Neuroradiology Brigitte
Poncelet,
P.
Brain with
(MR)
measured
tion
imaging, the
of brain
sitive,
J.
Van
#{149}
intrinsic
pulsatile
parenchyma.
mo-
Phase-sen-
two-dimensional
planar
cine
throughout a spin-echo,
MR
pulse
images
were
the cardiac cycle blipped echo-
sequence.
Trans-
verse and coronal planes were obtamed in 14 healthy volunteers. Corrections were made for gross head
motion.
Brain
motion
consisted
of a
rapid displacement in systole, with slow diastolic recovery. The motion occurred chiefly in the cephalocaudal
a
and lateral directions; the anteroposterior motions were relatively small. Cephalocaudal velocities increase with
proximity
num.
The
to the
lateral
foramen
motion
mag-
is mainly
compressive motion of the Brain parenchymal velocities high as 2 mm/sec caudally
a
thalami. were in the
as
brain stem and 1.5 mm/sec medially in the thalami. Net parenchymal excursions were at most 0.5 mm. Phasebased echo-planar velocity measurements agreed well with echo-planar Fourier velocity zeugmatography measurements and were consistent with reported values. Velocity mapping with echo-planar imaging offers
a rapid
and
flexible
ing the pulsation man brain.
method velocities
of several techniques, including phase contrast (5,6), Fourier velocity zeugmatography (FVZ) (7,8), and image mnterferography (9). We present a method to map CNS velocity components by using spin-echo echo-planar
MR
imaging,
which
of assess-
the
fluid, MR. (MR), cine (MR), echo planar
representation of the (3D) dynamics of
AND
METHODS
2D sensitivity
echo-planar
image.
is created
by
incorpo-
1992; 185:645-651
From the MGH-NMR Center, Department of Radiology, 13th St. Charlestown, MA 02129. Received December 27, 1992; final reyision received June 30; accepted July 6. Supported GE Medical Systems, and Advanced NMR Systems. Address ‘ RSNA, 1992 See also the article by Enzmann and PeIc (pp 653-660) and this issue.
S. Cohen,
PhD
rating ing
a pair pulse
of unipolar
gradients
velocity-sensitiz-
along
a chosen
direc-
lion into an MR spin-echo pulse sequence (11). This spin-echo sequence allows us to measure slow motion by using long, velocity-sensitizing, gradient pulses without extensive T2* decay, a potential source of limitation in gradient-echo techniques.
Data
Acquisition
All imaging was performed with a 1.5-T Signa imager (GE Medical Systems, Muwaukee) retrofitted with Instascan technology (Advanced NMR Systems, Wilmington, Mass). The imaging pulse sequence was a blipped echo-planar acquisition (12,13) augmented by a pair of unipolar velocity-sensitizing gradient pulses placed before and after the 180#{176} radio-frequency pulse (Fig 1). The yeloc-
ity-sensitizing gradient either the section-select
was applied
along
axis (ie, throughplane motion) or the phase-encoding axis (in-plane motion); amplitudes were 0.11.0 C/cm (0.1-1.0 x 10 T/cm); gradient pulse duration, 8, was 20-40 msec; and the time interval between gradient pulses, , was 23-46 msec (total motion-encoding duration, + 8 = 43-86 msec). These pulses provided velocity sensitivities of 0.7-5.0 radians . mm sec. The velocity sensitivity, K, was made as large as possible, consistent with the re-
quirement not wrap;
that the measured that
is, p
=
K
phases,
V must
p,
satisfy
I’ I
< rr radians at all points. Thus K < radians/V,,), where Vma. 5 the maximum velocity to be imaged. The full expression of ip shows (see Appendix) that the measured phase corresponds to an average measurement of velocity over the duration of the total motion encoding + b. Acquisition parameters were as follows: echo time of 80-120 msec, acquisilion matrix of 64 x 128, in-plane resolution of 3 x 3 mm, and section thickness of 5-10 mm. The sequence was electrocardiography (ECC) gated; an image was collected every one to four R-R intervals with (IT
Our basic technique for brain motion measurement is to analyze a velocity-dependent phase map obtained from a yeVelocity
149,
to
CNS.
locity-sensitized
Radiology
can be used
acquire a two-dimensional (2D) image in less than 0.1 second (10). These rapid rates of acquiring echo-planar imaging data facilitate acquisition of more extensive data sets, offering a
of the
Mark
#{149}
Measurement Imaging’
the rigid cranium, blood, cerebrospinal fluid (CSF), and brain tissue engage in a complex and imperfectly understood three-dimensional (3D) motion. Although different proposed models represent brain motion as the “circulation pump” of the CSF (1,2), direct validations of these models in the human brain have been limited. Because derangements of central nervous system (CNS) dynamics may play an important role in a variety of diseases (3,4), a better understanding of the dynamics of normal CNS is required. As several recent reports have mdicated, magnetic resonance (MR) imaging allows detection and measurement of motion throughout the CNS precisely and noninvasively by means
MATERIALS Index terms: Cerebrospinal 10.1214 #{149} Magnetic resonance study #{149} Magnetic resonance
PhD
ITHIN
more complete three-dimensional
hu-
M. Weisskoff,
#{149} Robert
Motion: MR
W
magnetic resothe authors
electrocardiography-gated,
acquired by using
MD
Wedeen,
Parenchyma Cine Echo-Planar
With echo-planar nance
MS
Massachusetts General Hospital, Bldg 1991; revision requested February 12, in part by NIH grant no. 5RO1HC3937, reprint requests to B.P.P. editorial
by Feinberg
(pp
630-632)
in
Abbreviations:
CNS
=
central
nervous
system,
CSF = cerebrospinal fluid, ECG = electrocardiography, FVZ = Fourier velocity zeugmatography, 3D = three-dimensional, 2D = two-dimensional.
645
1. Blipped echo-planar Instascan (Advanced NMR Systems) spin-echo pulse sequence. The readout gradient (G-Readout) is a resonant gradient producing a train of 64 echoes, one every 500 sec, applied in combination with the “blipped” gradient in the phaseencode direction, for a 2D single-shot acquisition (12,13). An auxilFigure
iary
motion-encoding
gradient,
of duration
8, is applied
along
either
the section-select direction (as shown) or one of the in-plane direclions. The total motion-encoding duration is + b. This velocityencoding gradient is applied either in a single polarity for each image (solid boldface line) or with alternating polarities for pairs of images (solid boldface and dashed lines). RF = radio frequency.
G-Readout
RJ.Jii A
a cardiac
delay
by 50 msec
progressively
per
image,
G-22LflJLfL
incremented
for 25 images.
Typi-
cally, the delay range spanned two full cardiac cycles. Depending on technique (see below), one or two image series were obtained, with either a single-polarity velocity encoding (Fig 1, solid boldface line) or an interleaved acquisition with alternating positive and negative polarities (Fig 1, solid boldface and dashed lines). The total data acquisition limes were from 20 seconds to 3 minutes. For studies of cephalo-
caudal
and anteroposterior
velocity,
the
subject was positioned supine in the head coil, with restraint to reduce head motion.
Due to system
limitations,
repositioned
subjects
in a 90#{176} lateral
position
for studies
were
Motion
observed
phase
in each
Cp1[x,yJ=
where
image:
pj[X,y]
-
p[x,yJ/N,
(1)
is the
ith phase image after correction, Pi[X,Y] S the ith phase image, and i = 1, . . N, where N is the total number of phase data collected over the car[X,y]
.,
diac cycle. ages 1[X,y]
Each of the
corrected
phase
im-
is purged of all phase terms that are constant over the image series (5,16). The simple methodology embodied
decubitus
of the mediolateral
velocity.
