, where ωB = 4π f n is
angular frequency of the magnetic flux density, and γ is a viscous damping parameter characteristic of the frictional force of surrouding cytoplasm on the nanoparticles, and ω0 is natural frequency of the cytoskeleton elastic force. Alternatively at high modulation frequencies ( ω0 >> ωB ) amplitude of movement diminishes to zero. Variation of Δzs(t) by applying a swept frequency modulation is associated with spatial variations of viscoelastic tissue properties ( γ , ω0 ) in different specimens. The Voigt model of the nanoparticles in the macrophages was used in combination with Mindlin’s solution for a point source in an elastic half-space to compute tissue surface displacement. We assumed 108 nanoparticles in a macrophage positioned 50 μm below the tissue surface with B
⎛T2 ⎞ ∂B = 220 ⎜ ⎟ and ∂z ⎝m⎠
a tissue shear modulus G= 5 kPa and Poisson ratio ν= 0.45 to
give Δzs = 110 nm. This number of nanoparticles condensed in a single macrophage would occupy a volume of about 6.5 μm3. To improve quantitative analysis, a fractional calculus mathematical model which incorporates a more realistic cellular anatomy of iron nanoparticles contained in lysosomes may be required.
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In conclusion, frequency response of tissue surface displacement in response to an externally applied magnetic flux density was twice the stimulus frequency and is consistent with established magnetodynamic principles. Increasing the magnetic flux density strength increased magneto-mechanical surface displacement in specimens containing iron nanoparticles. In saline control specimens, no significant magneto-mechanical tissue surface displacement (Δzs(t)) was observed in response to an externally applied magnetic flux density in both liver and atherosclerotic aorta specimens. Results of our experiments suggest that although further research is required, magneto-mechanical DP-OCT may be a candidate technique to detect macrophages containing magnetic nanoparticles for imaging in atherosclerosis. Since presence of macrophages in plaque is a high risk feature, this technique may have clinical relevance to patients undergoing catheterization.
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Chapter 7 Hemoglobin contrast in magneto-motive optical Doppler tomography 10 7. 1
Introduction Optical coherence tomography (OCT) uses the short temporal coherence
properties of broadband light to extract structural information from heterogeneous samples such as biologic tissue. During the past decade, numerous advancements in OCT have been reported including cellular-level resolution [1] and real-time imaging speeds [2]. Conventional OCT imaging primarily utilizes a single backscattering feature to display intensity images. Functional OCT techniques process the backscattered light to provide additional information on birefringence [3-6], and flow properties [7]. Since ability to characterize fluid flow velocity using OCT was first demonstrated by Wang et al [8], several phase resolved [9], real-time [10, 11] optical Doppler tomography (ODT) approaches have been reported. In ODT, the Doppler frequency shift is inversely proportional to the angle between the probe beam and the scatterer’s flow direction. When the two directions are perpendicular, Doppler shift is zero. Because a priori knowledge of the Doppler angle is not available, and conventional intensity OCT imaging provides a low contrast image of microvasculature structure, detecting small vessels with slow 10
Portions of this chapter have been published in Optics Letters, Vol. 31, No.6, pp. 778~780, 2006. Title: Hemoglobin contrast in magneto-motive optical Doppler tomography
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flow rates is difficult. However, the Doppler angle can be estimated [12] by combining Doppler shift and Doppler bandwidth measurements. The ability to precisely locate the microvasculature is important for diagnostics and treatments involving characterization of blood flow. Recently, several efforts to increase blood flow contrast mechanisms have been reported including protein microspheres incorporating nanoparticles into their shells [13], plasmon-resonant gold nanoshells [14], and use of magnetically susceptible
micrometer sized
particles with externally applied magnetic field [15]. Use of an externally applied magnetic field to move magnetically susceptible particles in tissue has been termed magneto-motive OCT (MM-OCT). Functional magnetic resonance imaging (fMRI) detects deoxy-hemoglobin which is a paramagnetic molecule. However the paramagnetic susceptibility of human tissue is very low compared to other biocompatible agents such as Ferumoxides (nanometer sized iron oxide particles). Therefore, it has been believed that, other than differentiating relaxation times (T2) between oxygenated and deoxygenated blood, the magnetic field strength required to produce a retarding force on blood flow is well above that of current imaging fields [16]. In this chapter, we present a novel extension of MM-OCT analogous to the features of fMRI, to image hemoglobin in erythrocytes in blood. The contrast of ODT images can be enhanced by activating iron-containing hemoglobin molecules in blood with an externally applied high-strength magnetic field
130
gradient. Importantly, our approach requires no exogenous contrast agent to detect blood flow and location. We describe the MM-ODT experimental setup containing an oscillating magnetic field generator, and present M-mode images of the Doppler shift of moving hemoglobin under the influence of an externally applied magnetic field gradient.
