NMR IN BIOMEDICINE
NMR Biomed. 2008; 21: 242–250
Published online 13 June 2007 in Wiley InterScience
(www.interscience.wiley.com) DOI:10.1002/nbm.1187
In vivo MRI using positive-contrast techniques in detection
of cells labeled with superparamagnetic iron oxide
nanoparticlesy
Wei Liu,1,3* Hannes Dahnke,2 E. Kay Jordan,3 Tobias Schaeffter2 and Joseph A. Frank3**
1
Philips Research Laboratories, Briarcliff Manor, NY, USA
Philips Research Laboratories, Hamburg, Germany
3
Experimental Neuroimaging Section, Laboratory of Diagnostic Radiology Research, National Institutes of Health, Bethesda, MD, USA
2
Received 26 March 2007; Revised 19 April 2007; Accepted 1 May 2007
ABSTRACT: Positive-contrast techniques are being developed to increase the detection of magnetically labeled cells in
tissues. We evaluated a post-processing positive-contrast technique, susceptibility-gradient mapping (SGM), and compared
this approach with two pulse sequences, a gradient-compensation-based ‘‘White Marker’’ technique and an offresonance-based approach, inversion recovery on-resonance water suppression (IRON), for the detection of superparamagnetic iron oxide (SPIO) nanoparticle-labeled C6 glioma cells implanted in the flanks of nude rats. The SGM, White
Marker and IRON positive-contrast images were acquired when the labeled C6 glioma tumors were 5 mm (small), 10 mm
(medium) and 20 mm (large) in diameter along the largest dimension to evaluate their sensitivity to the dilution of the SPIO
nanoparticles as the tumor cells proliferated. In vivo MRI demonstrated that all three positive-contrast techniques can
produce hyperintensities in areas around the labeled flank tumors against a dark background. The number of positive voxels
detected around small and medium tumors was significantly greater with the SGM technique than with the White Marker and
IRON techniques. For large tumors, the SGM resulted in a similar number of positive voxels to the White Marker technique,
and the IRON approach failed to generate positive-contrast images with a 200 Hz suppression band. This study also reveals
that hemorrhage appears as hyperintensities on positive-contrast images and may interfere with the detection of SPIO-labeled
cells. Published in 2007 by John Wiley & Sons, Ltd.
KEYWORDS: superparamagnetic iron oxide nanoparticles; cell labeling; positive contrast; susceptibility gradient
INTRODUCTION
Superparamagnetic iron oxide (SPIO) nanoparticles are
used to magnetically label cells ex vivo, providing
researchers with the ability to monitor the migration and
homing of these cells in vivo with MRI (1–3). Intracellular
SPIO nanoparticles placed in a magnetic field cause
signal dephasing because of the B0 inhomogeneities
induced near the cells. The disruption of the magnetic
field extends to a much larger distance than the actual size
*Correspondence to: W. Liu, Philips Research North America, 345
Scarborough Road, Briarcliff Manor, NY 10510, USA.
E-mail: [email protected]
**Correspondence to: J. A. Frank, Experimental Neuroimaging Section, Laboratory of Diagnostic Radiology Research, National Institutes
of Health, Building 10, Room B1N256, 9000 Rockville Pike, Bethesda,
MD 20892, USA.
E-mail: [email protected]
Contract/grant sponsor: NIH and Philips Research North America.
y
This article is a U.S. Government work and is in the public domain in
the U.S.A.
Abbreviations used: 1D, one-dimensional; 2D, two-dimensional; 3D,
three-dimensional; FFT, fast Fourier transform; FePro, ferumoxides
and protamine sulfate complex; GRASP, gradient echo acquisition for
superparamagnetic particles; IRON, inversion recovery on-resonance
water suppression; RF, radio frequency; SGM, susceptibility-gradient
mapping; SPIO, superparamagnetic iron oxide.
Published in 2007 by John Wiley & Sons, Ltd.
of the SPIO nanoparticles (4), making it possible to detect
single cells in vivo (5). On T2- and T2-weighted MR
images, SPIO nanoparticles appear as signal voids or
hypointense regions with associated blooming artifacts.
Therefore, differentiation between signal loss caused by
the intracellular SPIO nanoparticles and native low
signals in tissue is challenging. It has been suggested that
alternative approaches that result in positive contrast or
hyperintensities will improve the sensitivity for tracking
transplanted magnetically labeled cells within tissues.
Positive-contrast techniques produce images with
hyperintensities in the vicinity of SPIO nanoparticles.
