ARTICLE
Mapping the microscale origins of magnetic
resonance image contrast with subcellular diamond
magnetometry
Hunter C. Davis
1
, Pradeep Ramesh
2
, Aadyot Bhatnagar
3
, Audrey Lee-Gosselin
1
, John F. Barry
4,5,6,7
,
David R. Glenn
4,5,6
, Ronald L. Walsworth
4,5,6
& Mikhail G. Shapiro
1
Magnetic resonance imaging (MRI) is a widely used biomedical imaging modality that derives
much of its contrast from microscale magnetic
fi
eld patterns in tissues. However, the con-
nection between these patterns and the appearance of macroscale MR images has not been
the subject of direct experimental study due to a lack of methods to map microscopic
fi
elds in
biological samples. Here, we optically probe magnetic
fi
elds in mammalian cells and tissues
with submicron resolution and nanotesla sensitivity using nitrogen-vacancy diamond mag-
netometry, and combine these measurements with simulations of nuclear spin precession to
predict the corresponding MRI contrast. We demonstrate the utility of this technology in an
in vitro model of macrophage iron uptake and histological samples from a mouse model of
hepatic iron overload. In addition, we follow magnetic particle endocytosis in live cells. This
approach bridges a fundamental gap between an MRI voxel and its microscopic constituents.
DOI: 10.1038/s41467-017-02471-7
OPEN
1
Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
2
Division of Biology and Biological
Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
3
Division of Engineering and Applied Sciences, California Institute of Technology,
Pasadena, CA 91125, USA.
4
Harvard-Smithsonian Center for Astrophysics, Harvard University, Cambridge, MA 02138, USA.
5
Department of Physics,
Harvard University, Cambridge, MA 02138, USA.
6
Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.
7
Present address: MIT Lincoln
Laboratory, Lexington, MA 02420, USA. Hunter C. Davis and Pradeep Ramesh contributed equally to this work. Correspondence and requests for material
s
should be addressed to M.G.S. (email:
mikhail@caltech.edu
)
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1
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M
agnetic resonance imaging (MRI) is a widely used
biomedical imaging modality, with millions of scans
performed each year for medical diagnosis, human
neuroscience research, and studies in animal models. The con-
trast seen in MRI images is strongly in
fl
uenced by microscale
magnetic
fi
eld gradients in cells and tissues, produced by endo-
genous substances such as blood, cellular iron deposits
1
,
2
,or
molecular-imaging agents such as iron oxide nanoparticles
(IONs)
3
–
6
. The precise dependence of voxel-scale (~0.5 mm) MRI
contrast on the microscale magnetic
fi
eld has been a topic of
intense theory and simulation due to its importance for disease
diagnosis and contrast agent design
2
,
7
–
10
. These studies predict,
for example, that the spatial frequency of the local magnetic
fi
eld
can signi
fi
cantly impact the
T
2
relaxation rate of a tissue, and that
optimizing contrast agent size can maximize
T
2
contrast for a
given set of material and imaging parameters. However, despite
its signi
fi
cance for biological imaging, the relationship between
microscopic magnetic
fi
eld patterns in tissue and
T
2
relaxation
has not been studied experimentally due to a lack of effective
methods to map magnetic
fi
elds at the microscale under biolo-
gically relevant conditions.
Nitrogen-vacancy (NV) magnetometry is a recently developed
technique that enables the imaging of magnetic
fi
elds with optical
resolution using the electronic properties of
fl
uorescent NV
quantum defects in diamond
11
. The electronic structure of an NV
center forms a ground-state triplet, with the
m
s
=
±
1 states
separated from the
m
s
=
0 state by 2.87 GHz, making ground-state
spin transitions addressable by standard electron spin resonance
B
o
0.5 mm
MRI voxel
a
d
g
ef
bc
Magneto-
microscope
Magneto-
microscopy
Orthogonalization
axis rotation
NV diamond
MW
Laser
Tissue
Iron oxide
nanoparticle
y
x
z
Endosome
v
4
v
3
v
2
v
1
Identify local minima
Neighborhood fits
Microwave frequency (GHz)
Global fit (
R
2
= 0.97)
MRI-labeled cell
Magnetic field map
B
x
(
μ
T)
1
0
–1
B
1
(
μ
T)
B
2
(
μ
T)
B
3
(
μ
T)
1
0
3
2.8
2.75
R.F.
1
0.99
2.75
R.F.
1
0.99
2.75
R.F.
1
0.99
2.75
R.F.
1
0.99
2.95
3
2.8
2.95
3
2.8
2.95
3
2.8
2.95
–1
1
0
1
0
–1
–1
B
4
(
μ
T)
1
0
–1
–2
B
z
(
μ
T)
1
2
0
–1
B
y
(
μ
T)
0
0.5
–5
B
x
(
μ
T)
0
1
–1
–2
B
x
(
μ
T)
0
1
–1
–2
Fig. 1
Subcellular mapping of magnetic
fi
elds in cells labeled for MRI.
a
Schematic of subvoxel magnetic
fi
eld mapping using a NV magneto-microscope.
b
Illustration of a cell labeled with IONs and its expected magnetic
fi
eld pattern.
c
Bright-
fi
eld image of RAW 264.7 macrophage labeled with 200- nm IONs.
White arrows point to internalized IONs. A bright-
fi
eld imaging artifact also appears as black in the upper right corner of the cell.
d
Cartoon representation
of each NV orientation and the corresponding representative spectra from
fi
xed-cell experiments. The blue ball represents nitrogen and the red ball
represents the adjacent lattice vacancy. Highlighted peaks in each relative
fl
uorescence (RF) spectrum show the transition corresponding to each of the
four orientations.
e
Magnetic
fi
eld images of the
fi
eld projections along each of the four NV axes of macrophages 2 h after initial exposure to 279 ng ml
−
1
200- nm IONs.
f
Images in
e
converted via Gram
–
Schmidt orthogonalization and tensor rotation to
fi
eld maps along three Cartesian coordinates with the
z
axis de
fi
ned perpendicular to the diamond surface and the
x
axis de
fi
ned as the projection of the applied bias
fi
eld onto the diamond surface plane. The
y
axis is de
fi
ned to complete the orthogonal basis set.
g
Representative example of the procedure for dipole localization in cellular specimens. This procedure
comprises three steps:
fi
rst the local minima in the
fi
eld map are identi
fi
ed and ranked; next, in decreasing order of magnitude, the neighborhood of each
local minimum is
fi
t to a point dipole equation and the resulting
fi
eld is subtracted from the
fi
eld map to reduce the
fi
t-deleterious effect of overlapping
dipole
fi
elds; and
fi
nally, the results of these
fi
ts are used as guess parameters for a global
fi
t over the full
fi
eld of view. The
fi
t shown has a degree-of-
freedom-adjusted
R
2
of 0.97. Scale bars are 5
μ
m
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(ESR) techniques. The Zeeman energy difference between the + 1
and
−
1 states leads to the splitting of the 2.87 -GHz resonance
into two distinct energy levels, whose separation from each other
increases linearly with magnetic
fi
eld strength. Upon green laser
excitation (532 nm), the
m
s
=
±
1 states are more likely to undergo
non-radiative relaxation than the zero-spin state, so that
microwave-induced transitions from
m
s
=
0to
m
s
=
±
1 cause a
drop in NV
fl
uorescence. Thus, the local magnetic
fi
eld of an NV
center can be extracted from the optically reported ground-state
spin transition frequency. Diamonds densely doped with NV
centers make it possible to optically image this resonant transition
frequency over a wide
fi
eld of view, thus providing an Abbe-
limited image of the magnetic
fi
eld at the diamond surface
12
.NV
magnetometry has recently been used in proof-of-concept bio-
logical applications such as imaging the magnetic
fi
elds produced
by magnetotactic bacteria
13
, detecting magnetically labeled cancer
cells
14
, visualizing paramagnetic ions bound to cells
15
, and
measuring magnetic
fi
elds produced by neuronal action
potentials
16
.