7. 2
Method and experimental setup
The material parameter characterizing magnetic materials, including biologic tissue, is the magnetic volume susceptibility, χ, which is dimensionless in SI units and is defined by the equation M = χH. Here M is the magnetization at the point in question and H is the local density of the magnetic field strength. The high iron content due to, four atoms in each hemoglobin molecule, and the large concentration of hemoglobin in human red blood cells (RBCs) makes this molecule a useful test case for investigating magneto-motive effects in biologic tissue. The susceptibility of the hemoglobin molecule consists of a paramagnetic component due to the electron spins of the four iron atoms. The paramagnetic susceptibility is given by the Curie Law,
χ=
μ0 N p ( μeff2 μ B2 ) 3kT
131
(7.1)
where μ0 is permeability of free space and has the value 4π×10-7 H/m, and Np is the volume density of paramagnetic iron atoms in hemoglobin, Np = 4.97×1025 iron atoms/m3, and μeff is the effective number of Bohr magnetons per atom [17] reported as 5.35, and the Bohr magneton, μB=9.274×10-24 J/T, and Boltzmann’s constant, k=1.38×10-23 J/K, and T is the absolute temperature (K). The calculated susceptibility of an RBCs is about 1×10-6 under assumption of 90% concentration of hemoglobin per RBCs. An RBCs placed in a magnetic field gradient experiences forces and torques that tend to position and align it with respect to the field’s direction. The magnetic force, in direction of the probing light z, is given by FZ = mRBC
∂ 2 z (t ) ∂t 2
=−
∂U ∂z
=
ΔχV u0
B
∂B ∂z
,
(7.2)
where V is the particle volume, and B is the magnitude of the magnetic flux density. According to equation(7.2), the magnetic force on a RBCs per unit field gradient, B(∂B/∂z) T2/m, is 125 nN. The displacement [z(t)] of a RBCs driven by a time varying magnetic flux density can be included in the analytic OCT fringe expression, If the fringe intensity is given by, ⎡ ⎛ 4π n ⋅ z (t ) ⎞ ⎤ I f ∝ 2 I R I S exp ⎢i ⎜ 2π f 0t + ⎟⎥ , λ 0 ⎝ ⎠⎦ ⎣
132
(7.3)
where IR and IS are the back scattered intensities from reference and sample arms, respectively, and f0 is the fringe carrier frequency, and λ0 is the center wavelength of the light source, and z(t) is the RBCs displacement. Here we describe MM-ODT imaging of the hemoglobin Doppler shift of hemoglobin by applying an oscillating magnetic field to moving blood. A schematic of the MM-ODT apparatus is shown in Figure 7-1. The OCT light source consisted of a super luminescent diode (B&W TEK, DE) centered at 1.3 μm with a bandwidth of 90 nm. Light was coupled into a single-mode optical fiber based interferometer that provided 1 mW of optical power at the sample. A rapid-scanning optical delay (RSOD) line is used in the reference arm. The RSOD is aligned such that no phase modulation is generated when the group phase delay is scanned at 4 kHz. The phase modulation is generated using an electro-optical waveguide phase modulator that produced a carrier frequency (1 MHz). To reduce the light source noise from the OCT interference signal, a dual-balanced photodetector of 80 MHz bandwidth was used. A hardware in-phase and quadrature demodulator with high/bandpass filters was constructed to improve imaging speed. Doppler information was calculated with the Kasai autocorrelation velocity estimator. Labview software (National Instruments, TX, USA) was used to implement the MM-ODT system with a dual processor based multitasking scheme. Maximum frame rate of the system is 16 frames per second for a 400 × 512 pixel sized image. In the sample arm, a collimated beam was redirected to the
133
sample by two galvonometers that permit three-dimensional scanning. The probe beam was focused by an objective lens, which yields a 10 μm spot at the focal point. A 750 μm-diameter glass capillary tube was placed perpendicularly to the probing beam. Deoxygenated blood was injected through the tube at a constant flow rate controlled by a dual-syringe pump (Harvard Apparatus 11 Plus, Holliston, MA) with ± 0.5% flow rate accuracy. SLD
RSOD
Circulator
2 x 2 Splitter
X- scanner Magnetic Field Cos LPF
Y- scanner
HPF
Sample LPF
Figure 7-1
Schematic diagram of the MM-ODT system. SLD: Super-
luminescent diode, HPF: high pass filter, LPF: low pass filter.