Contrast enhancement based on the resonance frequency
shifts caused by the bulk magnetic susceptibility effects
was reported in 1990 by Xu et al. (6) for the paramagnetic
contrast agent, dysprosium triethylenetetraminehexaacetate. Recently, Cunningham et al. (7) achieved positive contrast using a spin-echo sequence with spectrally
selective radio frequency (RF) pulses to excite and refocus the off-resonant water in regions near the SPIOlabeled cells. As this method cannot be easily combined
with conventional slice selection, it acquires a positive
projection image of the SPIO-labeled cells. Stuber et al. (8)
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IN VIVO POSITIVE-CONTRAST MRI ON SPIO-LABELED CELLS
used spectrally selective RF pulses to pre-saturate on-resonant
water [inversion recovery on-resonance water suppression (IRON)] generating voxels with hyperintensities
from SPIO-labeled cells. Zurikya and Hu (9) used a
diffusion-mediated off-resonance saturation method to
obtain images with positive contrast. Bulk water protons
were imaged with and without the presence of an
off-resonance saturation pulse, and the positive-contrast
image was calculated as the difference image. Offresonance-based positive-contrast techniques allow the
generation of hyperintensities against a suppressed
background. A potential limitation of the off-resonance
positive-contrast techniques is that voxels with hyperintensities can be seen arising from endogenous areas (i.e.
lipids, areas of magnetic gradients, or other susceptibilityinduced off-resonance signals from hemorrhage or
calcium) that are also shifted in frequency from the
water proton. Moreover, off-resonance-based positivecontrast techniques are very sensitive to large-scale B0
field inhomogeneities.
Seppenwoolde et al. (10) reported a gradientcompensation-based approach (White Marker technique)
that used the local field inhomogeneities caused by the
paramagnetic marker. Positive contrast was achieved by
dephasing the background signal with a slice gradient. In
the region near the marker, the signal was conserved
because the induced dipole field compensated for the
dephasing gradient. A similar approach has been used for
imaging of SPIO-labeled cells and is known as gradient
echo acquisition for superparamagnetic particles
(GRASP) (11). The White Marker or GRASP technique
only compensates for the susceptibility gradients along
the slice direction.
The local magnetic gradients induced by an object with
magnetic susceptibility lead to an echo-shift in k-space
with gradient-echo imaging. As a result of this shift,
positive-contrast images can be derived from the
magnetic field map by applying different post-processing
techniques. Posse (12) extracted local phase information
by k-space filtering. Reichenbach et al. (13) produced
positive-contrast images by subtracting the complex
filtered image from the magnitude-filtered image or by
performing a one-dimensional (1D) fast Fourier transform (FFT) along the slice direction and selecting the
appropriate Fourier-encoded slice. Bakker et al. (14)
exploited the echo-shift by applying a shifted reconstruction window in k-space. The latter technique requires the
acquisition of a larger k-space and heuristic determination
of the reconstruction window. Recently, a susceptibilitygradient mapping (SGM) technique has been reported
that calculates the positive-contrast images from a regular
complex gradient-echo dataset (15). The local echo-shift
in a certain spatial direction is determined by 1D FFT over
a subset of neighboring voxels. The SGM method
generates a color map of the three-dimensional (3D)
susceptibility-gradient vector for every voxel by computing the echo-shifts in all three dimensions. The SGM is a
Published in 2007 by John Wiley & Sons, Ltd.
243
post-processing technique that does not require dedicated
positive-contrast pulse sequences, thereby providing the
flexibility to display susceptibility gradients or suppress
susceptibility artifacts in specific directions.
The proposed positive-contrast techniques have shown
improved contrast between labeled cells and the surrounding environment in phantom experiments (7–9,11) with
limited applications in vivo. In this study, we compared
the SGM positive-contrast technique with the White
Marker and IRON techniques in an experimental model of
SPIO-labeled C6 glioma tumors in the flanks of nude rats.
The SGM, White Marker and IRON positive- contrast
images were acquired at different stages of tumor
development to evaluate their sensitivity to the dilution
of the SPIO nanoparticles as the tumor cells proliferated.
The possible limitations of each of the techniques in
the detection of SPIO-labeled cells in vivo are also
presented.
METHODS
Positive-contrast techniques
Gradient-compensation techniques (e.g. White
Marker, GRASP). The White Marker sequence (10) is
illustrated in Fig. 1a. In a conventional gradient-echo
pulse sequence, immediately after the magnetic center of
the RF pulse, the slice selection gradient Gselect dephases
the spins within the slice. Normally, the 100% rephasing
gradient Grephase is used to compensate for the shaded
slice-selection area. Decreasing the amplitude of the
rephasing gradient creates a gradient imbalance effectively reducing the signal intensity from areas with
homogeneous B0. However, in locations where negative
local gradients, Gsuscep, caused by SPIO nanoparticles
within cells or other fields are present, the gradient
balance is restored, and a hyperintense signal is observed
against the dark background.