Here, we establish a method that uses the unique capabilities of
NV magnetometry to study the connection between subcellular
magnetic
fi
elds and MRI contrast. Doing so requires adapting NV
magnetometry for high-sensitivity imaging of sparse magnetic
fi
elds in cells and tissues, developing methods to convert two-
dimensional (2D) NV data into the three-dimensional (3D) dis-
tribution of magnetic
fi
eld sources, and simulating the behavior of
nuclear spins in the resulting magnetic
fi
elds. In addition, mon-
itoring the evolution of magnetic
fi
elds in live cells requires
operating under nondamaging optical and thermal conditions
with reduced available signal. In this work, we address these
challenges to enable the mapping of subcellular magnetic
fi
elds in
an in vitro model of macrophage iron oxide endocytosis and
histological samples from a mouse model of liver iron overload,
connecting both to MRI contrast.
Results
Mapping subcellular magnetic
fi
elds
. Our home-built NV
magneto-microscope (Fig.
1
a) was optimized for both high-
resolution magnetic
fi
eld imaging of
fi
xed samples and dynamic
imaging of living cells. By virtue of a relatively thick NV layer in
our diamond (~4
μ
m), we were able to signi
fi
cantly reduce the
applied laser power compared to shallower surface-implanted NV
diamond microscopes, while maintaining a strong NV
fl
uorescent
signal for rapid imaging. We used a total internal re
fl
ection
geometry to minimize phototoxicity
13
,
16
and bonded a silicon
carbide wafer to the diamond base to improve thermal dissipa-
tion
16
. For cell-imaging experiments, we applied a moderate bias
fi
eld (10 mT) to magnetize cell-internalized superparamagnetic
IONs. While a larger bias
fi
eld would increase the magnetization
of the sample, it would also produce stronger off-axis magnetic
fi
elds for each NV axis, which signi
fi
cantly reduces the sensitivity
of NV magnetometry
17
.
As a
fi
rst test of our method, we imaged the magnetic
fi
elds
resulting from the endocytosis of superparamagnetic IONs by
murine RAW 264.7 macrophages. Magnetic labeling and in vivo
imaging of macrophages are under development for a variety of
diagnostic and therapeutic applications
4
,
18
–
20
, which could
bene
fi
t from an improved understanding of the resulting MRI
contrast. In particular, although labeling is typically done with
dispersed particles of sizes ranging from a few nanometers to
several microns
21
–
23
, their internalization and subsequent
compaction by the cell (Fig.
1
b, c) could produce radically
different magnetic
fi
eld pro
fi
les
8
–
10
, which cannot be directly
observed by conventional electron microscopy or iron-staining
techniques. We performed vector magnetometry on
fi
xed
macrophages after incubating them for 1 h with 200 -nm,
multicore IONs and allowing one additional hour for inter-
nalization. After measuring the magnetic
fi
eld along each of the
four NV orientations (Fig.
1
d), we projected the
fi
eld maps along
0.5 mm
MRI voxel
Simulated signal
Fitted
T
2
decay
T
2
= 24.48 ms
Magnetically mapped cells
Monte Carlo simulation
Clustered
+IONs
–IONs
Diffuse
Clustered
Diffuse
Time (ms)
Norm. MRI signal
c
b
a
e
df
10
0
0
0.2
0.4
0.6
0.8
1
20 30 40 50 60 70
Experiment
Simulation
T
2
Relaxation time (ms)
T
2
Relaxivity (mM
–1
s
–1
)
0
10
20
30
Exp.
Sim.
0
10
20
30
Fig. 2
Predicted and experimental MRI behavior in cells.
a
Schematic of Monte Carlo modeling of spin relaxation using NV-mapped magnetic
fi
elds. A
library of 11 cells mapped with vector magnetometry (three representative cells shown) in a 1:1 mix with unlabeled cells, was used to randomly
fi
ll a 108-cell
FCC lattice with periodic boundary conditions and run a Monte Carlo simulation of spin-echo MRI to predict
T
2
relaxation behavior.
b
Representative
simulated MRI signal.
c
T
2
-weighted MRI image of cell pellets containing a 1:1 mixture of supplemented and unsupplemented cells (+ IONs and
–
IONs,
respectively) or 100% unlabeled cells (bottom).
d
Simulated and experimentally measured
T
2
relaxation times for the 1:1 mixture.
e
Illustration of the same
quantity of magnetic particles endocytosed or distributed in the extracellular space.
f
Simulated and experimentally measured relaxivity for endocytosed
and extracellular distributions of IONs. Measurements and simulations have
N
=
5 replicates. All error bars represent
±
SEM
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3
Cartesian axes convenient for magnetic dipole localization via
orthogonalization and tensor rotation (Fig.
1
e, f).
Connecting microscale
fi
elds to MRI contrast
. To connect
microscale magnetic
fi
eld measurements to MRI contrast, we
fi
rst
converted our 2D images to 3D maps of magnetic
fi
eld sources in
the sample, and then simulated the behavior of aqueous nuclear
spins in the corresponding 3D
fi
eld. To convert 2D vector maps
imaged at the diamond surface into a 3D model of magnetic
fi
elds
in cells above the diamond, we developed an algorithm for
iterative localization of magnetic dipoles (Fig.
1
g, Supplementary
Fig.
1
). First, the in-plane coordinates of putative dipole
fi
eld
sources (clusters of magnetic particles) were identi
fi
ed from local
minima in the
x
component of the vector
fi
eld, chosen parallel to
the projection of the bias
fi
eld onto the diamond surface. Then,
the off-diamond height (
z
) and magnetic moment of each cluster
were determined by
fi
tting the local dipole
fi
eld pro
fi
le. After
fi
tting the dipole at the strongest local minimum, the resulting
magnetic
fi
eld pattern was subtracted, and the next strongest local
minimum
fi
tted, with this process repeated until all local minima
were exhausted. A global
fi
t was then performed using the results
from the local
fi
ts as starting parameters. The degree-of-freedom-
adjusted
R
2
for all the global
fi
ts made to six representative
particle-containing cells was greater than 0.90. Magnetic locali-
zation of nanoparticle clusters was con
fi
rmed in a separate set of
cells using
fl
uorescently labeled nanoparticles (Supplementary
Fig.
2
). In addition, independent measurements of intracellular
iron concentration using inductively coupled plasma mass spec-
troscopy, 1.09
±
0.10 pg Fe per cell, corroborated the estimated
iron content inferred from NV measurements, which was 1.126
pg Fe per cell. The
fi
nal dipole values were scaled from the 10-mT
bias
fi
eld of the NV instrument to the 7 -T
fi
eld of our MRI
scanner using the bulk magnetization curve of the IONs (Sup-
plementary Fig.
3
, Supplementary Note
1
).
To translate subcellular magnetic
fi
eld maps into predictions
about MRI contrast, we performed Monte Carlo simulations of
nuclear spin
T
2
decoherence in lattices of representative cells.