134
As shown in Figure 7-2, a solenoid coil (Ledex 4EF, USA) was placed underneath the sample during MM-ODT imaging. The solenoid coil, with a coneshaped ferrite core at the center, was driven by a current amplifier supplying up to 960 W of power. Combination of the core and solenoid, using high power operation, extensively increased the magnetic field strength (Bmax= 1.5 Tesla) at the tip of the core and also focused the magnetic force on the targeted samples. The magnetic force applied to the capillary tube was varied by the sinusoidal current to introduce RBC movement.
ODT SYSTEM ODT Probe Beam
Capillary Tube
Red Blood Cells
Blood Flow
Power Supply Amplifier Magnetic Generator Figure 7-2
Signal Generator
Schematic diagram of the probe beam, blood flow sample,
solenoid coil, and function generator.
135
7. 3
Results and Discussion To demonstrate the experimental approach, we recorded M-mode
OCT/ODT images of a capillary glass tube filled with a turbid solution with and without an external magnetic field as a control sample. The turbid solution was a mixture of deionized water and 10% volume concentration 0.5 μm latex micro spheres. The magnetic flux density and its frequency were about 1 Tesla and 50 Hz, respectively. M-mode OCT/ODT images were acquired for 100 ms per frame. Figure 7-3 (a) and (b) show M-mode OCT and ODT images without any external magnetic field. The ODT image (Figure 7-3 (b)) contains small random phase fluctuations due to ambient vibration in the optical path. Figure 7-3 (c) and (d) show M-mode OCT/ODT images with a 50 Hz external magnetic field. No distinguishable Doppler shift could be observed in the ODT image (Figure 7-3 (d)) indicating no interaction between the external magnetic field and the moving microspheres. Deoxygenated blood was extracted from a vein of a male volunteer’s left arm, and diluted with saline. During the preparation, the blood was not exposed directly to air to remain deoxygenated. To simulate blood flow, the syringe pump injected the blood through the capillary tube at a relatively constant flow rate. An oscillating Doppler frequency shift, resulting from RBCs movement, could be observed (Figure 7-4) at two different flow rates (5 and 30 mm/s). Because the flow direction was nearly perpendicular to the probing beam, no
136
significant Doppler frequency shift was distinguishable at the 5 mm/s flow rate (Figure 7-4 (a)) without any external magnetic field. In the case of the high blood flow rate, 30 mm/s, as shown at Figure 7-4 (c).
(a)
(c) (b)
1 KHz
(d)
(b)
- 1 KHz Figure 7-3
OCT/ODT images of a turbid solution with and without an external
magnetic field. (a), (b) OCT and ODT images without a magnetic field, respectively. (c), (d) OCT and ODT images with a 50 Hz magnetic field, respectively.
Doppler frequency shift, caused by blood flow, could be observed. However, application of a 50 Hz magnetic field increased blood contrast at both
137
the slow and fast flow rates as shown at Figure 7-4 ((b) and (d)). Note that in the high flow rate case, 30 mm/s, higher blood contrast is observed than the low flow rate case, but the Doppler frequency shift of the former as a function of depth is less homogeneous than the latter, which is indicative of perturbation by blood flow. The same blood was diluted to 5% HCT, but no RBC movement could be observed below 8% HCT.