Off-resonance techniques (e.g. IRON). The IRON
pulse sequence (8) uses a spectrally selective saturation
pre-pulse with center frequency v0 and bandwidth
BWwater (Fig. 1b). Signals originating from on-resonant
protons are therefore suppressed, while off-resonant
protons in close vicinity to the SPIO nanoparticles are left
unaffected. The signal enhancement observed adjacent to
these SPIO nanoparticles occurs as a direct result of the
suppression of the on-resonant water protons and appears
as hyperintense areas on the IRON images.
Post-processing techniques (SGM). An object with
a magnetic susceptibility that deviates from its surrounding creates a local inhomogeneous magnetic field. The
local susceptibility gradient, Gsuscep, acts additionally to
the imaging gradients and leads to an echo-shift in
k-space for the signal that stems from the affected voxel
NMR Biomed. 2008; 21: 242–250
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W. LIU ET AL.
Gsuscep in x, y and z directions was determined for each
voxel separately by performing a 1D FFT over a subset of
n neighboring voxels in that direction. The position of the
maximum (echo-peak) of the n discrete Fourier components was found at a sub-voxel level by a quadratic fit.
The resulting 3D susceptibility-gradient vector represented the relative strength and direction of Gsuscep. By
assigning grey values to the strength of the susceptibility-gradient vector, a positive-contrast image was
generated. Alternative positive-contrast images were
created by assigning grey values to the strength of 1D
or two-dimensional (2D) susceptibility-gradient vectors
which represented susceptibility gradient in just one or
two dimensions, respectively. The positive-contrast images
were adapted to low- and high-susceptibility gradients via
a standard image level and window operation.
Phantom and animal preparation
Figure 1. (a) In conventional gradient-echo sequence, after
the magnetic center of the excitation RF pulse, the slice
selection gradient, Gselect, dephases the spins within the
slice. To rephrase the excited spins, the 100% Grephase
compensates for the shaded slice selection area. Reducing
Grephase creates a gradient imbalance, effectively resulting in
a signal decrease. However, in regions with a negative
susceptibility gradient, Gsuscep, the gradient imbalance, is
restored and the signal remains conserved, whereas other
regions will experience signal loss. (b) A spectral selective RF
pulse with center frequency v0 and bandwidth BWwater is
applied to saturate the on-resonance water. However,
signals originating from off-resonant protons are unaffected. (c) An object with a magnetic susceptibility that
deviates from the surroundings creates a local magnetic
gradient, Gsuscep, which leads to an echo-shift in k-space
with gradient-echo imaging. The SGM method determines
this echo-shift at every voxel in a certain direction by local 1D
FFT, which is used to determine the strength of the susceptibility gradient in that direction.
(Fig. 1c) (13). Gsuscep for a given voxel is proportional to
the echo-shift in k-space mx,y,z:
Gsuscp
x;y;z mx;y;z Gimaging
tx;y;z
x;y;z
TE
where tx,y,z represents the duration of the imaging
gradient. By measuring the shift, mx,y,z, a map of the
strength of the susceptibility-gradient vector can be
created that allows the depiction of the positive contrast
for every voxel (15).
Published in 2007 by John Wiley & Sons, Ltd.
C6 glioma cells (ATCC, Manassas, VA, USA) were
labeled with ferumoxides (Berlex Laboratories, Wayne,
NJ, USA) and protamine sulfate (American Pharmaceuticals Partner Inc., Schaumburg, IL, USA) (FePro)
complexes using procedures described previously (3).
Prussian blue staining was performed to confirm cell
labeling with SPIO nanoparticles. A phantom was made
from a cylindrical glass tube, 6 cm in diameter, filled with
distilled water. Three plastic vials with 1 106, 4 106
and 16 106 FePro-labeled C6 glioma cells suspended in
1 mL agarose gel were embedded in the middle of the tube
on a plastic rack. The cell doubling time for the C6 glioma
cell line was 2 days in culture.