These cells contained magnetic dipole distributions and magni-
tudes derived from NV magnetometry of a representative cellular
library (Fig.
2
a, Supplementary Fig.
4
). The resulting lattice
thereby contains information about the spatial frequencies of the
magnetic
fi
eld present in the pellet tissue, a critical parameter for
T
2
contrast. Importantly, since this information can be obtained
from NV measurements performed on a representative sampling
of cells or tissues, this obviates the need for NV evaluation of the
exact individual sample imaged with MRI, enhancing the
versatility of this approach.
Our simulation predicted a bulk MRI
T
2
relaxation time of
23.6 ms for a 1:1 mixture of supplemented and unsupplemented
cells (Fig.
2
b). Mixing was done to obtain a suf
fi
ciently long
T
2
for
accurate measurement with our MRI system. When compared to
an experimental MRI measurement of
T
2
in macrophages
prepared as in the NV experiment and pelleted in a 1:1 mixture
with unsupplemented cells, the Monte Carlo prediction was
accurate to within 2.8% (Fig.
2
c, d). The
T
2
relaxation time of the
cell pellets could not have been predicted solely from the
concentration of IONs in the sample, as previous simulations
have suggested a major in
fl
uence of packing geometry on contrast
agent relaxivity
8
–
10
. To establish that this relationship also holds
for our model system, we performed MRI measurements and
Monte Carlo simulations with IONs distributed in the extra-
cellular space (Fig.
2
e). Per iron mass, we found that this diffuse
extracellular arrangement produces approximately sixfold faster
T
2
relaxation than do endocytosed particles (Fig.
2
f), underlining
the importance of the microscale magnetic
fi
eld patterns mapped
with our method. Simulations of additional particle distributions
examine the relative in
fl
uence of particle clustering and
con
fi
nement inside cells and endosomes (Supplementary Fig.
5
,
Supplementary Note
2
).
Mapping magnetic
fi
elds in histological specimens
. To extend
this technique to diagnostic imaging, we performed NV magne-
tometry on liver specimens from a mouse model of hepatic iron
overload. The spatial distribution of iron deposits in the liver and
other tissues has been a topic of interest in clinical literature as an
indicator of disease state, including efforts to discern it non-
invasively using MRI
2
. Iron overload was generated through
intravenous administration of 900 -nm IONs to C57bl/6 mice
(Fig.
3
a). Livers were harvested 18 h after injection and imaged
with 7- T MRI, showing enhanced macroscale
T
2
relaxation
compared to controls (Fig.
3
b). To investigate the microscale
nature of this contrast enhancement, we cryosectioned the livers
of saline- and iron-injected mice and imaged the magnetic
fi
eld
pro
fi
les of these tissue sections on our NV magneto-microscope.
We measured the projection of the magnetic
fi
eld along a single
NV orientation, probing the
m
s
=
0to
m
s
=
+ 1 and
m
s
=
0to
m
s
=
–
1 transitions. The magnetic particle clusters were relatively
sparse, resulting in a punctate distribution of magnetic dipoles
within the liver tissue of the iron-overloaded mouse (Fig.
3
c,
Supplementary Fig.
6
). We con
fi
rmed that these magnetic
fi
elds
Liver
Iron
Saline
Iron
B
(
μ
T)
B
(
μ
T)
1
Fluorescence image
Fluorescence image
0.5
abcd
0
–0.5
–1
1
0.5
0
–0.5
–1
Fig. 3
Magnetometry of histological samples.
a
Diagram of mouse model of iron overload, prepared by injecting 10 mg kg
−
1
of 900 nm iron oxide
nanoparticles into the tail vein.
b
7T
T
2
-weighted MR image of
fi
xed, excised mouse livers from mice injected with IONs or saline.
c
NV magnetic
fi
eld maps
of 10
μ
m liver sections obtained from the mice in
b
.
d
Fluorescence images of the tissue samples in
c
. Fluorescence images were taken with autogain to
reduce the necessary exposure time, resulting in the visibility of the auto
fl
uorescence of the tissue in the saline control. Magnetometry scans were taken
with a
fi
xed gain. This experiment was repeated a total of three times, with data from two additional experiments shown in Supplementary Fig.
6
. Scale bars
in
b
and
c
–
d
are 5 mm and 10
μ
m, respectively
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resulted from IONs using
fl
uorescent imaging, for which purpose
the IONs were labeled with a
fl
uorescent dye (Fig.
3
d). These
results suggest that NV magnetometry could be used to map
subvoxel magnetic
fi
eld patterns within histological specimens,
increasing the diagnostic power of MRI by correlating magnetic
fi
eld distributions to disease state.
Magnetic imaging of endocytosis
. Finally, we tested whether NV
magnetometry could be used to follow the magnetic con-
sequences of the dynamic redistribution of magnetic material in
living mammalian cells. Macrophages endocytosing IONs go
through several stages of internalization, gradually recon
fi
guring
diffuse particles into compacted lysosomal clusters (Fig.
4
a). This
process could be relevant to interpreting MRI data from labeled
macrophages and to the development of clustering-based mag-
netic nanoparticle contrast agents
24
,
25
. To image living cells, we
adjusted our NV methodology to minimize optical and thermal
energy deposition. We subsampled the NV spectrum to probe
only the
m
s
=
0to
m
s
=
+ 1 transition of one NV orientation and
limited laser illumination to 5 min per image. This allowed us to
generate time-lapse images of magnetic
fi
elds coalescing inside
macrophages after ION internalization (Fig.
4
b, c, Supplementary
Fig.
7
), at the expense of precise 3D source localization, which
requires vector magnetometry using multiple NV orientations.
Cell viability (assessed via a Trypan Blue exclusion assay) was
approximately 90%. This technique for magnetic imaging of a
dynamic cellular process could aid the development of dynamic
contrast agents for MRI.
Discussion
In summary, this work establishes the capability of subcellular
NV diamond magnetometry to map microscale magnetic
fi
eld
patterns in mammalian cells and tissues and introduces compu-
tational methods to connect these patterns to MRI contrast. The
ability to make this connection experimentally will facilitate the
interpretation of noninvasive images through microscopic ana-
lysis of matching histological specimens, and aid the development
of magnetic contrast agents for molecular imaging and cellular
tracking. Alternative methods for magnetic measurement, such as
scanning superconducting quantum interference device (SQUID)
microscopy
26
,
27
and magnetic force microscopy
28
,
29
, are more
dif
fi
cult to apply to tissue-scale biological specimens due to the
need to raster scan samples, the spatial offsets required for
thermal insulation of SQUID magnetometers from biological
materials, and the need to penetrate samples with probe tips for
force microscopy. MRI itself can also be used at higher resolution
to examine ex vivo specimens, but does not typically approach the
single-micron level
30
,
31
. Meanwhile, methods such as electron
microscopy or iron staining, which can also reveal the in vitro
locations of putative magnetic materials based on their density or
atomic composition, contain no information about the magnetic
properties of such materials and their resulting
fi
elds, limiting the
utility of these methods to examining the distribution of known
magnetic
fi
eld sources.
Although the present study also used known particles to enable
direct experimental validation of our methods, NV magnetometry
can in principle be used to measure magnetic
fi
eld pro
fi
les arising
from unknown sources, such as biomineralized iron oxide. To
enable such measurements, NV imaging could be performed with
a variable, electromagnet-driven bias
fi
eld to
fi
rst map the loca-
tions of magnetic
fi
eld sources at low
fi
eld (where vector mag-
netometry is possible), and then apply a ramping
fi
eld along a
single NV axis to assess the
M
versus
H
behavior of each
fi
eld
source. Such in situ saturation curves would provide the infor-
mation needed to model MRI relaxation in samples with
unknown saturation behavior. Additional improvements in this
technique may be needed to reconstruct the location and mag-
netization of more diffuse magnetic materials that are less easily
detected as point dipoles.