138
(a)
(b)
(a) (b)
(c)
(d)
1 KHz
(b)
- 1 KHz
Figure 7-4
M-mode ODT images of the diluted deoxygenated blood flow
(HCT 18%) with and without an external magnetic field. (a), (b) ODT images of 5 mm/s blood flow without/with a 50 Hz magnetic field, respectively. (c), (d) ODT images of 30 mm/s blood flow without/with a 50 Hz magnetic field, respectively.
Doppler frequency shift profiles were calculated from ODT images (Figure 7-4 (a) and (b)) by averaging 20 lines at a selected depth indicated by horizontal arrows. Figure 7-5 (a) indicates no significant Doppler frequency shift
139
over a 100 ms time period, whereas Figure 7-5 (b) displays ± 200-300 Hz Doppler frequency shifts oscillating 20 times over 100 ms (200 Hz). The implication of the Doppler frequency shift is that the RBCs physically move into and away from the incident light while passing through the external magnetic field, and that the 200 Hz oscillation of the Doppler frequency shift correlates with a 50 Hz magnetic field. We observed frequencies 4 times higher than that of the external magnetic field (fm). According to equation (7.2), the frequency of the force on paramagnetic targets is twice that of the magnetic flux density; therefore, a 50 Hz B field might be expected to targets at 100 Hz. Although the fringe signal (equation (7-4)) contains harmonics at frequency (2 fm), the modulation frequency, fm, was set so that the second-order sideband (4 fm) is dominant as shown in Figure 7-5 (b).
140
(a)
(b)
Figure 7-5
Doppler frequency shift profiles (a) without an external magnetic
field, (b) with a 50 Hz magnetic field.
141
7. 4
Conclusions In conclusion, we have demonstrated what is believed to be the first
implementation of MM-ODT for improved Doppler imaging of blood flow using an external oscillating magnetic field. We could successfully introduce mechanical movement of RBCs during blood flow by a temporally oscillating high-strength magnetic field. MM-ODT may allow imaging of tissue function in a manner similar to functional magnetic resonance imaging (fMRI) of deoxygenated blood in organs. The controlled and increased Doppler frequency in MM-ODT may provide a new investigational tool to study in vivo blood transport.
142
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145
Appendix A
1
Magneto-motive detection of macrophages in liver and spleen by DP-OCT 11
Introduction Superparamagnetic iron oxide (SPIO) nanoparticles have been studied for
over a decade to evaluate hepatic and splenic tumors by magnetic resonant imaging (MRI) [1]. Macrophages, especially Kupffer cells inside liver and spleen, take up SPIO nanoparticles by the reticuloendothelial (RES) system. According to previously reported clinical studies, the most common application of SPIO nanoparticles was as a liver-specific MRI contrast agent, especially for imaging focal liver lesions and hepacellular carcinoma [1, 2]. Following intravenous administration of SPIO nanoparticles, peak concentration of nanoparticles was observed one hour later in liver and spleen of rats; decreased amounts of iron were observed after 9 days in both liver (~ 20% of SPIO IV) and spleen (~ 6% of SPIO IV) [1]. Differential phase optical coherence tomography (DP-OCT) is a fiberbased dual channel optical low-coherence reflectometer which may be applied to measure optical differential phase of light reflected from two discrete surfaces [3]. Recently, DP-OCT studies have been reported to measure nanometer displacement
11
of
several
phenomenon,
including
electrokinetic
Portion of this chapter was published in Laser surgery medicine and biology
146
surface