Equation (1) is applicable provided that the image phases do not wrap; more cornplex methods are required if phase wrap is in
Phase
Corrections
The phase
of the reconstructed
image
data reflects the velocity of the brain tissue at each pixel, but also contains additive phase errors of several types that must be
removed to isolate the velocity-dependent phase shifts. Two methods were investigated to remove such phase errors. (We shall abuse notation and refer to phase and velocity interchangeably, recaffing that phase p = K V for a constant of sensilivity K in each experiment [14].) .
Method
1 : phase
subtraction-Subtracting
the phase of pairs of images collected with velocity-encoding gradient pulses of opposite polarities cancels constant phase errors and isolates the motion-specific phase terms (15): (j = (p1f ‘P1’ where and p denote the velocity encodings of
_
the respective signs for the ith phase image and (j S the final phase-subtracted image. The phase-subtraction technique assumes that the brain motion is periodic, so that the same sequence of velocity dis-
tributions is played out in each heartbeat. It also assumes that the velocity-sensitizing gradient substantial Method
Unlike has
pulse does not itself cause phase errors. 2: cycle mean phase correction.-
blood
and CSF, solid brain
no net translation:
over one cardiac
cycle
Its average
must
tissue velocity
be zero.
This
principle allows us to correct any timeconstant phase errors, such as those of magnetic field variation or radio-frequency phase dispersion. At each pixel, compute the mean phase over the cardiac cycle and subtract this mean from the
we 646
Radiology
#{149}
present.
Data Processing: Compensation To identify
the motion
five to the skull, skull
Head
Motion of the brain
the rigid
is measured
and
motion
rela-
of the
subtracted
from
the
parenchyma velocity maps. A vector component of the motion of a rigid body
brain
(translation
plus
function L1[x,y]:
of the L1[x,yJ
where
the rates
x,y
rotation) image
=Ax
must be a linear coordinates,
+ By
of translation
+ V0,
Encoding
Gradients
of the ith lime point. This procedure removes the instantaneous contribution of rigid head motion on a frame-by-frame basis. This is not a substitute for immobilization of the head, since internal brain motions (“sloshing”) may be induced by rigid accelerations, particularly rotation, of the head. This procedure also corrects echo miscentering in k space, accomplished in other cases with the aid of stationary reference phantoms. The effect of this head motion compensation on observed parenchymal motion is illustrated
for
two
different
regions
(Fig
2).
Cephalocaudal velocity curves are shown for a frontal pole region (Fig 2a) and for a deep gray region (Fig 2b). The curves represent the computed, rigid motion at the selected locations, as well as the brain yelocity before and after rigid motion correclion. Cerebral periphery velocities (Fig 2a) are seen to be correlated strongly to the head motion and are reduced substanlially after correction. By contrast, the yelocities of the central structures appear less strongly correlated with the rigid head motion.
(2)
RESULTS
and rotation
determine the constant V0 and the rotalion rate determines the constants A and B. The values of V0, A, and B could be fixed by determining the value of V at three locations, but it is preferable from a signalto-noise standpoint to measure V, at a
This
study
volunteers years).
examined
of both Informed
14 healthy
sexes
(aged
consent
was
20-40 ob-
large set of points and to solve for the coefficientrmn Equation (2) by a linear least-
tamed according to the Subcommittee on Human Studies guidelines at our institution. Single or multiple axial and/or coronal images were obtained.
squares
In total,
fit. In practice,
we have typically 150 points in the scalp, which we assume moves with the skull and which furnishes a readily identifled MR signal. For adequate skin signal, we used four R-R intervals for repetition
measured
V at
and
about
cording
L1[x,y],
locity
at each
where and
point:
V[x,y]
=
V[x,y]
V[x,y] is the corrected yeV1[x,y] is the observed velocity
series
to section
were
collected
in Table
1 ac-
orientation,
section
acquisition mode, and velocity ponent measured (cephalocaudal, anteropostenor, or mediolateral).
time and 1.0 cm for section thickness. To find the rigid motion corrected velocity for each lime frame, a linear-fit function is subtracted from the observed velocity
84 cine
are summarized
Brain -
Motion
com-
Observations
Figure 3 shows a typical, throughplane motion study. By using the phase-subtraction
technique,
a cine
December
1992
Cephalic
Cephalic
I
At 0
(C
a) C’,
a)
E E
E E
>‘
>‘
U)
0
(C
0 a,
0
a)
>
-0.5
>
-
\.
.
Caudal
‘I
#{149}
0
.
Ii
“1’
-1
100
200
300 Delay
.
from
400 A-wave
500
600
Caudal
700
0
100
200
(msec)
300
400
500
Delay from R-wave
a.
600
700
(msec)
b.
Figure
2. Head motion (b) in a deep gray region.
(El) head
motion
correction For each
correction,
and
at the region,
the local
periphery and center. Time three velocity-time curves
head
motion
(U) derived
curves for correspond
from
cephalocaudal to the measured
the linear
velocities measured (a) in the parenchymal velocity, with
fit, computed
at these
I
frontal brain and (0) and without
locations.
Figure
3.
Phase
subtraction
cine study
level man.
of the basal A magnitude
vals/90
ganglia image
[repetition
time
indicate
ECG
gate
at the
in a 37-year-old (four R-R intermsec/echo
time])
at top left, followed by 14 images caudal velocity covering a cardiac times
of ye-
head-motion-corrected, cephalocaudal locity imaged in a transverse plane
delays
is
of cephalocycle. from
the
The R
wave. The velocities are shown in gray-scale representation, ranging over ±2 mm/sec. Darker shades correspond to caudal velocities,
and
zero
velocity
lighter
shades,
is medium
to cephalic
velocities;
gray.
image frames
at top left; the following 15 are the velocity maps for one full cardiac cycle, with velocity rendered in gray scale. Figure 4 shows the cephalocaudal velocity in a coronal plane through the fourth ventricle and brain stem (in-plane motion study). The magnitude image is at left, and two frames of the cine images are shown measured at gate delays of 0 and 75 msec after the ECG R wave. Figure 5 shows a study of a healthy data set of 25 images was obtained for cephalocaudal velocities in a transverse plane at the level of basal gan-
performed cine data des, with
glia,
50 msec.
Vnliime
and
rigid ic
motion
#{149} Number
correction
I
was
as described set covered a progressive Figure
3 shows
two
above. The cardiac cygate delay of a magnitude
volunteer
in which
the
nal velocity components consecutively in transverse The anteroposterior and
three
orthogo-
were imaged planes. cephalocau-
Radin1nv
#{149} 1s47
dal
components
were
measured
in an
Head
identical transverse plane 1.5 cm above the orbitomeatal line; the mediolateral component was imaged at a similar but not identical location coyenng the thalami. Figure 5a shows magnitude and velocity images at ECG
gate
delays
of 50 and
100
tion
Motion
occurs
biphasic
Scalp motion, assumed to be directly equal to head motion, was evaluated in a healthy volunteer and was found to be highly reproducible. Qualitatively, most of this head mo-
in systole cephalocaudal
and
consists
of a
displacement
followed by quiescence during diastole (see Fig 2a). To evaluate intercycle variability, studies of multiple heartbeats were same individual.