All animal experiments were performed according to
the protocol approved by the Animal Care and Use
Committee at our institution. Six female nude rats (Harlen
Sprague Dawley nu/nu) were implanted subcutaneously
bilaterally in the flanks with 1 106 FePro-labeled and
unlabeled (control) C6 glioma cells. The animals were
imaged with MRI at different stages of their tumor
development to investigate the dilution effect of dividing
SPIO-labeled cells over 2 weeks. Owing to the availability of the MR scanner and the variations in tumor
growth, six rats were divided into three groups. Three rats
were imaged when their labeled tumors reached 5 mm
(small) and 10 mm (medium) in diameter along the
largest dimension. Two rats were imaged when their
labeled tumors reached 5 mm and 20 mm (large) in
diameter along the largest dimension. One rat was imaged
when its labeled tumor reached 10 mm and 20 mm in
diameter along the largest dimension. All rats were killed
after the second MRI scan, and tumors were removed and
fixed in 4% paraformaldehyde. Tumor sectioning for
histological analysis was preformed on 6 mm thick slices.
Tissue sections were stained with Prussian blue to
evaluate the distribution of SPIO-labeled cells and
counterstained with nuclear fast red.
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245
MRI
Calculation of number of positive voxels
Phantom experiment. MRI was performed on a 3 T
clinical MR scanner (Achieva; Philips Medical System,
Best, The Netherlands) using a dedicated 7 cm solenoid
receive-only RF coil (Philips Research Laboratories,
Hamburg, Germany). 3D gradient-echo images were
acquired with TR ¼ 17 ms, TE ¼ 15 ms, flip angle ¼ 208,
field of view ¼ 100 mm 100 mm, scan matrix ¼
256 256, reconstructed matrix ¼ 256 256, slice thickness ¼ 1 mm, number of excitations ¼ 2. Images were
saved as complex datasets. SGM positive-contrast images
were calculated directly from the complex 3D gradient
echo datasets. The post-processing was performed on a
PC with an in-house-built IDL software (ITT Visual
Information and Solutions, Boulder, CO, USA). White
Marker positive-contrast images were acquired with a
modified 2D multislice gradient-echo sequence to allow
manual control of the refocusing gradient: TR ¼ 395 ms,
TE ¼ 6.2 ms, flip angle ¼ 208, field of view ¼ 100 mm 100 mm, scan matrix ¼ 160 144, reconstructed matrix ¼
256 256, slice thickness ¼ 1 mm, number of excitations ¼
2 with 20% refocusing slice gradient. IRON positivecontrast images were acquired with a 2D multislice
spin-echo sequence using a spectral water saturation
inversion recovery pre-pulse with v0 ¼ 50 Hz, BWwater ¼
200 Hz and TR ¼ 845 ms, TE ¼ 9.4 ms, field of
view ¼ 100 mm 100 mm, scan matrix ¼ 160 144,
reconstructed matrix ¼ 256 256, slice thickness ¼
1 mm, and number of excitations ¼ 2.
Voxels were considered positive if their signal intensities
were more than three times the standard deviation of the
background. The number of positive voxels was calculated
within a region of interest that covered the SPIO- labeled
tumor. The region of interest was drawn on multiple slices
of the positive-contrast images to cover the whole tumor
volume and to include as few artifacts as possible.
In vivo experiment. MRI was also performed on the 3
T Achieva clinical MR scanner using the dedicated 7 cm
solenoid receive RF coil. Animals were anesthetized with
1.5–2% isofluorane and 100% oxygen delivered through a
nose cone. The heart rate and respiration rate were
monitored (MedRad LLC, Chicago, IL, USA). 3D
gradient-echo images were acquired with TR ¼ 18 ms,
TE ¼ 4.6 ms, flip angle ¼ 208, field of view ¼ 60 mm 60 mm,
scan
matrix ¼ 256 256,
reconstructed
matrix ¼ 256 256, slice thickness ¼ 1 mm, number of
excitations ¼ 4. SGM positive-contrast images were
calculated from the 3D complex gradient-echo datasets.
White Marker positive-contrast images were acquired
with a modified 2D multislice gradient-echo sequence to
allow manual control of the refocusing gradient:
TR ¼ 319 ms, TE ¼ 4.4 ms, flip angle ¼ 208, field of
view ¼ 60 mm 60 mm, scan matrix ¼ 256 231, reconstructed matrix ¼ 256 256, slice thickness ¼ 1 mm,
number of excitations ¼ 4 with no refocusing slice
gradient. IRON positive-contrast images were acquired
using a 2D multislice spin-echo sequence with spectral
water saturation inversion recovery pre-pulse v0 ¼ 50 Hz,
BWwater ¼ 200 Hz and TR ¼ 290 ms, TE ¼ 9.4 ms, field of
view ¼ 60 mm 60 mm, scan matrix ¼ 256 205, reconstructed matrix ¼ 256 256, slice thickness ¼ 1 mm, and
number of excitations ¼ 4.