displacement in cartilage samples in response to an electric current [4], neuron activity without application of chemicals or a reflecting coating [5], laser induced photothermal response in tissue [5], and quantitative phase contrast imaging [6]. More recently, Oldenburg reported magneto-motive detection using optical coherence tomography to detect nanoparticles in tadpole (Bmax = 0.06 Tesla) [7]. Magneto-motive optical Doppler tomography was applied to detect human blood flow in an in vitro preparation by applying a temporally oscillating high strength magnetic flux density (Bmax = 0.7 Tesla) [8]. Magneto-motive ultrasound was demonstrated to identify tissue-based macrophage cells by applying a high focused magnetic flux density (Bmax = 2 Tesla) [9]. Herein, we describe use of magneto-motive detection of tissue-based iron laden macrophages by applying a high-strength focused magnetic flux density (Bmax = 0.5 Tesla)
2
Materials and methods
2.1
Animal model All experimental procedures were performed in accordance with
protocols approved by the University of Texas Institutional Animal Care and Use Committee. Colloidal suspensions of SPIO are tissue-specific MRI contrast agents approved in 1996 by the United States Food and Drug administration (FDA) for human use. Mean core diameter of these nanoparticles is 20 nm and total aggregation diameter is about 100 nm [10]. Magnetic susceptibility of SPIO
147
nanoparticles was reported as 0.89 x 10-2 in CGS unit [10]. Liver and spleen from apolipoprotein E knockout (ApoE-/-) mice of 25 g mean weight and 12 weeks old, were examined. Mice were injected intravenously via the jugular vein (1.5 mmol Fe/kg body weight) with Feridex IV (Berelex Lab, USA). After 9 days post intravenous (IV) injection of SPIO, the mice were euthanized with a lethal dose of Ketamine and Xylazine. After euthanizing, abdominal incisions were made to remove the entire liver from the mouse. Animals were divided into two groups, iron-laden and control mice with saline injection. DP-OCT was used to measure tissue surface displacement in two groups of isolated specimens in response to application of a high strength focused magnetic field. Physical thickness of specimens was 1mm and 0.5 cm x 0.5 cm in the lateral dimension. After completion of DP-OCT measurements, the mouse liver and spleen were embedded in 10% formalin acid and processed for histology. 5 μm thick sections were cut and stained with Prussian blue to identify iron deposition in liver and spleen macrophage cells. To verify SPIO uptake by macrophage cells from histology slides, Image Pro Plus (Mediacynernetics Inc., USA) software was used to measure fractional area of liver and spleen SPIO uptake that is Prussian blue positive.
148
2.2
Magnetic Force Acting on SPIO Nanoparticles To evaluate magnetic force on superparamagnetic (SPIO) nanoparticles,
magnetic energy, U, can be used [11]. Magnetic force, F, acting on SPIO nanoparticles is written: F = −∇U = ∇(
χ sV 2u0
B2 ) = χ sV ∇(
B2 ) 2u0
(4)
Where μ0 (= 4π × 10−7 H/M) is permeability of free space, V is nanoparticle volume, χs, is susceptibility of SPIO nanoparticles, and B is magnetic flux density →
∧
on magnetic nanoparticles. We write B ( x , y , z ; t ) = sin(2 π f n t ) B z ( z ) k where ∧
k is the unit vector in the z-direction and parallel to DP-OCT incident light direction. Magnetic force equation can be rewritten as F=
χ sVs ∂B [1 − cos(2π (2 f n )t )]B z ( z ) z , 2 μ0 ∂z
(5)
and the magnetic force Fz acting on nanoparticles in the z-direction is given by,
Where Fm
∂ 2 z (t ) ∂z (6) ∑ Fz = m ∂t 2 = Fm − kz (t ) − r ∂t , χV ∂B ∂z (7) ∑ Fz = 2sμ s [1 − cos(2π (2 f n )t )]B z ( z ) ∂zz − kz (t ) − r ∂t , 0 is magnetic force, fn is the modulation frequency of the applied
sinusoidal magnetic flux density, kz(t) is an elastic restoring force, and r
∂z is a ∂t
viscous drag force that accounts for the viscoelastic properties of the local tissue
149
environment surrounding nanoparticles. Motion of nanoparticles at double the modulation frequency originates from the magnetic force being proportional to the product of the field and field-gradient. Magnetic flux density was measured by a Teslameter, which was connected to A/D converter and personal computer before performing DP-OCT measurement.