The sensitivity of our current instrument, established by
computing the variance between three sequential magnetic
measurements of the identical sample, was 17 nT at 1 -
μ
m in-
plane resolution. This sensitivity corresponds to the
fi
eld pro-
duced by a 92 -nm particle situated 10
μ
m above the diamond
surface (assuming the same volumetric magnetization as the
IONs used in this study), or a 10 -nm particle located immedi-
ately on top of the diamond. This sensitivity was more than
suf
fi
cient to detect the 200-nm IONs used in our proof-of-
concept experiments. While these particles are within the size
range used in MRI contrast agents
21
–
23
, future work should focus
on improving the sensitivity of NV magnetometry and demon-
strating detection of smaller sources. Sensitivity could be
improved by employing diamonds with thinner NV layers, which
would allow detection of signi
fi
cantly smaller magnetic sources
near the diamond surface and would reduce the point-spread
function of NV-imaged magnetic
fi
elds, increasing the precision
of source localization. Combined with improved methods for
positioning tissue sections
fl
atter on the diamond surface, this
would allow the mapping of
fi
elds produced by smaller, endo-
genous magnetic inclusions and ultrasmall superparamagnetic
nanoparticles.
The study of microscale sources of
T
2
contrast could be
complemented by methods to map the concentrations of
T
1
contrast agents using alternating current (AC) NV magneto-
metry
15
. In particular, adapting this technique to measure the 3D
distribution of
T
1
agents inside of the cell using
Fusion
Trafficking
Endocytosis
Time (min)
120
130
140
150
160
170
180
190
200
210
10
5
0
–5
–10
–15
2 hrs
5 hrs
10 hrs
20
10
0
–10
–20
ab
c
B
(
μ
T)
B
(
μ
T)
Fig. 4
Dynamic magnetic microscopy in live mammalian cells.
a
Cartoon showing the typical progression of endocytotic uptake of IONs.
b
Bright
fi
eld and
series of time-lapse magnetic
fi
eld images of RAW macrophages over 10 h. Three additional replicates are shown in Supplementary Fig.
7
.
c
Bright
fi
eld and
series of time-lapse magnetic
fi
eld images of a RAW macrophage with 10 min between magnetic
fi
eld images. Two additional replicates of this experiment
are shown in Supplementary Fig.
7
. Scale bars are 5
μ
m
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5
nanodiamonds
32
,
33
could enable Monte Carlo modeling of
T
1
relaxation in contrast-labeled cells and tissues. In addition to
mapping the distribution of contrast agents and the resultant
magnetic
fi
elds, recent advances in NV magnetometry could
allow for in situ imaging of water-bound proton relaxation,
enabling a direct measurement of the effect of contrast agents on
the relaxation of surrounding water molecules
34
.
Besides contributing to the study of MRI contrast, the methods
presented for mapping magnetic
fi
eld sources in 3D from planar
optical data will enable biological imaging applications directly
using NV diamonds and magnetic labels. Because the optical
readout in this technique is con
fi
ned to the diamond surface, this
method can be used to study opaque tissues inaccessible to
conventional microscopy. To this end, our demonstration that
time-resolved wide-
fi
eld NV magnetic imaging can be performed
on living cells increases the utility of this technique for mon-
itoring dynamic biological processes.
Methods
Nitrogen-vacancy magneto-microscope
. The NV magneto-microscope was
constructed from a modi
fi
ed upright Olympus BXFM microscope and a 532 nm
laser source. The diamond used in this work is an electronic grade (
N
<
5 p.p.b.)
single crystal substrate with nominal rectangular dimensions of 4.5 mm × 4.5
mm × 500
μ
m, grown using chemical vapor deposition (CVD) by Element Six. The
top-surface NV sensing layer is measured to be 3.87
μ
m thick, consists of 99.999%
isotopically pure
12
C with 21.4 p.p.m.
14
N (3.77 × 10
17
cm
−
3
) incorporated into the
layer during growth. Layer thickness and nitrogen concentration were determined
by secondary ion mass spectroscopy. The diamond was irradiated with a 4.5 MeV
electron source with an irradiation dose of 9 × 10
18
cm
−
2
. The samples were sub-
sequently annealed at 400 °C for 2 h, 800 °C for 16 h, and 1200 °C for 2 h. This
diamond was af
fi
xed to a silicon carbide wafer (for enhanced heat dissipation),
which was in turn af
fi
xed to a pair of triangular prisms to facilitate a total internal
re
fl
ection excitation path. The prisms, silicon carbide wafer and diamond were
fused using Norland Optical Adhesive (NOA 71). The diamond assembly was
removable to allow live-cell culture on the diamond surface in a cell culture
incubator. Light was collected from the top of the diamond through a water-
immersion objective. Images were acquired on a Basler acA2040-180kmNIR
—
CMV4000 CCD camera with 2048 × 2040 5.5
μ
m pixels (we used 256 × 1020 pixels
to increase frame rate). For high-resolution vector magnetometry and tissue
imaging, NV
fl
uorescence was excited using a 100 mW Coherent OBIS LS 532 nm
optically pumped semiconductor laser. For live-cell imaging, we used an attenuated
2 W 532 nm laser from Changchun New Industries Optoelectronics. When
necessary, focal drift was adjusted for using a piezo-driven stage (Thorlabs).
Microwave radiation was applied through a single turn copper loop immediately
surrounding the diamond. The microwave signal was generated by a Stanford
Research Systems Inc. SG384 signal generator and ampli
fi
ed by a ZHL-16W-43-S
+ ampli
fi
er from MiniCircuits. Experimental timing was controlled by a National
Instruments USB 6363 X Series DAQ. A bias magnetic
fi
eld was generated by two
NeFeB grade N52 magnets (1
′′
×2
′′
× 0.5
′′
, K&J Magnetics) positioned on opposite
sides of the NV diamond. The NV setup was controlled by custom software written
in LabView.
Cell culture
. RAW 264.7 cells (ATCC) were cultured at 37 °C and 5% CO
2
in
Dulbecco
’
s Modi
fi
ed Eagle Medium (DMEM, Corning Cellgro) and passaged at or
before 70% con
fl
uence. For particle labeling, media was aspirated and replaced with
phenol red-free DMEM supplemented with 279 ng ml
−
1
IONs (200 nm Super Mag
Amine Beads Ocean Nanotech, MHA). After 1 h, the ION solution was aspirated
and cells were washed twice with phosphate buffered saline (PBS) to remove
unbound particles. For
fi
xed-cell magnetometry, the cells were trypsinized, quen-
ched with DMEM and deposited on the diamond surface at 40
–
70% con
fl
uency.
After 1 h incubation on the diamond under ambient conditions, the cells were
fi
xed
with 4% paraformaldehyde-zinc
fi
xative (Electron Microscopy Services) and
washed twice with PBS.
For live-cell imaging, the cells were cultured as above until trypsinization and
spotting on the diamond. Their media was supplemented with 0.1 mM ascorbic
acid to mitigate phototoxicity
35
. For extended imaging, the cells were maintained
on the diamond in DMEM supplemented with 10 mM HEPES to stabilize pH at 7.4
under ambient atmosphere.