compared In a typical
in the case,
six
msec,
in all three motional axes. Figure 5b shows the three corresponding, complete velocity-time curves for a region of interest in the thalamus. In summary, brain motion appears to consist of a single displacement in systole
the
followed
initial
by
a slow
configuration
This displacement of the midbrain
and
return
to
in diastole. includes brain
a descent stem to-
ward the foramen magnum, with yelocities increasing with proximity to the foramen ( 2 mm/sec) and medial compression of the thalami on the third ventricle ( 1.5 mm/sec). Table 2 summarizes our measurements of maximum cephalocaudal, mediolateral, and anteropostenor velocities for six subjects transverse
on selected plane through
regions the
Figure 4. Phase-subtraction cine coronal study of head-motion-corrected cephalocaudal yelocities (coronal plane) through the quadrigeminal plate cistern and the brain stem in a 25year-old woman. At left is the T2-weighted magnitude image (four R-R intervals/90), and at right are two images of the cephalocaudal velocity, corresponding to delays of 0 and 100 msec after the ECG R wave. These data were acquired with motion encoding in the phase-encode direction. Velocity gray scale ranges over ±2 mm/sec. darker shades being caudal and lighter
of a lateral
and third ventricles (Fig 6). Cornputed net pulsatile displacements of the brain parenchyma are not greater than 0.5 mm. The axial motion of the midbrain is subtly asymmetric in the anteroposterior direction, with iniliation with respect to systole occurring more posteriorly. The motion of the cerebral periphery is relatively small. Anteroposterior motions tend also to be small in the forebrain, no more than 25% of the observed cephalocaudal and lateral motion, but may be of larger magnitude in the brain stem.
Cephalic Anterior Right
shades
being
foramen
cephalic.
Note
the
increase
in caudal
yelocities
(darker)
with
proximity
to the
magnum.
-
Caudal Posterior Left
-
0
100
200
-
300 Delay
400 From
-..-
Cephalo-Caudal
-
Antero-Posterior
._;;_
Left-Right
---
A-wave
500
600
700
800
(msec)
b. a. Figure 5. (a) Phase-subtraction cine study (four R-R intervals/90) of head motion-corrected cephalocaudal, anteroposterior, and lateral yelocities (transverse plane) through the third ventricle and the thalami in a 33-year-old man. Anatomic images (center) and velocity maps (right) corresponding to 50 and 100 msec after the R wave are shown for cephalocaudal motion (top), anteroposterior motion (middle), and mediolateral motion (bottom). The mediolateral measurement required 90#{176} rotation of the head, approximating the prior section position. Note the strong negalive cephalocaudal velocities, indicating caudal displacement of the midbrain, as well as the strong opposite mediolateral yelocities in the thaIami, associated with a medial compression of the thalami on the third ventricle. Ant = anterior, caud = caudal, cepli = cephalic, post = posterior. (b) Three corresponding complete velocity-time curves for a region of interest in the left thalamus indicated on the magnitude images. MR
Radinlnv
#{149}
December
1992
cine
series
were
of cephalocaudal
collected
and
ations of series were computed; to 0.3 mm/sec.
and
velocity
the standard
devi-
of equal-delay images they varied from 0.1 depending on time
tion cine ure 3.
location.
with
Comparison To verify native ment, FVZ
one
=
our
velocity
data,
shown
sional velocity gies may omit CNS
results
with
dimension)
in Fig-
DISCUSSION Observations Implications
technique,
as ([7] with
dal velocities were measured at six different cardiac phases (0-500-msec cardiac delays from the R wave) in the same volunteer and at the same section as that in Figure 3. Figure 7b shows multiple velocity profiles across the section, extracted from our 3D Fourier-transformed data set collected during early systole (see Fig 7
This
prior
study
of Brain Motion for Imaging confirms
MR imaging
several observed
points:
and
and
observations First,
the
on
Phase
6.
T2-weighted
MR
image
(four R-R for Ta-
area gray callo-
of
are observed
for CSF
venous
difference
flow
flow
is confirmed
and
in the
more
arterioneck
(6).
high of brain If this generally,
MR imaging not being for accurate measurement persons. Our echo-planar
finding
is at variance
preliminary findings Mark (7); it suggests
with
us to identify the of brain motion.
subtraction
in
the
of Feinberg and that one-dimen-
niques lional
and
represent
cycle-mean-
alternative
tech-
for the removal of nonmophase terms. Two contrasts
between
these
techniques
are
of basic
artifacts. The phase alternation method should remain accurate in these conditions. Thus, the cycle-
measurement, however, may be valuable in the study of transient, experimentally induced perturbation of brain velocity by mechanical or pharmaceutical means. The present study indicates that at least two vector components contribute substantially to the total motion, the cephalocaudal and the lateral. This
should
importance. First, the cycle-meansubtraction method is inaccurate where the temporal-mean velocity is nonzero, for it removes nonzero mean velocities along with the phase
it will validate the previous and future use of conventional ECG-gated multishot velocity MR imaging technique in the CNS and is suggestive of
Figure
time,
will help source”
subtraction
maximum
The study also demonstrates beat-to-beat reproducibility motion in healthy subjects.
intervals/80) shows regions selected ble 2. A = frontal lobe, B = anterior corpus callosum, Cl and C2 = deep matter, D = posterior area of corpus sum, E = occipital lobe.
measurement-encoding
ternthe
Technique
extends
(7). Second, the observed CNS motion is temporally simple, being essentially the velocities of a single monophasic displacement of the brain (in various directions) that occurs chiefly during cardiac systole, confirming previous results (7,9). Similar temporal patterns
single-shot essential healthy
of the
motion.
sampling “initiating
parenchymal velocities are on the order of 2-3 mm/sec. which is in agreement with Feinberg and Mark
finding
methodolofacets
allow for a finer sampling of the sequence of movements within the thalami, brain stem, and spinal cord. Finer
an alter-
others have done in conventional with 2D FVZ) or echo-planar ([8] 3D FVZ) imaging mode. Cephalocau-
imaging substantial
Future improvements in the poral resolution, by shortening
3D FVZ
method of velocity measurewe applied a 2D FVZ (3D two spatial dimensions and
velocity
legend for full technical description). Note the good correlation of this result with Figure 7c, representing the corresponding profiles derived from the first frame of the phase-subtrac-
mean-subtraction method would not detect the small, steady velocity of CSF drift. Conversely, phase alternalion requires an identical motion pattern in successive heartbeats (true periodicity), subtraction
whereas method
mean subtraction ful if the cardiac although a large may ased
the cycle-meandoes not. Thus,
should rhythm number
remain useis irregular, of images
be needed to guarantee sample. A mean phase
an may
unbialso
be measured from ungated data, vided the cardiac cycle is covered formly
and
densely
sense). Comparison
(in
of our
the
prouni-
Nyquist
2D phase-con-
trast rapid imaging method with FVZ suggests a few general points. FVZ suffers important limitations corn-
pared with presented.
the 2D instant FVZ is a more
suming procedure, measurements.