Published in 2007 by John Wiley & Sons, Ltd.
Statistical analysis
Comparisons between two groups used two-tailed paired
Student’s t-test with equal variance. Differences among
three groups were analyzed by analysis of variance. All
measurements were presented as mean SD. Statistical
significance was determined at P < 0.05 after correction
for multiple comparisons.
RESULTS
Phantom
Fig. 2a is a photomicrograph of Prussian blue positive C6
glioma cells that were labeled with SPIO nanoparticles.
The phantom images in Fig. 3 were acquired towards the
bottom of the vials filled with 1 106, 4 106 and
16 106 SPIO-labeled C6 glioma cells in 1 mL gel. All
three techniques, the SGM, White Marker and IRON,
generated hyperintense voxels surrounding the three
vials, whereas they all appeared as dark spots on
T2-weighted images (Fig. 3a). With the SGM technique,
hyperintense regions were all around the vials representing the susceptibility gradients at the interface of the vials
and distilled water (Fig. 3b). The hyperintense voxels
from the White Marker and IRON techniques, however,
depended on the geometry of the dipole field induced by
the SPIO nanoparticles. The White Marker technique
only highlighted the negative lobes of the dipole resulting
in high signal intensities in small regions surrounding the
vials (Fig. 3c). In comparison, the positive-contrast
images from IRON produced both the positive and
negative lobes of the dipole that was induced by the vials
Figure 2. (a) Prussian blue-stained C6 glioma tumor cells
after SPIO labeling. (b) Prussian blue-stained tissue slice from
an SPIO-labeled tumor (left) and an unlabeled tumor (right).
Blue dots represent SPIO nanoparticles.
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W. LIU ET AL.
(Fig. 3d). The high concentration of SPIO nanoparticles
induced a fast signal decay, thereby resulting in
hypointense areas in the vials.
In vivo detection of SPIO-labeled cells
Figure 3. Positive-contrast images of the phantom with
T2-weighted (a), SGM (b), White Marker (c) and IRON (d)
techniques. Vials 1, 2 and 3 were filled with 1 106/mL,
4 106/mL, 16 106/mL SPIO-labeled C6 glioma cells,
respectively.
Highly concentrated SPIO-labeled C6 glioma
cells. Five rats were scanned when the SPIO-labeled
tumors were 5 mm in diameter along the largest
dimension. Fig. 4a shows an axial slice from a rat with
an SPIO-labeled tumor implanted on the flank using
T2-weighted imaging. The focal hypointense areas on the
flank (Fig. 4b) represented high concentrations of SPIO
nanoparticles in the implanted tumor cells or in the
daughter cells after a limited number of divisions. With
the SGM technique, hyperintense regions were detected
surrounding the focal hypointensities, clearly delineating
the tumor border as shown in Fig. 4c. In addition, there
were small areas of focal hyperintense regions within the
tumor, indicating a heterogeneous distribution of the
labeled cells containing SPIO nanoparticles because of
cell division. The White Marker (Fig. 4d) and IRON
(Fig. 4e) techniques also demonstrated hyperintense
Figure 4. Top row: Images were acquired when the SPIO-labeled tumor was 5 mm in diameter, representing highly
concentrated SPIO-labeled tumor cells (yellow circle). An axial slice of the rat (a) and zoom views of the labeled tumor with
T2-weighted (b), SGM (c), White Marker (d) and IRON (e) techniques. Middle row: Images were acquired when the
SPIO-labeled tumor was 10 mm in diameter, representing relatively diluted SPIO nanoparticles (yellow arrows). An axial
slice of the rat (f) and zoom views of the labeled tumor with T2-weighted (g), SGM (h), White Marker (i) and IRON (j)
techniques. Bottom row: Images were acquired when the SPIO-labeled tumor was 20 mm in diameter, representing
diluted SPIO nanoparticles (yellow arrows). An axial slice of the rat (k) and zoom views of the labeled tumor with
T2-weighted (l), SGM (m) and White Marker (n) techniques. The IRON technique failed to generate positive-contrast
images of the diluted SPIO nanoparticles.
Published in 2007 by John Wiley & Sons, Ltd.
NMR Biomed. 2008; 21: 242–250
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IN VIVO POSITIVE-CONTRAST MRI ON SPIO-LABELED CELLS
Table 1. Number of positive voxels from the SGM,
White Marker and IRON techniques for in vivo experiments. Values are mean SD
SGM
Small tumor
Medium tumor
Large tumor
a
1288 155
2584 177b
5137 1633
White Marker
IRON
330 130
2047 378
4514 1185
85 52
126 91
—
a
P < 0.01 versus White Marker and IRON.