Vector magnetometry
. The bias magnetic
fi
eld was aligned close to in-plane with
the diamond surface while having suf
fi
cient out-of-plane
fi
eld strength to resolve
the resonance of each NV axis, and the full NV optically detected magnetic
resonance (ODMR) spectrum was probed. The out-of-plane component was
necessary because a purely in-plane bias
fi
eld did not provide each NV axis with a
unique parallel
B
-
fi
eld, causing absorption lines to overlap. The microwave
resonance for each pixel in the image was set as the center of the middle hyper
fi
ne
peak of the transition. Spectra were swept at 0.5 Hz with 2000 images acquired per
spectrum (0.9 ms exposure time). Images were acquired with an Olympus 60×
water immersion objective (NA 1.0). Magnetometry spectra were acquired for 2 h
each. For a sub-set of measurements, this time was extended to 6 h to improve
signal-to-noise ratio (SNR).
Projection
fi
eld maps for each NV orientation were generated from the
corresponding peaks in the NV ODMR spectrum, and the background magnetic
gradient from the bias magnets (32
μ
Tmm
−
1
in a representative scan) was
subtracted out by
fi
tting the background to a 2D quadratic function and
subtracting the
fi
t from the signal. Projection
fi
eld maps were combined to form 3
orthogonal
fi
eld maps with
B
z
oriented normal to the diamond sensing surface.
B
x
is de
fi
ned as the projection of the applied
fi
eld onto the diamond plane and
B
y
is
de
fi
ned along the vector that completes the orthogonal set. Pixels were binned 2 × 2
in post-processing to boost SNR. This does not cause a signi
fi
cant reduction in
resolution, as the binned pixels in the object plane are 92 nm on a side, which
oversamples the Abbe limit of ~340 nm.
Live cell magnetometry
. For live cells, the bias magnetic
fi
eld was aligned such
that it was possible to resolve at least one NV resonance, and the magnetic
fi
eld
projection along a single NV orientation was probed using the
m
s
=
0
→
m
s
=
+1
transition. The microwave resonance for each pixel in the image was set as the
center of the middle hyper
fi
ne peak of the transition. While probing only one NV
transition allowed us to reduce the light dose to the sample while maintaining good
SNR, it also limited our information to a projection of the
fi
eld along one axis. This
limitation precludes the source
fi
tting performed on the
fi
xed samples. Spectra were
swept 10 MHz at 1 Hz with 200 images acquired per spectrum (4 ms exposure
time). In order to limit phototoxicity, each image was averaged for only 5 min and
the laser was shuttered for 5 min in between images, resulting in a 50% duty cycle.
Regions of interest were selected to include all relevant
fi
elds for a given cell.
Optical power density was ~40 W cm
−
2
. Images were acquired with a Zeiss 40×
near infrared water immersion objective (NA 0.8). Cell viability was assessed by
performing a Trypan Blue exclusion assay after NV measurements.
Intracellular iron quanti
fi
cation
. We performed inductively coupled plasma mass
spectrometry (ICP-MS) to independently con
fi
rm the intracellular iron con-
centration estimated by NV magnetometry. RAW 264.7 cells were cultured and
labeled with IONs as described above. After trypsinizing, the cells were counted
using a disposable hemocytometer (InCYTO C-Chip). The cells were then pelleted
at 400 g for 5 min, and the supernatant was aspirated. The cell pellet was
fi
rst boiled
in 2 mL of 70% nitric acid (ICP grade, Sigma) for 24 h to completely oxidize and
dissolve any intracellular iron. The dried residue was then resuspended in 2% nitric
acid and diluted 10-fold with deionized water for analysis using an Agilent ICP-MS
quadrupole spectrometer. Unsupplemented cells contained 0.21 + /
−
0.04 pg Fe per
cell. A procedural blank was included throughout the process to account for
background iron contamination (~34 p.p.b.), which was subtracted from measured
samples.
Field
fi
tting and dipole localization
. In-plane dipole coordinates were identi
fi
ed
as local minima in the
B
x
fi
eld map. Before localization, the
fi
eld map was spatially
low-passed (2D Gaussian
fi
lter with
σ
=
0.5 pixels) to eliminate noise-generated
local minima in the background. A pixel was identi
fi
ed as a local minimum if and
only if its
B
x
fi
eld value was smaller than all of its immediate neighbors (including
diagonals) in the spatially low-passed image.
Starting with the strongest local minimum, the measured magnetic
fi
eld in a
10 × 10 pixel (1.8 × 1.8
μ
m) square surrounding this minimum was
fi
tted to a point
dipole equation and averaged through the full NV layer depth (assuming uniform
NV density), with the magnetic moment, height off of the diamond, and dipole
orientation as free parameters.
B
x
ð
i
;
j
Þ¼
R
ð
z
þ
h
Þ
z
B
xo
i
′
;
j
′
;
b
;
M
;
θ
;
φ
ðÞ
d
b
h
where
B
xo
ð
i
;
j
Þ¼
μ
0
4
π
3
x
ð
M
r
Þ
r
5
M
^
x
r
3
Here
i
′
¼
i
i
0
ðÞ
and
j
′
¼
j
j
0
ðÞ
, where (
i
0
,
j
0
) are the in-plane coordinates of the
magnetic dipole,
θ
and
φ
correspond to the in-plane and out-of-plane angles,
respectively, of the point dipole orientation,
M
is the magnetic moment,
z
is the
height of the dipole over the diamond,
r
is the displacement vector,
^
x
is the unit
vector along the projection of the dipole axis onto the diamond surface plane,
x
¼
i
′
cos
θ
ðÞ
j
′
sin
θ
ðÞ
,
b
is a dummy variable for integration through the NV
layer, and
h
is the NV layer thickness. All parameters are free to
fi
t other than the
in-plane dipole coordinates, which are
fi
xed by the local minimum of the
B
x
fi
eld
map. While the
z
offset between the dipole and the diamond and the magnetic
moment of the dipole both affect the strength of the detected
fi
eld, they have
distinguishable effects on the resultant
fi
eld pattern. This is clear from the distinct
dependence of the dipole function on
M
and
z
(Supplementary Note
3
).
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After the strongest minimum has been
fi
tted, the
fi
tted
fi
eld from the
fi
t dipole
(within the full
fi
eld of view) was subtracted from the magnetic
fi
eld image, to
facilitate the
fi
tting of weaker dipoles. The 10 × 10 pixel neighborhood of the
second strongest dipole was then
fi
tted in the subtracted image. The
fi
tted
fi
eld was
subtracted, and the
fi
tting continued until the list of local minima had been
exhausted.
A global
fi
t was then performed using the results from the neighborhood
fi
ts as
starting parameters. The global
fi
t function is the sum of
N
dipoles (where
N
is the
number of local minima) with the in-plane dipole coordinates
fi
xed at the local
minima.
B
x
tot
i
;
j
ðÞ¼
X
q
B
x
q
ð
i
;
j
Þ
Here
q
is an index that runs from one to
N
and indicates the dipole
fi
eld source.
The precision of this technique is limited by the key assumption that the local
minima are not signi
fi
cantly shifted in the
x
–
y
plane by neighboring dipoles. The
degree of freedom-adjusted
R
2
for each of the four global
fi
ts in the cell library was
greater than 0.9. For 3 of the 6 labeled cells, with image acquisition time increased
from 2 to 6 h, the
R
2
was greater than 0.95. While this approach was able to
produce a suf
fi
ciently precise magnetic
fi
eld reconstruction to predict MRI
relaxation, other methods are also available for analytic dipole localization and
magnetic
fi
eld reconstruction
36
.