The
requiring velocity
techniques time-conmultiple spectrum
obtained with such a method provides an orderly way to organize the velocity distribution within a voxel and so to eliminate “partial voluming”
effects
between
multiple
velocity
components. (Similarly, it will spread velocity information among multiple levels in the case of cardiac variability or nonperiodic motion.) Unfortunately for brain this offers little
have pointed in the brain FVZ velocity results
from
attenuating with high Volume
185
Number
#{149}
3
parenchyma motion, interest. As others
out (8), proton diffusion introduces a blurring into spectra. Such blurring diffusion
progressively
the signal from images encoding gradients. ReferRadiology
#{149} 649
present methodology. For example, covering the brain with 20 sections, 10 gate delays, and three velocity cornponents requires 1,200 images. At 150
ring to the FVZ experiment described in Figure 7, velocity line broadening due to brain water apparent diffusion (10 cm2/sec) would be 0.4 mm/sec (kernel full width at half maximum). Deconvolulion methods to reduce blurring have been proposed (8).
msec only
versus
Total
Motion
tudes
components.
of these
effects
are
The
magni-
not
known,
however, and may influence producibility and interpretation brain motion data. The methodology of linear scribed
here
the
computed
this
possibility,
may
introduce
images. the
the
facts in MR signals from
memory
only
by
space
of
imaging single
to disperse voxels will
fit deinto
signal
loss
affect
measurement
fusion
due
to brain
constant.
knowledge
To investigate
lion
noninvasively.
Further
imaging
studies of CNS kinematics with brain motion-sensitive MR imaging will be needed to evaluate its ability to define normal and abnormal states, such as normal pressure hydrocephalus
the result
motion
of the model
dif-
increased
features
motion,
adequate
can
of the water Despite
parenchymal
fit model
parameters were evaluated by means of linear regression. With the optimal acquisition parameters indicated in Materials and Methods, the standard deviation, a, of the difference between the data and the linear fit was mm/sec. The standard error of the model varies with position, being lowest near the centroid of the sample points. By assuming the data deviations are distributed normally, the standard error of the linear regression would be approximately a/ N near the centroid of the sample points (central brain) and range up to a / 2/N peripherally (17), where N is the least-
of brain
we
with
still
which
lack
an
to detera.
a -T------
0.11
squares points.
fit total By using
standard
error
number
sec
throughout
smaller
than
variability
I 3
the
‘
-3 ‘t 3 2 1
of data
typical
‘
-4 C
-1
--
1____ -2 -3
is 0.01-0.02 mm/ the brain, much
of 0.1-0.3
b L____-
N = 150 points, the of the linear model in
these experiments
motion
of appar-
in false signal attenuation and quantitative errors in, for example, relaxation time measurements. In addition,
reof
noise
linear
image
prototype instrument. We believe that small head and brain motions are probable contaminants of most MR imaging procedures. Such motions add to the incoherent noise present on all images and, in some cases, may be a limiting factor in applications where critical evaluation of signal intensities is required. The tendency for motion arli-
stead, to be influenced strongly by the mechanics of the neck. As noted, mathematical correction of rigid movement does not remove all the effects of an external impulse on the brain, which may include both rigid
plastic
set requires lime. Such
is precluded
limited
such
ent diffusion coefficient. This will be the object of further investigations for modeling and simulation. High-speed MR imaging has a unique capacity to image brain mo-
our
We corrected for the rigid head motion because we assume this motion to reveal little about the CNS, but in-
and
this data of imaging
an acquisition the
Relative
per image, 3 minutes
mine quantitatively how will affect the measurement
beat-to-beat
mm/sec.
CONCLUSION The present investigation prompted by our belief that standing of CNS kinematics
advanced
by an approach
was an underwould be
that
in-
creases data rates, allowing large sets of the full position-lime-velocity
sub-
matrix
effiIn
ciently
the image
of the brain to be sampled and presented coherently. present framework, a complete of CNS
motion
would
vector with one spatial coordinates.
temporal While
such
data
are
herein,
their
acquisition
650
#{149} Radiology
presented
is feasible
with
Figure
7.
Comparison
(a) T2-weighted pared in b and 3D echo-planar
the
a
sensitized repetition
of cephalocaudal
2D cine
MR image (four R-R intervals/80) c. Lateral to the head are static FVZ
tion of multiple
specify
3D velocity and three
not
b.
method.
2D time
to motion time was
data,
Velocity
profiles
stepped
through
along the section-select four R-R intervals, and
were collected by using a 3-msec cardiac well with the phase-subtraction profiles by using velocities
the 50-msec as positive
frame from and caudal
the data velocities
phase-subtraction shows the location
phantoms. are
obtained
32 gradient
direction. echo time
delay shown
(b) Velocity by means
steps
(±1.0
profiles
obtained
of Fourier
G/cm
2D FVZ. profiles corn-
with
a
transforma-
1±0.0001
T/cm]),
Velocity resolution was 0.5 mm/sec. was 170 msec. Velocity profiles shown the R wave. These FVZ profiles compare
after in c. The
set shown as negative
studies with of velocity
phase-sensitive
in Figure 2. Both (in millimeters
profiles
were
b and c show per second).
derived
cephalic
December
1992
(18,19)
and
nal cord
diseases
involving
the
plexuses as the generator of the force for flow of the fluid and ventricular enlargement. J Neurosurg 1962; 19:405-413.
spi-
(20,21). 2.
APPENDIX In the presence with
zero
of any gradient
net moment,
I: where
G(t)
=
that
G(t)dt
0,
pulse
4.
KE, et al. Marked cerebrospinal fluid void: indicator of successful shunt in patients with suspected normal-pressure hydrocephalus. Radiology 1991; 178:459-466. Hennig J, Ott D, Adam T, Friedburg H.
+ -1 fT[ft
v(t’)dt’}}G(t)dt
lion (Al),
That
and
=
--YfoT
[ft
=
-1
w(t)v(t)dt.
IT
Jo
is, the phase
weighted dient-encoding
by using
Equa-
G(t’)dt’]v(t)dt
7. on the
velocity
during
period.
R, Greitz of pulsatile
imaging
discussions
David shy,
sion
with
Mikulis,
Gilberto
Gonzalez,
MD. We thank
Robert
the gra-
8.
Enzmann surement trast cine
grateful
for the support
MD,
9.
and
McKin-
an initial especially ofThomas J. Brady,
ver-
and
Bering
EA.
Circulation
of the cerebrospi-
nal fluid: demonstration
185
#{149} Number
of the choroid
3
using
DE, Ross MR. Pelc NJ. Meaof CSF flow using a phase conMR pulse sequence (abstr). In:
fluid
DA, Jakab studied
line scan, and echo-planar
Magn
Reson
Med
1990;
(abstr).
In: Book
Weisskoff
Reson
10.
Poncelet
Cohen
BP, Wedeen
MS, Brady motion
with
VJ, Weisskoff
TJ.
14.
the human heart using a new, whole-body MR imaging system. AJR 1987; 149:245-250. Moran P. A flow velocity zeugmatographic interlace for NMR imaging in humans. Magn Reson Imaging 1982; 1:197-
IL.
15.
203. O’Donnell M. using multiecho,
NMR blood phase
flow imaging
contrast
sequence.
Med Phys 1985; 12:59-64. Wedeen VJ, Crawley AP, Weisskoff Holmvang
C, Cohen
MS.
RM,
Real-time
MR
imaging of structured fluid flow (abstr). In: Book of abstracts: ninth annual meeting of the Society of Magnetic Resonance in Medicine, 1990. Berkeley, Calif: Society of Magnetic Resonance in Medicine, 1990; 164.
18.
20.
Bevington
P.
Data
reduction
and
error
analysis for the physical sciences. New York: McGraw-Hill, 1969. Bradley WG, Atkinson DJ, Nitz WR, et al. Quantitative cerebrospinal fluid velocity imaging: comparison of normals and patients with shunt-responsive normal pressure hydrocephalus. JMRI 1992; 2(P):59. HennigJ, Wahkloo AK, Jungling FD. MR interferographic examination of brain motion. JMRI 1992; 2(P):108. Levy LM, Di Chiro C, McCullough DC,
Dwyer AJ, Johnson DL, Yang SSL. Fixed spinal cord: diagnosis with MR imaging. Radiology 1988; 169:773-778. 21.