P < 0.05 versus White Marker and IRON.
b
voxels in the area of the SPIO-labeled cells. However,
neither approach fully outlined the SPIO-labeled flank
tumor with hyperintense voxels. Unlike the positivecontrast images of the SGM and White Marker
techniques, lipids also appeared as voxels with high
signal intensities on the IRON images (Fig. 4e). For small
tumors, the number of positive voxels for the SGM
technique was significantly (P < 0.01) greater
(1288 155) than for the White Marker (330 130)
and IRON techniques (85 52) (Table 1).
Dilution of the SPIO-labeled C6 glioma cells in
growing tumor. As FePro-labeled C6 glioma flank
tumors increase in size, the concentration of SPIO
nanoparticles per tumor cell decreases. Four rats were
imaged when the flank tumors were 10 mm in diameter
along the largest dimension. As each cell may not divide
at the same rate in the flanks of the rats, T2-weighted
images were able to delineate areas of relatively high
concentration of SPIO-labeled cells appearing as
hypointensities within the tumor as well as regions in
the periphery in which the signal intensity of the tumor
was greater than the adjacent muscle (Fig. 4f). The
calculated SGM images contained areas of hyperintense
voxels (Fig. 4h) corresponding to the hypointense regions
on the T2-weighted images within the tumor (Fig. 4g).
The White Marker (Fig. 4i) and IRON techniques (Fig. 4j)
also generated hyperintensities in areas of relative high
concentration of SPIO-labeled cells. For flank tumors that
were 10 mm in diameter, the number of positive voxels
for the SGM was significantly (P < 0.05) greater
(2584 177) than for the White Marker (2047 378)
and IRON techniques (126 91) (Table 1). For the
resulting IRON image, the background suppression was
incomplete because of the field inhomogeneities with
the relatively narrow suppression band (Fig. 4j). While
the signal voids were obvious in the tumor on the
T2-weighted gradient-echo images, the use of positivecontrast techniques certainly led to explicit detection in
areas of the tumor appearing as the hyperintense regions.
Three animals were imaged when the flank tumors
reached 20 mm in diameter along the largest dimension.
The concentration of SPIO nanoparticles in dividing cells
had further decreased, and the nanoparticles had been
diffusely spread in the tumor mass. Fig. 2b shows
photomicrographs of a tissue slice from an SPIO-labeled
Published in 2007 by John Wiley & Sons, Ltd.
247
tumor with widespread Prussian blue positive spots and a
tissue slice from a control tumor free of Prussian blue
spots. T2-weighted images of the tumors that originated
from the SPIO-labeled C6 glioma cells had more diffuse
hypointense regions (Fig. 4l) and closely resembled the
tumors in the contralateral flank implanted with unlabeled
cells (Fig. 4k). The calculated SGM image (Fig. 4m) and
White Marker (Fig. 4n) images showed hyperintense
voxels in areas that corresponded to the low signal
intensities on T2-weighted images. However, the images
produced with the IRON pulse sequence failed to
generate any hyperintense voxels when tumors reached
20 mm in size (image not shown). There was no
significant difference in the number of positive voxels that
originated from large tumors for the SGM and White
Marker techniques (Table 1).
Artifacts with the SGM technique
On the SGM positive-contrast images, susceptibility
artifacts caused by other magnetic field inhomogeneities
such as air/tissue interfaces were also seen as hyperintense voxels around the tumors. These susceptibility
artifacts can be reduced on the SGM image by 1D or 2D
SGM. Fig. 5a is an axial T2-weighted image of a rat with
the SPIO-labeled tumor 10 mm in size. Hyperintense
voxels on the calculated SGM image were displayed in
the tumor containing SPIO-labeled cells (Fig. 5b) and in
areas with magnetic field inhomogeneities such as air/
tissue interfaces (red and yellow arrows). Fig. 5c is a 2D
SGM image containing the susceptibility gradients
within the axial plane (x, y). The susceptibility artifacts
near the edges of the tumor (red arrows) were reduced,
whereas the susceptibility artifacts induced by the gut
in the middle (yellow arrows) remained qualitatively
unchanged. This 2D SGM map showed that the
susceptibility artifacts near the edges of the tumor were
mainly in the through plane direction (z), whereas those
induced by the gut were mainly in the axial plane.