Fluorescent colocalization
. For
fl
uorescence colocalization, IONs were labeled at
their amino groups with Alexa 488-NHS (ThermoFisher Scienti
fi
c). Before label-
ing, nanoparticles were diluted to 1 mg ml
−
1
in 0.1 M sodium bicarbonate at pH
=
8.2. Alexa 488 dye was dissolved in dimethyl sulfoxide (DMSO) at 10 mg ml
−
1
and
added in 10 times molar excess to the nanoparticle surface amino groups. Fluor-
escent images were taken before the NV magnetometry commenced to avoid
photobleaching due to NV illumination. A 2-h vector magnetometry scan was then
performed for localization of magnetic
fi
eld sources. Alexa 488
fl
uorescent signal
was Wiener
fi
ltered to remove background speckle and then Gaussian blurred.
Local maxima of the Gaussian blurred image were designated the centroids of the
fl
uorescent signal. In one case, we were unable to establish a
fl
uorescent centroid
corresponding to a dipole that was visible on the NV magnetometry scan. Fitting of
this magnetic source predicted a magnetic moment corresponding to a single
nanoparticle, which may explain its weak
fl
uorescent signal.
Monte carlo simulations and cell library
. Nuclear spin relaxation was simulated
by assigning 11 representative cells from vector magnetometry to random positions
in a repeating face-centered cubic (FCC) lattice containing a total of 108 spherical
cells with periodic boundary conditions. The intracellular volume fraction of this
packing geometry is 74%. While spherical cells in a periodic lattice represent a
geometric simpli
fi
cation compared to real tissues, this and similar simpli
fi
cations
have been used previously to model diffusion in cell pellets and tissues
37
–
39
. Cell
size was set to match previously measured values for RAW 264.7 cells
40
. Water
molecules were randomly assigned initial
x
,
y
, and
z
coordinates in the lattice and
allowed to diffuse while their phase in the rotating frame evolved from
φ
(0)
=
0by
δφ
(
t
)
=
−
γ
B
x
(
x
,
y
,
z
)
δ
t
, where
B
x
(
x
,
y
,
z
) is the component of the local nanoparticle-
induced
fi
eld along the MRI bias
fi
eld. This phase step does not account for inner-
sphere effects from water coordinating to the nanoparticle surface, which will cause
rapid dephasing of water coordinated to the ION surface that cannot be refocused
by the pi pulses in the CPMG sequence. Re-focusing pulses were simulated at 5.5
ms Carr
–
Purcell time (11 ms echo time) by setting
φ
(
t
)
=
−
φ
(
t
−
δ
t
) Adjusting the
Carr
–
Purcell time can affect the determination of
T
2
. We used an 11 ms echo time
to match the echo time of our cell pellet MR measurements. The magnetic
fi
eld was
mapped within this 3D-volume using a
fi
nite mesh whose mesh size was inversely
proportional to the local
fi
eld gradient. If a water molecule moved within a distance
equivalent to six nanoparticle cluster radii of a cluster, the
fi
eld contribution from
that cluster was calculated explicitly. Background RAW cell relaxation was
accounted for by post-multiplying the simulated signal with an exponential decay
with time constant set to the measured relaxation rate of an unlabeled RAW cell
pellet. Cell membranes were modeled as semi-permeable boundaries with a per-
meability of .01
μ
mms
−
1
in accordance with previously measured values for
murine macrophage-like cells, adjusted to the temperature in our magnet bore
(12.9 °C)
41
. Intracellular and extracellular water diffusivity were set, respectively, to
0.5547 and 1.6642
μ
m
2
ms
−
1
in accordance with previous studies of cellular dif-
fusion
37
,
38
,
42
and established values for water diffusivity at 12.9 °C
43
, the tem-
perature of our scanner bore. Bulk spin magnetization in the sample was calculated
as
Mt
ðÞ¼
P
i
cos
½
φ
i
t
ðÞ
, where
i
is the index of simulated water molecules and the
magnetic moment of a single molecule is normalized to 1.
Nanoparticle clusters were modeled as spheres packed so as to occupy three
times the volume of their constituent nanoparticles, within the range of measured
literature values and grain packing theory
44
–
46
. To account for the increase in
nanoparticle magnetizations at 7 T compared to our NV bias
fi
eld, we scaled dipole
magnetization using a SQUID-measured curve (Supplementary Fig.
3
). Magnetic
dipole coupling effects between particles were neglected, as is valid for our average
cluster size and geometry. (See Supplementary Information for further discussion).
The data presented in the manuscript represents the output of
N
=
10 simulations,
each containing 20 random arrangements of cells and 2000 water molecules. The
number of trials was chosen such that the SEM for our simulations was smaller
than the SEM of our corresponding experiments.
To assess the impact of an alternative nanoparticle distribution (Fig.
2
e, f;
Supplementary Fig.
5
), we simulated the same 200 nm nanoparticles in the
arrangements indicated in the
fi
gures. The presented data comprises
N
=
10 simulations, each containing 20 random arrangements of particles and 2000
water molecules.
MR imaging and relaxometry
. Imaging and relaxometry were performed on a
Bruker 7 T MRI scanner. A 72 mm diameter volume coil was used to both transmit
and receive RF signals. To measure the
T
2
relaxation rate of RAW cells after
nanoparticle labeling, the cells were labeled identically to their preparation for NV
magnetometry, then trypsonized, resuspended in 10 mL DMEM and pelleted for 5
min at 350 g. DMEM was aspirated and cells were resuspended in 150
μ
L PBS. The
cells were mixed with an equal number of unsupplemented cells during resus-
pension in PBS to extend the
T
2
time of the
fi
nal pellet, improving the
fi
delity of the
T
2
fi
t. After transferring the cells to a 300
μ
L centrifuge tube, the cells were pelleted
for 5 min at 350 ×
g
. These tubes were embedded in a phantom comprising 1%
agarose dissolved in PBS and imaged using a multi-echo spin-echo (CPMG)
sequence (TR
=
4000 ms, TE
=
11 ms, 2 averages, 20 echoes, 273 × 273 × 1000
μ
m
voxel size).
T
2
relaxation was obtained from a monoexponential
fi
t of the
fi
rst 6
echoes. In order to establish the intrinsic
T
2
of RAW cell pellets for our Monte
Carlo simulations, we measured the
T
2
relaxation of 4 pellets of unsupplemented
RAW cells using the same parameters as above, except that, since the
T
2
was
signi
fi
cantly longer, we
fi
tted the
fi
rst 20 echoes. Fitting using only even echoes
produced the same results as
fi
tting all echoes (Supplementary Fig.
8
).
For the scenario in which nanoparticles are unclustered in the extracellular
space, unsupplemented RAW cells were pelleted and resuspended in PBS
supplemented with 100
μ
gml
−
1
IONs. This concentration was selected to ensure a
measurable
T
2
and allow both in silico and in cellulo comparisons between the per-
iron relaxation rates of extracellular and internalized particle scenarios. The validity
of a per-iron comparison was con
fi
rmed by previous studies of the linearity of
relaxivity for this size of iron oxide nanoparticles when unclustered
47
. To limit
endocytosis, cells were moved to the cold MRI bore and imaged immediately after
supplementation and pelleting. Imaging parameters were as described above.