Levy
LM,
Wang
H, Carson
B, Schellinger
D, Di Chiro G, Bryan RN. Dynamic MR imaging for Chiari malformations (abstr). Radiology
1991;
181(P):172.
RM,
Measurement
EPI (abstr).
RR, Pykett
Ultra-fast im1991; 9:1-37. Instant images of
Rzedzian
imag-
tenth
RM.
Imaging
13.
16:280-293.
of abstracts:
855.
MS,
19.
annual meeting of the Society of Magnetic Resonance in Medicine, 1991. Berkeley, Calif: Society of Magnetic Resonance in Medicine, 1991; 44.
1991;
Magn
circulation
PD. Tissue perfusion by Fourier velocity dis-
in Medicine,
aging.
17.
imaging.
Soci-
Cohen
16.
HennigJ, Wahkloo AK, Koch D, Laubenberger J. The examination of ECG-dependent brain motion with MR-interferogra-
brain
Volume
motion
of the
12.
(abstr).
cerebrospinal
Feinberg in humans
phy MD.
References 1.
Mea-
Book of abstracts: tenth annual meeting of the Society of Magnetic Resonance in Medicine, 1991. Berkeley, Calif: Society of Magnetic Resonance in Medicine, 1991; 155. Feinberg DA, Mark AS. Human brain mo-
ing.
helpful
for his help in providing of a pulse sequence. We are MD,
brain
M.
meeting
Resonance in Medicine, Calif: Society of Magnetic
Stejskal EO. Use of spin echoes in a pulsed magnetic-field gradient to study anisotropic, restricted diffusion and flow. Chem Phys 1965; 43:3597-3603.
an inter-
demonstrated with MR velocity Radiology 1987; 163:793-799.
N
We appreciate
Resonance
C, St#{228}h-
F, Stubgaard
MR phase
tribution, Acknowledgments:
using
D, Thomsen
surement
tion
depends
average
flow
annual
11.
In: Book of abstracts: ninth annual meeting of the Society of Magnetic Resonance in Medicine, 1990. Berkeley, Calif: Society of Magnetic Resonance in Medicine, 1990; 1107.
v(t’)dt’]G(t)dt.
by parts,
Wirestam
AR, Kortman
MR technique based on the imaging sequence. Magn Re1990; 8:543-536.
lebrg F, Nordell
6.
integrating
Whittermore
of CSF
ferographic RARE-FAST son Imaging
,yfTx#{216}G(t)dt
=
WG,
Measurement
5.
[ft
+
{0
Bradley
amplitude,
position, v(t) = velocity, and _)‘ = gyromagnetic constant, the full expression of the phase shift of a moving spin is given by
fT
3.
(Al)
xo = initial
‘p = -y
Bostick on pulfluid 13:497-
tenth
ety of Magnetic 1991. Berkeley,
523.
is,
=
gradient
pulse
Du Boulay G, O’ConnellJ, CurrieJ, T, Verity P. Further investigations satile movements in the cerebrospinal pathways. Acta Radiol Diagn 1972;
abstracts:
In: Book
of of
Radiology
#{149} 651
Poncelet,
P.
Brain with
(MR)
measured
tion
imaging, the
of brain
sitive,
J.
Van
#{149}
intrinsic
pulsatile
parenchyma.
mo-
Phase-sen-
two-dimensional
planar
cine
throughout a spin-echo,
MR
pulse
images
were
the cardiac cycle blipped echo-
sequence.
Trans-
verse and coronal planes were obtamed in 14 healthy volunteers. Corrections were made for gross head
motion.
Brain
motion
consisted
of a
rapid displacement in systole, with slow diastolic recovery. The motion occurred chiefly in the cephalocaudal
a
and lateral directions; the anteroposterior motions were relatively small. Cephalocaudal velocities increase with
proximity
num.
The
to the
lateral
foramen
motion
mag-
is mainly
compressive motion of the Brain parenchymal velocities high as 2 mm/sec caudally
a
thalami. were in the
as
brain stem and 1.5 mm/sec medially in the thalami. Net parenchymal excursions were at most 0.5 mm. Phasebased echo-planar velocity measurements agreed well with echo-planar Fourier velocity zeugmatography measurements and were consistent with reported values. Velocity mapping with echo-planar imaging offers
a rapid
and
flexible
ing the pulsation man brain.
method velocities
of several techniques, including phase contrast (5,6), Fourier velocity zeugmatography (FVZ) (7,8), and image mnterferography (9). We present a method to map CNS velocity components by using spin-echo echo-planar
MR
imaging,
which
of assess-
the
fluid, MR. (MR), cine (MR), echo planar
representation of the (3D) dynamics of
AND
METHODS
2D sensitivity
echo-planar
image.
is created
by
incorpo-
1992; 185:645-651
From the MGH-NMR Center, Department of Radiology, 13th St. Charlestown, MA 02129. Received December 27, 1992; final reyision received June 30; accepted July 6. Supported GE Medical Systems, and Advanced NMR Systems. Address ‘ RSNA, 1992 See also the article by Enzmann and PeIc (pp 653-660) and this issue.
S. Cohen,
PhD
rating ing
a pair pulse
of unipolar
gradients
velocity-sensitiz-
along
a chosen
direc-
lion into an MR spin-echo pulse sequence (11). This spin-echo sequence allows us to measure slow motion by using long, velocity-sensitizing, gradient pulses without extensive T2* decay, a potential source of limitation in gradient-echo techniques.
Data
Acquisition
All imaging was performed with a 1.5-T Signa imager (GE Medical Systems, Muwaukee) retrofitted with Instascan technology (Advanced NMR Systems, Wilmington, Mass). The imaging pulse sequence was a blipped echo-planar acquisition (12,13) augmented by a pair of unipolar velocity-sensitizing gradient pulses placed before and after the 180#{176} radio-frequency pulse (Fig 1). The yeloc-
ity-sensitizing gradient either the section-select
was applied
along
axis (ie, throughplane motion) or the phase-encoding axis (in-plane motion); amplitudes were 0.11.0 C/cm (0.1-1.0 x 10 T/cm); gradient pulse duration, 8, was 20-40 msec; and the time interval between gradient pulses, , was 23-46 msec (total motion-encoding duration, + 8 = 43-86 msec). These pulses provided velocity sensitivities of 0.7-5.0 radians . mm sec. The velocity sensitivity, K, was made as large as possible, consistent with the re-
quirement not wrap;
that the measured that
is, p
=
K
phases,
V must
p,
satisfy
I’ I
< rr radians at all points. Thus K < radians/V,,), where Vma. 5 the maximum velocity to be imaged. The full expression of ip shows (see Appendix) that the measured phase corresponds to an average measurement of velocity over the duration of the total motion encoding + b. Acquisition parameters were as follows: echo time of 80-120 msec, acquisilion matrix of 64 x 128, in-plane resolution of 3 x 3 mm, and section thickness of 5-10 mm. The sequence was electrocardiography (ECC) gated; an image was collected every one to four R-R intervals with (IT
Our basic technique for brain motion measurement is to analyze a velocity-dependent phase map obtained from a yeVelocity
149,
to
CNS.