2.3
Differential Phase Optical Coherence Tomography (DP-OCT) Magnetic generator consisted of a solenoid (Ledex 4EC, Saia-Burgess
Inc., USA) with conical iron core, signal generator, current amplifier and power supply. DP-OCT system was used to measure differential phase between light backscattered from specimens and a reference surface when applying sinusoidal focused magnetic field excitation. Partially polarized light from an optical semiconductor amplifier (AFC Technologies, central wavelength λ0= 1.31 μm, FWHM = 60 nm, optical coherence length= 22 μm) was polarized and coupled into fast and slow axes of a polarization-maintaining (PM) fiber in the input port [6]. High speed 12-bit A/D converter (GaGe, CompuScope 12100) sampled at 5 Msamples/s was used for data acquisition of two interference signals from the photodetector, and stored in personal computer. Optical path length change (Δp) in tissue can be calculated from the measured differential phase (ϕ0) and central wavelength of a broad-band light source (λ0: 1310 nm).
150
Δp =
λ0 Δϕ . 4π
(8)
After receiving the signal from the photodetector, two interference signals are bandpass filtered. Forward and reverse band-pass filtering was used for zerophase distortion and to eliminate noise from interferometric fringe data. After data processing, second order low pass Chebyshev type II digital filter was utilized to eliminate noise from optical path length change signal with a stopband ripple 20 dB down from the peak passband and with cutoff frequency 30Hz in Figure 2, and 4. Parameters were selected by examining the FFT transform on the basis of amplitude and phase response of optical path length change signal. Additional details of the DP-OCT setup and various biomedical applications have been reported [5, 6, 12]. 20X microscope objective was used to laser beam probe for specimens and transverse spot size was 4 um at the sample. The samples are positioned between two glasses (1 mm thickness) that was served as sample holder to avoid sample movement.
3
Results DP-OCT measurement was performed on iron laden macrophages taken
from liver, spleen, and a control in an isolated specimen under a highly focused magnetic field. When we applied a magnetic field oscillating at 3 Hz, 2 volt peakto-peak (Vpp) over a 1 second time period (Figure 1 (a)), optical path length
151
change (Δp) with and without a conical iron core are shown in (b) and (d), respectively. While the iron core was inserted into the solenoid, optical path length change (Δp) was about five times greater than without the core. The maximum magnetic flux density with the iron core was 0.43 Tesla and maximum tissue surface displacement was 156.53 nm after the Chebyshev type II digital low pass filtering with stopband ripple 20 dB down from the peak passband and with cutoff frequency 30Hz (Figure 1 (c)) due to excitation of SPIO nanoparticles. No distinguishable optical path length change (Δp) was observed in both control liver and spleen. Figure 2 shows frequency response of iron-laden liver was exactly twice (100 Hz, (b)) the modulation frequency (50 Hz, (a)), since the magnetic force is proportional to the product of the magnetic flux density and field-gradient as indicated in equation (2). To compare iron-laden liver with spleen samples, nanoparticle movement was measured by optical path length change (Δp) in Figure 3. Magnitude of optical path length change (Δp) in liver specimens was three times larger than that in iron-laden spleen; this result is consistent with a previous study [1] confirmed that concentration of iron in the liver 9 days after injection was approximately three times greater than that of spleen. In histological analysis (Figure 3 (B)), the Prussian blue stain identifies tissue based macrophages that represents Kupffer cells in the liver and spleen. The total SPIO uptake areas are 0.0211mm2 and 0.0073 mm2 of liver and spleen
152
in histology slides, respectively. The uptake area in liver image is approximately three times bigger than that of spleen. Therefore, tissue surface displacement measured by DP-OCT system was exactly corresponded to histology analysis. It may also be possible phase difference occurring due to mechanical properties of both liver and spleen; however tissue properties may not be dominant in this experiment.