Mouse model of iron overload
. Animal experiments were conducted under a
protocol approved by the Institutional Animal Care and Use Committee of the
California Institute of Technology. Female C57bl/6 mice were injected in the tail
vein with 10 mg kg
−
1
of dragon green labeled 900 nm ION (Bangs) or saline. A total
of three mice were used in this study. No randomization or blinding were needed
given the design of the study. Eighteen hours after injection, the mice were perfused
with 20 mL of 10% neutral buffered formalin, and their livers were collected for
MRI or NV magnetometry. MRI was performed on livers embedded in 1% agarose
using the 7T scanner described above, using a spin-echo pulse sequence with TR
=
2500 ms, TE
=
11 ms, 4 averages, and a 273 × 273 × 1000
μ
m voxel size. For NV
magnetometry, the liver was frozen in OCT embedding media and sectioned into
10
μ
m slices. Sections were mounted in on glass coverslips. We inverted the glass
cover slip and pressed the tissue sample against the NV diamond. Silicon vacuum
grease was applied at the edge of the cover slip (away from the diamond) to hold
the sample against the diamond. After this preparation was complete, PBS was
added to the dish to wet the sample. We performed
fl
uorescent imaging to locate
magnetic sources in the tissue. As the sources were sparsely distributed, the camera
was set to an autogain function to allow for short exposure time and rapid scan-
ning. The camera was set back to
fi
xed gain before NV imaging commenced. To
compensate for magnetic
fi
eld sources being further from the diamond due to
tissue thickness and/or folds in the sections, NV imaging was performed with a
strong (25 mT) bias
fi
eld applied along a single NV axis. This strong bias
fi
eld
served to increase the magnetization of the magnetic inclusions in the liver. As it
was applied along an NV axis, this bias
fi
eld did not signi
fi
cantly reduce the
contrast of the relevant ODMR spectral lines. However, such a strong bias
fi
eld
precludes the use of vector magnetometry. Future improvements to histological
sample preparation should increase the sample
fl
atness and bring the magnetic
material closer to the diamond surface, allowing for a lower bias
fi
eld and, as a
result, vector magnetometry and source localization. Images were acquired with a
Zeiss 40× near infrared water immersion objective (NA 0.8).
Software and image processing
. All
fi
ts and plots were generated in MATLAB.
Monte Carlo Simulations were performed in C + + on a Linux High Performance
Computing Cluster.
Statistical analysis
. Sample sizes were chosen on the basis of preliminary
experiments to have suf
fi
cient replicates for statistical comparison. Data are plot-
ted, and values are given in the text, as mean
±
S.E.M. Statistical comparisons
assumed similar variance.
Code availability
. All the relevant software scripts are available from the authors
upon request.
NATURE COMMUNICATIONS | DOI: 10.1038/s41467-017-02471-7
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(2018) 9:131
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DOI: 10.1038/s41467-017-02471-7
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7
Data availability
. All the relevant data are available from the authors upon
request.
Received: 15 April 2017 Accepted: 3 December 2017
References
1. Rouault, T. A. Iron metabolism in the CNS: implications for neurodegenerative
diseases.
Nat. Rev. Neurosci.
14
, 551
–
564 (2013).
2. Ghugre, N. R. & Wood, J. C. Relaxivity-iron calibration in hepatic iron
overload: Probing underlying biophysical mechanisms using a Monte Carlo
model.
Magn. Reson. Med.
65
, 837
–
847 (2011).
3. Corot, C., Robert, P., Idée, J.-M. & Port, M. Recent advances in iron oxide
nanocrystal technology for medical imaging.
Adv. Drug. Deliv. Rev.
58
,
1471
–
1504 (2006).
4. Weinstein, J. S. et al. Superparamagnetic iron oxide nanoparticles: diagnostic
magnetic resonance imaging and potential therapeutic applications in
neurooncology and central nervous system in
fl
ammatory pathologies, a review.
J. Cereb. Blood Flow. & Metab.
30
,15
–
35 (2010).
5. Kircher, M. F., Gambhir, S. S. & Grimm, J. Noninvasive cell-tracking methods.
Nat. Rev. Clin. Oncol.
8
, 677
–
688 (2011).
6. Shapiro, E. M., Sharer, K., Skrtic, S. & Koretsky, A. P. In vivo detection of single
cells by MRI.
Magn. Reson. Med.
55
, 242
–
249 (2006).
7. Vuong, Q. L., Gillis, P. & Gossuin, Y. Monte Carlo simulation and theory of
proton NMR transverse relaxation induced by aggregation of magnetic particles
used as MRI contrast agents.
J. Magn. Reson.
212
, 139
–
148 (2011).
8. Bowen, C. V., Zhang, X., Saab, G., Gareau, P. J. & Rutt, B. K. Application of the
static dephasing regime theory to superparamagnetic iron
‐
oxide loaded cells.
Magn. Reson. Med.
48
,52
–
61 (2002).
9. Gossuin, Y., Gillis, P., Hocq, A., Vuong, Q. L. & Roch, A. Magnetic resonance
relaxation properties of superparamagnetic particles.
Wiley Interdiscip. Rev.
Nanomed. Nanobiotechnol.
1
, 299
–
310 (2009).
10. Matsumoto, Y. & Jasanoff, A. T2 relaxation induced by clusters of
superparamagnetic nanoparticles: Monte Carlo simulations.
Magn. Reson.
Imaging
26
, 994
–
998 (2008).
11. Balasubramanian, G. et al. Nanoscale imaging magnetometry with diamond
spins under ambient conditions.
Nature
455
, 648
–
651 (2008).
12. Schirhagl, R. C. K., Loretz, M. & Degen, C. L. Nitrogen-vacancy centers in
diamond: nanoscale sensors for physics and biology.
Annu. Rev. Phys. Chem.
65
,83
–
105 (2014).
13. Le Sage, D. et al. Optical magnetic imaging of living cells.
Nature
496
, 486
–
489
(2013).
14. Glenn, D. R. et al. Single-cell magnetic imaging using a quantum diamond
microscope.
Nat. Methods
12
, 736
–
738 (2015).
15. Steinert, S. et al. Magnetic spin imaging under ambient conditions with sub-
cellular resolution.
Nat. Commun.
4
, 1607 (2013).
16. Barry, J. F., T., M. J., Schloss, J. M., Glenn, D. R., Song, Y., Lukin, M. D., Park,
H. & Walsworth, R. L. Optical magnetic detection of single neuron action
potentials using quantum defects in diamond.
Proc. Natl Acad. Sci. USA
113
,
14133
–
14138 (2016). arXiv:1602.01056.
17. Tetienne, J. P. et al. Magnetic-
fi
eld-dependent photodynamics of single NV
defects in diamond: an application to qualitative all-optical magnetic imaging.
New. J. Phys.
14
, 103033 (2012).
18. Daldrup-Link, H. E. et al. MRI of tumor-associated macrophages with
clinically applicable iron oxide nanoparticles.
Clin. Cancer Res.
17
, 5695
–
5704
(2011).
19. Zanganeh, S. et al. Iron oxide nanoparticles inhibit tumour growth by inducing
pro-in
fl
ammatory macrophage polarization in tumour tissues.
Nat.
Nanotechnol.
11
, 986
–
994 (2016).
20. Corot, C. et al. Macrophage imaging in central nervous system and in carotid
atherosclerotic plaque using ultrasmall superparamagnetic iron oxide in
magnetic resonance imaging.
Invest. Radiol.
39
, 619
–
625 (2004).