locity-sensitized
Radiology
can be used
acquire a two-dimensional (2D) image in less than 0.1 second (10). These rapid rates of acquiring echo-planar imaging data facilitate acquisition of more extensive data sets, offering a
of the
Mark
#{149}
Measurement Imaging’
the rigid cranium, blood, cerebrospinal fluid (CSF), and brain tissue engage in a complex and imperfectly understood three-dimensional (3D) motion. Although different proposed models represent brain motion as the “circulation pump” of the CSF (1,2), direct validations of these models in the human brain have been limited. Because derangements of central nervous system (CNS) dynamics may play an important role in a variety of diseases (3,4), a better understanding of the dynamics of normal CNS is required. As several recent reports have mdicated, magnetic resonance (MR) imaging allows detection and measurement of motion throughout the CNS precisely and noninvasively by means
MATERIALS Index terms: Cerebrospinal 10.1214 #{149} Magnetic resonance study #{149} Magnetic resonance
PhD
ITHIN
more complete three-dimensional
hu-
M. Weisskoff,
#{149} Robert
Motion: MR
W
magnetic resothe authors
electrocardiography-gated,
acquired by using
MD
Wedeen,
Parenchyma Cine Echo-Planar
With echo-planar nance
MS
Massachusetts General Hospital, Bldg 1991; revision requested February 12, in part by NIH grant no. 5RO1HC3937, reprint requests to B.P.P. editorial
by Feinberg
(pp
630-632)
in
Abbreviations:
CNS
=
central
nervous
system,
CSF = cerebrospinal fluid, ECG = electrocardiography, FVZ = Fourier velocity zeugmatography, 3D = three-dimensional, 2D = two-dimensional.
645
1. Blipped echo-planar Instascan (Advanced NMR Systems) spin-echo pulse sequence. The readout gradient (G-Readout) is a resonant gradient producing a train of 64 echoes, one every 500 sec, applied in combination with the “blipped” gradient in the phaseencode direction, for a 2D single-shot acquisition (12,13). An auxilFigure
iary
motion-encoding
gradient,
of duration
8, is applied
along
either
the section-select direction (as shown) or one of the in-plane direclions. The total motion-encoding duration is + b. This velocityencoding gradient is applied either in a single polarity for each image (solid boldface line) or with alternating polarities for pairs of images (solid boldface and dashed lines). RF = radio frequency.
G-Readout
RJ.Jii A
a cardiac
delay
by 50 msec
progressively
per
image,
G-22LflJLfL
incremented
for 25 images.
Typi-
cally, the delay range spanned two full cardiac cycles. Depending on technique (see below), one or two image series were obtained, with either a single-polarity velocity encoding (Fig 1, solid boldface line) or an interleaved acquisition with alternating positive and negative polarities (Fig 1, solid boldface and dashed lines). The total data acquisition limes were from 20 seconds to 3 minutes. For studies of cephalo-
caudal
and anteroposterior
velocity,
the
subject was positioned supine in the head coil, with restraint to reduce head motion.
Due to system
limitations,
repositioned
subjects
in a 90#{176} lateral
position
for studies
were
Motion
observed
phase
in each
Cp1[x,yJ=
where
image:
pj[X,y]
-
p[x,yJ/N,
(1)
is the
ith phase image after correction, Pi[X,Y] S the ith phase image, and i = 1, . . N, where N is the total number of phase data collected over the car[X,y]
.,
diac cycle. ages 1[X,y]
Each of the
corrected
phase
im-
is purged of all phase terms that are constant over the image series (5,16). The simple methodology embodied
decubitus
of the mediolateral
velocity.
Equation (1) is applicable provided that the image phases do not wrap; more cornplex methods are required if phase wrap is in
Phase
Corrections
The phase
of the reconstructed
image
data reflects the velocity of the brain tissue at each pixel, but also contains additive phase errors of several types that must be
removed to isolate the velocity-dependent phase shifts. Two methods were investigated to remove such phase errors. (We shall abuse notation and refer to phase and velocity interchangeably, recaffing that phase p = K V for a constant of sensilivity K in each experiment [14].) .
Method
1 : phase
subtraction-Subtracting
the phase of pairs of images collected with velocity-encoding gradient pulses of opposite polarities cancels constant phase errors and isolates the motion-specific phase terms (15): (j = (p1f ‘P1’ where and p denote the velocity encodings of
_
the respective signs for the ith phase image and (j S the final phase-subtracted image. The phase-subtraction technique assumes that the brain motion is periodic, so that the same sequence of velocity dis-
tributions is played out in each heartbeat. It also assumes that the velocity-sensitizing gradient substantial Method
Unlike has
pulse does not itself cause phase errors. 2: cycle mean phase correction.-
blood
and CSF, solid brain
no net translation:
over one cardiac
cycle
Its average
must
tissue velocity
be zero.
This
principle allows us to correct any timeconstant phase errors, such as those of magnetic field variation or radio-frequency phase dispersion. At each pixel, compute the mean phase over the cardiac cycle and subtract this mean from the
we 646
Radiology
#{149}
present.
Data Processing: Compensation To identify
the motion
five to the skull, skull
Head
Motion of the brain
the rigid
is measured
and
motion
rela-
of the
subtracted
from
the
parenchyma velocity maps. A vector component of the motion of a rigid body
brain
(translation
plus
function L1[x,y]:
of the L1[x,yJ
where
the rates
x,y
rotation) image
=Ax
must be a linear coordinates,
+ By
of translation
+ V0,
Encoding
Gradients
of the ith lime point. This procedure removes the instantaneous contribution of rigid head motion on a frame-by-frame basis. This is not a substitute for immobilization of the head, since internal brain motions (“sloshing”) may be induced by rigid accelerations, particularly rotation, of the head. This procedure also corrects echo miscentering in k space, accomplished in other cases with the aid of stationary reference phantoms. The effect of this head motion compensation on observed parenchymal motion is illustrated
for
two
different
regions
(Fig
2).
Cephalocaudal velocity curves are shown for a frontal pole region (Fig 2a) and for a deep gray region (Fig 2b). The curves represent the computed, rigid motion at the selected locations, as well as the brain yelocity before and after rigid motion correclion. Cerebral periphery velocities (Fig 2a) are seen to be correlated strongly to the head motion and are reduced substanlially after correction. By contrast, the yelocities of the central structures appear less strongly correlated with the rigid head motion.
(2)
RESULTS
and rotation
determine the constant V0 and the rotalion rate determines the constants A and B. The values of V0, A, and B could be fixed by determining the value of V at three locations, but it is preferable from a signalto-noise standpoint to measure V, at a
This
study
volunteers years).
examined
of both Informed
14 healthy
sexes
(aged
consent
was
20-40 ob-
large set of points and to solve for the coefficientrmn Equation (2) by a linear least-
tamed according to the Subcommittee on Human Studies guidelines at our institution. Single or multiple axial and/or coronal images were obtained.
squares
In total,
fit. In practice,
we have typically 150 points in the scalp, which we assume moves with the skull and which furnishes a readily identifled MR signal. For adequate skin signal, we used four R-R intervals for repetition
measured
V at
and
about
cording
L1[x,y],
locity
at each
where and
point:
V[x,y]
=
V[x,y]
V[x,y] is the corrected yeV1[x,y] is the observed velocity
series
to section
were
collected
in Table
1 ac-
orientation,
section
acquisition mode, and velocity ponent measured (cephalocaudal, anteropostenor, or mediolateral).
time and 1.0 cm for section thickness. To find the rigid motion corrected velocity for each lime frame, a linear-fit function is subtracted from the observed velocity
84 cine
are summarized
Brain -
Motion
com-
Observations
Figure 3 shows a typical, throughplane motion study. By using the phase-subtraction
technique,
a cine
December
1992
Cephalic
Cephalic
I
At 0
(C
a) C’,
a)
E E
E E
>‘
>‘
U)
0
(C
0 a,
0
a)
>
-0.5
>
-
\.