4
Discussion Results of experiments described herein demonstrate that iron laden
macrophages in liver and spleen were both capable of responding to an applied high-strength focused magnetic field and measured by DP-OCT. Frequency response of iron-laden tissues was twice the modulation frequency since the magnetic force is proportional to the product of the magnetic flux density and field-gradient. These studies may be expanded to inflammation processes, which are known to be associated with monocyte infiltration and increased macrophage activity in high risk lesions [13, 14]. This macrophage activity suggests that SPIO nanoparticles should also be uptaken by macrophages in specific targeted lesions such as atherosclerosis [15, 16]. Macrophages are also considered an important marker to identify a weak fibrous cap and subsequent plaque rupture in cardiovascular disease. Moreover, activated macrophage cells may induce
153
increasing numbers of matrix metalloproteinases (MMP), which may rupture collagen comprising a thin fibrous cap. Imaging macrophages is of great interest and significant for identification of both hepatic disease and early stage inflammatory disease. Noteworthy is that SPIO nanoparticles have been explored for other applications such as MRI imaging of malignant lymph nodes of metastases in cancer [17], bone marrow [18], and brain tumors using high-resolution sonography [19]. The utilization of magneto-motive DP-OCT will be applicable to biomedical research in targeted drug delivery [20], magnetic bio-sensing [21], and magnetic separation [22] due to strong magnetic susceptibility. Magneto-motive detection technique have a potential for in vivo imaging applications, non invasive, and real time quantification combined by phase sensitive frequency domain OCT [23] and spectral domain phase microscopy [24] . Quantitative interpretation of optical path length change (Δp) with different dosages, variations in magnetic nanoparticles, and size of the nanoparticles will be required for further study using magneto-motive DP-OCT. In summary, the results of our experiments indicate magneto-motive DP-OCT is a candidate methodology to identify iron-laden tissue macrophages excited by an externally applied magnetic field.
154
Figure 1
Optical path length change (Δp) in livers (1.5 mmol Fe/kg dose)
using focused magnetic field excitation (3Hz 4Vpp) (a). Optical path length change with conical iron core (Δp = 167.13 nm, Bmax= 0.43 Tesla) (b), after the Chebyshev type II digital low pass filtering from optical path length change signal with conical iron core (Δp = 156.53 nm, Bmax= 0.43 Tesla), and without conical iron core (Δp = 35.4 nm, Bmax = 0.04 Tesla) (d). No displacement observed in control liver specimen (Δp = 11 nm, Bmax= 0.43 Tesla) (e).
155
Figure 2
Focused magnetic field excitation (50Hz, 4 Vpp, Bmax = 0.38 Tesla)
(a) and optical path length change (Δp) in iron laden liver (1.5 mmol Fe/kg dose) (b). (c) is the result of fast Fourier transform (FFT) of input magnetic field (50Hz modulation frequency), and (d) is the fast Fourier transform (FFT) of optical path length change (Δp) in (c).
156
157
Figure 3
Optical path length change (Δp) in liver and spleen (1.5 mmol
Fe/kg dose) using focused magnetic field excitation (8 Hz, 4 Vpp, Bmax = 0.5 Tesla) (A). Optical path length change (Δp) in iron laden liver (b) and spleen (d) using focused magnetic field. After Chebyshev type II digital low pass filtering of original path length change in liver (c) and spleen (d) with stopband ripple 20 dB down from the peak pass-band and with cutoff frequency 30Hz. Histological cross section of iron-laden liver and spleen with Prussian blue stain that identifies macrophages in histology images (B). Control specimen in liver (f) and spleen (h), and iron-laden liver (g) and spleen (i) by intravenous injection of SPIO nanoparticles (1.5 mmol Fe/kg body weight).
158
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VITA
Jung Hwan Oh was born in Pusan, Korea, on February 19, 1969, the son of Hyun-Gen Oh and Jung-Ja Kim. Jung Hwan graduated with special honors from Pukyung National University where he received a Bachelor of Science in 1992 and a Master Science in 1994 in Mechanical Engineering Department. He worked at the Research Center for Ocean Industrial Development (RCOID) in Korea from 1994 to 2000 as a senior researcher developing Nondestructive Testing (NDT) to inspect structures and materials using ultrasound, acoustic emission, eddy current and magnetic particle testing. During this period, Jung Hwan worked at Ulsan University as a lecturer in the Computer Engineering Department. In spring 2001, Jung Hwan entered the Graduate School at the University of Texas at Austin to pursue a Doctor of Philosophy. Jung Hwan earned his second masters degree in Biomedical Engineering in 2003. He has specialized in optical coherence tomography and ultrasound for molecular imaging under the supervision of Thomas E. Milner.
Permanent Address: 9955 Buffalo Speedway #1407, Houston, Texas 77054
This dissertation was typed by Jung Hwan Oh
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