21. Tarulli, E. et al. Effectiveness of micron-sized superparamagnetic iron oxide
particles as markers for detection of migration of bone marrow-derived
mesenchymal stromal cells in a stroke model.
J. Magn. Reson. Imaging
37
,
1409
–
1418 (2013).
22. Shapiro, E. M. et al. MRI detection of single particles for cellular imaging.
Proc.
Natl Acad. Sci. USA
101
, 10901
–
10906 (2004).
23. McAteer, M. A. et al. In vivo magnetic resonance imaging of acute brain
in
fl
ammation using microparticles of iron oxide.
Nat. Med.
13
, 1253
–
1258
(2007).
24. Perez, J. M., Josephson, L., O
’
Loughlin, T., Hogemann, D. & Weissleder, R.
Magnetic relaxation switches capable of sensing molecular interactions.
Nat.
Biotechnol.
20
, 816
–
820 (2002).
25. Atanasijevic, T., Shusteff, M., Fam, P. & Jasanoff, A. Calcium-sensitive MRI
contrast agents based on superparamagnetic iron oxide nanoparticles and
calmodulin.
Proc. Natl Acad. Sci. USA
103
, 14707
–
14712 (2006).
26. Kirtley, J. R. & Wikswo, J. P. Jr Scanning SQUID microscopy.
Annu. Rev.
Mater. Sci.
29
, 117
–
148 (1999).
27. Finkler, A. et al. Self-aligned nanoscale SQUID on a tip.
Nano Lett.
10
,
1046
–
1049 (2010).
28. Hartmann, U. Magnetic force microscopy.
Annu. Rev. Mater. Sci.
29
,53
–
87
(1999).
29. Sidles, J. A. et al. Magnetic resonance force microscopy.
Rev. Mod. Phys.
67
, 249
(1995).
30. Moore, E. & Tycko, R. Micron-scale magnetic resonance imaging of both
liquids and solids.
J. Magn. Reson.
260
,1
–
9 (2015).
31. Deans, A. E., Wadghiri, Y. Z., Aristizábal, O. & Turnbull, D. H. 3D mapping of
neuronal migration in the embryonic mouse brain with magnetic resonance
microimaging.
Neuroimage
114
, 303
–
310 (2015).
32. Maclaurin, D., Hall, L. T., Martin, A. M. & Hollenberg, L. C. L. Nanoscale
magnetometry through quantum control of nitrogen
–
vacancy centres in
rotationally diffusing nanodiamonds.
N. J. Phys.
15
, 013041 (2013).
33. Kucsko, G. et al. Nanometre-scale thermometry in a living cell.
Nature
500
,
54
–
58 (2013).
34. Rugar, D. et al. Proton magnetic resonance imaging using a nitrogen
–
vacancy
spin sensor.
Nat. Nanotechnol.
10
, 120
–
124 (2015).
35. Wäldchen, S. L. J., Klein, T., van de Linde, S. & Sauer, M. Light-induced cell
damage in live-cell super-resolution microscopy.
Sci. Rep.
5
, 15348 (2015).
36. Mosher, J. C., Lewis, P. S. & Leahy, R. M. Multiple dipole modeling and
localization from spatio-temporal MEG data.
IEEE Trans. Biomed. Eng.
39
,
541
–
557 (1992).
37. Mukherjee, A., Wu, D., Davis, H. C. & Shapiro, M. G. Non-invasive imaging
using reporter genes altering cellular water permeability.
Nat. Commun.
7
,
13891 (2016).
38. Szafer, A., Zhong, J. & Gore, J. C. Theoretical model for water diffusion in
tissues.
Magn. Reson. Med.
33
, 697
–
712 (1995).
39. Imae, T. et al. Estimation of cell membrane permeability and intracellular
diffusion coef
fi
cient of human gray matter.
Magn. Reson. Med. Sci.
8
,1
–
7
(2009).
40. Hevia, D. et al. Cell volume and geometric parameters determination in living
cells using confocal microscopy and 3D reconstruction.
Protoc
.
Exch
.
https://
www.nature.com/protocolexchange/protocols/2264
(2011).
41. Loike, J. D. et al. Role of facilitative glucose transporters in diffusional water
permeability through J774 cells.
J. Gen. Physiol.
102
, 897
–
906 (1993).
42. Pfeuffer, J., Flögel, U., Dreher, W. & Leibfritz, D. Restricted diffusion and
exchange of intracellular water: theoretical modelling and diffusion time
dependence of 1 H NMR measurements on perfused glial cells.
Nmr. Biomed.
11
,19
–
31 (1998).
43. Holz, M., Heil, S. R. & Sacco, A. Temperature-dependent self-diffusion
coef
fi
cients of water and six selected molecular liquids for calibration in
accurate 1 H NMR PFG measurements.
Phys. Chem. Chem. Phys.
2
, 4740
–
4742
(2000).
44. Wilhelm, C., Cebers, A., Bacri, J. C. & Gazeau, F. Deformation of intracellular
endosomes under a magnetic
fi
eld.
Eur. Biophys. J.
32
, 655
–
660 (2003).
45. Aubertin, K. et al. Impact of photosensitizers activation on intracellular
traf
fi
cking and viscosity.
PLoS ONE
8
, e84850 (2013).
46. Huang, W., Liang, Y. Serial symmetrical relocation algorithm for the equal
sphere packing problem.
http://arxiv.org/abs/1202.4149
(2012).
47. Thorek, D. L. J. & Tsourkas, A. Size, charge and concentration dependent
uptake of iron oxide particles by non-phagocytic cells.
Biomaterials
29
,
3583
–
3590 (2008).
Acknowledgements
We acknowledge Arnab Mukherjee, George Lu, Vivek Bharadwaj, My Linh Pham,
Andrei Faraon, Geoffrey Blake, Joe Kirschvink, Manuel Monge, Hans Gruber, Michael
Tyszka, Russ Jacobs, and John Wood for helpful discussions. This work was supported by
the National Science Foundation Graduate Research Fellowship (P.R.), Caltech Center
for Environmental
–
Microbial Interactions (M.G.S.), the Burroughs Wellcome Fund (M.
G.S.), the NSF EPMD and PoLS programs (R.L.W.), and the U. S. Army Research
Laboratory and the U. S. Army Research Of
fi
ce under contract/grant number
W911NF1510548 (R.L.W.). Research in the Shapiro Laboratory is also supported by the
Heritage Medical Research Institute, the Pew Scholarship in the Biomedical Sciences and
the David and Lucile Packard Fellowship for Science and Engineering.
Author contributions
H.C.D., P.R. and M.G.S. conceived and planned the study with input from J.F.B., D.R.G.
and R.L.W. H.C.D., P.R. and J.F.B. constructed the magneto-microscope. H.C.D. per-
formed the NV magnetometry experiments and analyzed the resulting data. H.C.D., P.R.
and A.L.-G. prepared the in vitro and in vivo specimens. P.R. and H.C.D. performed the
MRI measurements and analyzed the resulting data. H.C.D. and A.B. developed and
ARTICLE
NATURE COMMUNICATIONS | DOI: 10.1038/s41467-017-02471-7
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NATURE COMMUNICATIONS
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DOI: 10.1038/s41467-017-02471-7
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performed the Monte Carlo simulations. H.C.D., P.R. and M.G.S. wrote the manuscript
with input from all other authors.
Additional information
Supplementary Information
accompanies this paper at
https://doi.org/10.1038/s41467-
017-02471-7
.
Competing interests:
The authors declare no competing
fi
nancial interests.
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