.
Caudal
‘I
#{149}
0
.
Ii
“1’
-1
100
200
300 Delay
.
from
400 A-wave
500
600
Caudal
700
0
100
200
(msec)
300
400
500
Delay from R-wave
a.
600
700
(msec)
b.
Figure
2. Head motion (b) in a deep gray region.
(El) head
motion
correction For each
correction,
and
at the region,
the local
periphery and center. Time three velocity-time curves
head
motion
(U) derived
curves for correspond
from
cephalocaudal to the measured
the linear
velocities measured (a) in the parenchymal velocity, with
fit, computed
at these
I
frontal brain and (0) and without
locations.
Figure
3.
Phase
subtraction
cine study
level man.
of the basal A magnitude
vals/90
ganglia image
[repetition
time
indicate
ECG
gate
at the
in a 37-year-old (four R-R intermsec/echo
time])
at top left, followed by 14 images caudal velocity covering a cardiac times
of ye-
head-motion-corrected, cephalocaudal locity imaged in a transverse plane
delays
is
of cephalocycle. from
the
The R
wave. The velocities are shown in gray-scale representation, ranging over ±2 mm/sec. Darker shades correspond to caudal velocities,
and
zero
velocity
lighter
shades,
is medium
to cephalic
velocities;
gray.
image frames
at top left; the following 15 are the velocity maps for one full cardiac cycle, with velocity rendered in gray scale. Figure 4 shows the cephalocaudal velocity in a coronal plane through the fourth ventricle and brain stem (in-plane motion study). The magnitude image is at left, and two frames of the cine images are shown measured at gate delays of 0 and 75 msec after the ECG R wave. Figure 5 shows a study of a healthy data set of 25 images was obtained for cephalocaudal velocities in a transverse plane at the level of basal gan-
performed cine data des, with
glia,
50 msec.
Vnliime
and
rigid ic
motion
#{149} Number
correction
I
was
as described set covered a progressive Figure
3 shows
two
above. The cardiac cygate delay of a magnitude
volunteer
in which
the
nal velocity components consecutively in transverse The anteroposterior and
three
orthogo-
were imaged planes. cephalocau-
Radin1nv
#{149} 1s47
dal
components
were
measured
in an
Head
identical transverse plane 1.5 cm above the orbitomeatal line; the mediolateral component was imaged at a similar but not identical location coyenng the thalami. Figure 5a shows magnitude and velocity images at ECG
gate
delays
of 50 and
100
tion
Motion
occurs
biphasic
Scalp motion, assumed to be directly equal to head motion, was evaluated in a healthy volunteer and was found to be highly reproducible. Qualitatively, most of this head mo-
in systole cephalocaudal
and
consists
of a
displacement
followed by quiescence during diastole (see Fig 2a). To evaluate intercycle variability, studies of multiple heartbeats were same individual.
compared In a typical
in the case,
six
msec,
in all three motional axes. Figure 5b shows the three corresponding, complete velocity-time curves for a region of interest in the thalamus. In summary, brain motion appears to consist of a single displacement in systole
the
followed
initial
by
a slow
configuration
This displacement of the midbrain
and
return
to
in diastole. includes brain
a descent stem to-
ward the foramen magnum, with yelocities increasing with proximity to the foramen ( 2 mm/sec) and medial compression of the thalami on the third ventricle ( 1.5 mm/sec). Table 2 summarizes our measurements of maximum cephalocaudal, mediolateral, and anteropostenor velocities for six subjects transverse
on selected plane through
regions the
Figure 4. Phase-subtraction cine coronal study of head-motion-corrected cephalocaudal yelocities (coronal plane) through the quadrigeminal plate cistern and the brain stem in a 25year-old woman. At left is the T2-weighted magnitude image (four R-R intervals/90), and at right are two images of the cephalocaudal velocity, corresponding to delays of 0 and 100 msec after the ECG R wave. These data were acquired with motion encoding in the phase-encode direction. Velocity gray scale ranges over ±2 mm/sec. darker shades being caudal and lighter
of a lateral
and third ventricles (Fig 6). Cornputed net pulsatile displacements of the brain parenchyma are not greater than 0.5 mm. The axial motion of the midbrain is subtly asymmetric in the anteroposterior direction, with iniliation with respect to systole occurring more posteriorly. The motion of the cerebral periphery is relatively small. Anteroposterior motions tend also to be small in the forebrain, no more than 25% of the observed cephalocaudal and lateral motion, but may be of larger magnitude in the brain stem.
Cephalic Anterior Right
shades
being
foramen
cephalic.
Note
the
increase
in caudal
yelocities
(darker)
with
proximity
to the
magnum.
-
Caudal Posterior Left
-
0
100
200
-
300 Delay
400 From
-..-
Cephalo-Caudal
-
Antero-Posterior
._;;_
Left-Right
---
A-wave
500
600
700
800
(msec)
b. a. Figure 5. (a) Phase-subtraction cine study (four R-R intervals/90) of head motion-corrected cephalocaudal, anteroposterior, and lateral yelocities (transverse plane) through the third ventricle and the thalami in a 33-year-old man. Anatomic images (center) and velocity maps (right) corresponding to 50 and 100 msec after the R wave are shown for cephalocaudal motion (top), anteroposterior motion (middle), and mediolateral motion (bottom). The mediolateral measurement required 90#{176} rotation of the head, approximating the prior section position. Note the strong negalive cephalocaudal velocities, indicating caudal displacement of the midbrain, as well as the strong opposite mediolateral yelocities in the thaIami, associated with a medial compression of the thalami on the third ventricle. Ant = anterior, caud = caudal, cepli = cephalic, post = posterior. (b) Three corresponding complete velocity-time curves for a region of interest in the left thalamus indicated on the magnitude images. MR
Radinlnv
#{149}
December
1992
cine
series
were
of cephalocaudal
collected
and
ations of series were computed; to 0.3 mm/sec.
and
velocity
the standard
devi-
of equal-delay images they varied from 0.1 depending on time
tion cine ure 3.
location.
with
Comparison To verify native ment, FVZ
one
=
our
velocity
data,
shown
sional velocity gies may omit CNS
results
with
dimension)
in Fig-
DISCUSSION Observations Implications
technique,
as ([7] with
dal velocities were measured at six different cardiac phases (0-500-msec cardiac delays from the R wave) in the same volunteer and at the same section as that in Figure 3. Figure 7b shows multiple velocity profiles across the section, extracted from our 3D Fourier-transformed data set collected during early systole (see Fig 7
This
prior
study
of Brain Motion for Imaging confirms
MR imaging
several observed
points:
and
and
observations First,
the
on
Phase
6.