Calculating the susceptibility gradients only in the z
direction confirmed that the high-signal-intensity voxels
near the edges of the tumor were indeed in the slice
direction (Fig. 5d). 1D SGM maps can be created for
susceptibility gradients in any direction (Fig. 5e and 5f)
demonstrating the suppression of the susceptibility
artifacts in other directions.
Hemorrhage
Fig. 6a is a T2-weighted image of a control tumor
20 mm in size with a central hypointense region that
corresponded to a hemorrhagic region on histological
examination (data not shown). The area of hemorrhage
within the control tumor generated hyperintense voxels
on the SGM image (Fig. 6b) and White Marker image
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W. LIU ET AL.
Figure 5. Susceptibility gradients or artifacts can be selectively displayed or
suppressed by 1D or 2D SGM in specific directions. An axial slice of a rat with
the SPIO-labeled tumor 10 mm in diameter (a), and positive-contrast images
from SGM in all three dimensions (b), 2D SGM within the image (x, y) plane (c), 1D
SGM in z (d), x (e) and y (f) directions. Yellow and red arrows represent
susceptibility artifacts at air/tissue interfaces.
(Fig. 6c) similar to the hyperintense voxels that would be
displayed from the SPIO-labeled tumor cells in the
contralateral flank.
DISCUSSION
Positive-contrast techniques have shown promise in
improving the sensitivity of detecting and delineating
the presence of magnetically labeled cells within tissues.
Three different positive-contrast techniques (SGM, IRON
and White Marker) were evaluated in an experimental
flank tumor model. Implanting FePro-labeled cells into
the flanks of nude rats was used to simulate the
implantation of SPIO-labeled cells into target tissues.
Furthermore, as tumor cells proliferated, the SPIO
nanoparticles within a cell became diluted resulting in
a range of SPIO concentrations throughout the tumor
providing the opportunity to evaluate the sensitivity of
each technique over time. All three techniques were able
to depict the presence of the SPIO-labeled cells as
hyperintense voxels at different stages of tumor growth.
Compared with surrounding tissues in which the signal
intensity was suppressed, the hyperintensities observed
with the SGM, IRON and White Marker approaches
originating from regions containing labeled cells
appeared to provide a greater sensitivity than the
T2-weighted images. Moreover, the hyperintense regions
can be easily differentiated from other signal voids that
are seen on T2-weighted images (such as blood flow),
Figure 6. Hemorrhage appears as hyperintensities on positive-contrast images
and may interfere with the detection of SPIO-labeled cells. T2-weighted (a), SGM
(b) and White Marker (c) assessment of an unlabeled tumor with a hemorrhage
region in the middle (yellow arrows).
Published in 2007 by John Wiley & Sons, Ltd.
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IN VIVO POSITIVE-CONTRAST MRI ON SPIO-LABELED CELLS
249
Table 2. Summary of the salient features of three positive-contrast techniques
Special sequence
Extra scan
Major parameters
for optimal contrast
Sources of bright signals
Applicability of high
SPIO concentration
Applicability of low
SPIO concentration
Artifacts
SGM
White Marker
IRON
No
No
TE
Yes
Yes
Strength of slice rephasing
gradient and TE
Regions with negative
susceptibility gradient in
slice direction
Generates bright signals
partially around the ROI
depending on the geometry
Highlights SPIO nanoparticles
Yes
Yes
Center frequency v0 and
saturation bandwidth BWwater
Regions with off-resonance
frequency
Regions with
susceptibility gradient
Clearly delineates the ROIa
with bright
signals all around the ROI
Highlights SPIO
nanoparticles
Susceptibility gradient in
all three
dimensions or in certain
dimensions
(for 1D or 2D SGM)
Susceptibility in slice
direction
Generates bright signals
partially around the ROI
depending on the geometry
Failed
Large-scale field inhomogeneity
and off-resonance substance
such as lipid
a
ROI, Region of interest.
thereby providing a greater degree of certainty in the
determination of the location of the labeled cells.
Table 2 is a summary of the salient features of three
positive-contrast techniques evaluated in this study. The
SGM technique generated significantly more positive
voxels for small tumors than the White Marker and IRON
techniques. At this high concentration of SPIO nanoparticles, the hyperintensities generated from White Marker
and IRON techniques only partially covered the labeled
tumor, making definition of the region of interest difficult.
For medium tumors, the SGM also produced more positive
voxels than both the White Marker and IRON techniques.
For tumors 20 mm in size, the number of positive voxels
of the SGM was similar to that of the White Marker
technique, whereas the IRON technique failed to detect the
presence of SPIO-labeled cells.
A saturation bandwidth of 200 Hz was used for the
in vivo experiment for the IRON technique. Reducing
the saturation bandwidth would have increased the
detectability for this technique. However, a smaller
bandwidth would result in insufficient background
suppression (Fig. 4j). In this study, a standard Gaussian
suppression pulse was applied, which had a relatively
wide transition band. Use of a dedicated RF pulse for the
IRON technique should improve the balance between
detection of SPIO-labeled cells and sufficient background
suppression (7). No fat suppression was applied in the
present study so that it could be compared with the White
Marker and SGM techniques. Adding a fat suppression
RF pre-pulse to the IRON pulse sequences should result in
suppression of the lipid signals as seen in Fig. 4e. Another
approach for differentiating between fat and magnetically
labeled cells is to use the fact that fat resonates 3 ppm
away from water, whereas off-resonance effects due to
SPIO-labeled cells are shifted in both directions.
However, the sensitivity of IRON to labeled cells will
be decreased if only one direction is considered.
Published in 2007 by John Wiley & Sons, Ltd.
One potential limitation of the positive-contrast
techniques is the inability to distinguish SPIO-labeled
cells from hemorrhage within tissues. A recent study
suggested that off-resonance positive contrast was able to
distinguish SPIO-labeled cells from hemorrhage (16).
However, in the present study, hemorrhage in the control
tumors had similar hyperintense voxels on the SGM and
White Marker images to clusters of SPIO-labeled cells,
making it difficult to discriminate between the disparate
pathologies. Differentiation of SPIO-labeled cells from
adjacent areas of hemorrhage within the tumors is
dependent on the iron content in the region and will
require further investigation.
As positive-contrast images do not provide sufficient
anatomical information, it is necessary to combine
positive-contrast techniques with regular T2-weighted
imaging. Both the White Marker and IRON techniques
require special pulse sequence design; therefore extra
scans are required to obtain the anatomical reference
dataset. In contrast with these two approaches, the SGM
method is a post-processing approach, and the positivecontrast images can be derived from the T2-weighted
images. By calculating SGM maps in various combinations of dimensions, different susceptibility artifacts
can be selectively displayed or suppressed. The trade off
of using the SGM method with calculation of the
susceptibility gradients in 2D versus 3D is that the
sensitivity for detection of SPIO-labeled cells might be
reduced depending on the susceptibility gradients
induced by these cells.
The model of SPIO-labeled C6 glioma cells implanted
in the flanks of rats is an extreme condition for evaluating
positive-contrast techniques. SPIO-labeled cells were implanted subcutaneously, resulting in cells that were very
close to the skin surface such that imaging of the tumors
occurred at tissue/air interfaces. As the positive-contrast
techniques image the tissues surrounding the SPIO
NMR Biomed. 2008; 21: 242–250
DOI: 10.1002/nbm
250
W. LIU ET AL.
nanoparticles, this flank tumor model can exaggerate the
strength and weakness of each approach. As a result, the
White Marker and IRON techniques generated hyperintense voxels along a small portion of the labeled tumor
because the geometry of the dipole field induced by the
tumor did not mimic the typical geometry of a dipole field
as in the phantom experiment (Fig. 3). In the case of a
more homogeneous background such as myocardium (17)
or muscle (18), implanted SPIO-labeled cells should be
displayed as hyperintense voxels similar to what would be
expected in a phantom containing labeled cells on the
White Marker and IRON positive-contrast images.
2.
3.
4.
5.
6.
7.
CONCLUSION
In vivo MRI with the experimental SPIO-labeled tumor
model has demonstrated that the positive-contrast
techniques, SGM, White Marker and IRON, can increase
the detection of SPIO-labeled cells by generating
hyperintensities in areas surrounding the cells. As a
post-processing technique, the SGM method does not
need a special sequence and extra scans and provides the
flexibility to display susceptibility gradients or suppress
susceptibility artifacts in specific directions. However,
hemorrhage in tissue may appear as hyperintensities on
positive-contrast images, making it difficult to detect the
presence of SPIO-labeled cells in tissues with hemorrhages.
8.
9.
10.
11.
12.
Acknowledgements
The intramural research program of the Clinical Center at
the National Institutes of Health supported this research.
We also acknowledge Philips Research North America as
part of a cooperative research and development agreement for providing part of the support for this study. We
are grateful for the veterinary support provided by Mr
Juan Ventura and Mr Justin Ganjei. Finally, we thank Dr
Daniel Herzka for reviewing the manuscript and giving
valuable comments.
13.
14.
15.
16.
17.
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