T2-weighted
MR
image
(four R-R for Ta-
area gray callo-
of
are observed
for CSF
venous
difference
flow
flow
is confirmed
and
in the
more
arterioneck
(6).
high of brain If this generally,
MR imaging not being for accurate measurement persons. Our echo-planar
finding
is at variance
preliminary findings Mark (7); it suggests
with
us to identify the of brain motion.
subtraction
in
the
of Feinberg and that one-dimen-
niques lional
and
represent
cycle-mean-
alternative
tech-
for the removal of nonmophase terms. Two contrasts
between
these
techniques
are
of basic
artifacts. The phase alternation method should remain accurate in these conditions. Thus, the cycle-
measurement, however, may be valuable in the study of transient, experimentally induced perturbation of brain velocity by mechanical or pharmaceutical means. The present study indicates that at least two vector components contribute substantially to the total motion, the cephalocaudal and the lateral. This
should
importance. First, the cycle-meansubtraction method is inaccurate where the temporal-mean velocity is nonzero, for it removes nonzero mean velocities along with the phase
it will validate the previous and future use of conventional ECG-gated multishot velocity MR imaging technique in the CNS and is suggestive of
Figure
time,
will help source”
subtraction
maximum
The study also demonstrates beat-to-beat reproducibility motion in healthy subjects.
intervals/80) shows regions selected ble 2. A = frontal lobe, B = anterior corpus callosum, Cl and C2 = deep matter, D = posterior area of corpus sum, E = occipital lobe.
measurement-encoding
ternthe
Technique
extends
(7). Second, the observed CNS motion is temporally simple, being essentially the velocities of a single monophasic displacement of the brain (in various directions) that occurs chiefly during cardiac systole, confirming previous results (7,9). Similar temporal patterns
single-shot essential healthy
of the
motion.
sampling “initiating
parenchymal velocities are on the order of 2-3 mm/sec. which is in agreement with Feinberg and Mark
finding
methodolofacets
allow for a finer sampling of the sequence of movements within the thalami, brain stem, and spinal cord. Finer
an alter-
others have done in conventional with 2D FVZ) or echo-planar ([8] 3D FVZ) imaging mode. Cephalocau-
imaging substantial
Future improvements in the poral resolution, by shortening
3D FVZ
method of velocity measurewe applied a 2D FVZ (3D two spatial dimensions and
velocity
legend for full technical description). Note the good correlation of this result with Figure 7c, representing the corresponding profiles derived from the first frame of the phase-subtrac-
mean-subtraction method would not detect the small, steady velocity of CSF drift. Conversely, phase alternalion requires an identical motion pattern in successive heartbeats (true periodicity), subtraction
whereas method
mean subtraction ful if the cardiac although a large may ased
the cycle-meandoes not. Thus,
should rhythm number
remain useis irregular, of images
be needed to guarantee sample. A mean phase
an may
unbialso
be measured from ungated data, vided the cardiac cycle is covered formly
and
densely
sense). Comparison
(in
of our
the
prouni-
Nyquist
2D phase-con-
trast rapid imaging method with FVZ suggests a few general points. FVZ suffers important limitations corn-
pared with presented.
the 2D instant FVZ is a more
suming procedure, measurements.
The
requiring velocity
techniques time-conmultiple spectrum
obtained with such a method provides an orderly way to organize the velocity distribution within a voxel and so to eliminate “partial voluming”
effects
between
multiple
velocity
components. (Similarly, it will spread velocity information among multiple levels in the case of cardiac variability or nonperiodic motion.) Unfortunately for brain this offers little
have pointed in the brain FVZ velocity results
from
attenuating with high Volume
185
Number
#{149}
3
parenchyma motion, interest. As others
out (8), proton diffusion introduces a blurring into spectra. Such blurring diffusion
progressively
the signal from images encoding gradients. ReferRadiology
#{149} 649
present methodology. For example, covering the brain with 20 sections, 10 gate delays, and three velocity cornponents requires 1,200 images. At 150
ring to the FVZ experiment described in Figure 7, velocity line broadening due to brain water apparent diffusion (10 cm2/sec) would be 0.4 mm/sec (kernel full width at half maximum). Deconvolulion methods to reduce blurring have been proposed (8).
msec only
versus
Total
Motion
tudes
components.
of these
effects
are
The
magni-
not
known,
however, and may influence producibility and interpretation brain motion data. The methodology of linear scribed
here
the
computed
this
possibility,
may
introduce
images. the
the
facts in MR signals from
memory
only
by
space
of
imaging single
to disperse voxels will
fit deinto
signal
loss
affect
measurement
fusion
due
to brain
constant.
knowledge
To investigate
lion
noninvasively.
Further
imaging
studies of CNS kinematics with brain motion-sensitive MR imaging will be needed to evaluate its ability to define normal and abnormal states, such as normal pressure hydrocephalus
the result
motion
of the model
dif-
increased
features
motion,
adequate
can
of the water Despite
parenchymal
fit model
parameters were evaluated by means of linear regression. With the optimal acquisition parameters indicated in Materials and Methods, the standard deviation, a, of the difference between the data and the linear fit was mm/sec. The standard error of the model varies with position, being lowest near the centroid of the sample points. By assuming the data deviations are distributed normally, the standard error of the linear regression would be approximately a/ N near the centroid of the sample points (central brain) and range up to a / 2/N peripherally (17), where N is the least-
of brain
we
with
still
which
lack
an
to detera.
a -T------
0.11
squares points.
fit total By using
standard
error
number
sec
throughout
smaller
than
variability
I 3
the
‘
-3 ‘t 3 2 1
of data
typical
‘
-4 C
-1
--
1____ -2 -3
is 0.01-0.02 mm/ the brain, much
of 0.1-0.3
b L____-
N = 150 points, the of the linear model in
these experiments
motion
of appar-
in false signal attenuation and quantitative errors in, for example, relaxation time measurements. In addition,
reof
noise
linear
image
prototype instrument. We believe that small head and brain motions are probable contaminants of most MR imaging procedures. Such motions add to the incoherent noise present on all images and, in some cases, may be a limiting factor in applications where critical evaluation of signal intensities is required. The tendency for motion arli-
stead, to be influenced strongly by the mechanics of the neck. As noted, mathematical correction of rigid movement does not remove all the effects of an external impulse on the brain, which may include both rigid
plastic
set requires lime. Such
is precluded
limited
such
ent diffusion coefficient. This will be the object of further investigations for modeling and simulation. High-speed MR imaging has a unique capacity to image brain mo-
our
We corrected for the rigid head motion because we assume this motion to reveal little about the CNS, but in-
and
this data of imaging
an acquisition the
Relative
per image, 3 minutes
mine quantitatively how will affect the measurement
beat-to-beat
mm/sec.
CONCLUSION The present investigation prompted by our belief that standing of CNS kinematics
advanced
by an approach
was an underwould be
that
in-
creases data rates, allowing large sets of the full position-lime-velocity
sub-
matrix
effiIn
ciently
the image
of the brain to be sampled and presented coherently. present framework, a complete of CNS
motion
would
vector with one spatial coordinates.
temporal While
such
data
are
herein,
their
acquisition
650
#{149} Radiology
presented
is feasible
with
Figure
7.
Comparison
(a) T2-weighted pared in b and 3D echo-planar
the
a
sensitized repetition
of cephalocaudal
2D cine
MR image (four R-R intervals/80) c. Lateral to the head are static FVZ
tion of multiple
specify
3D velocity and three
not
b.
method.
2D time
to motion time was
data,
Velocity
profiles
stepped
through
along the section-select four R-R intervals, and
were collected by using a 3-msec cardiac well with the phase-subtraction profiles by using velocities
the 50-msec as positive
frame from and caudal
the data velocities
phase-subtraction shows the location
phantoms. are
obtained
32 gradient
direction. echo time
delay shown
(b) Velocity by means
steps
(±1.0
profiles
obtained
of Fourier
G/cm
2D FVZ. profiles corn-
with
a
transforma-
1±0.0001
T/cm]),
Velocity resolution was 0.5 mm/sec. was 170 msec. Velocity profiles shown the R wave. These FVZ profiles compare
after in c. The
set shown as negative
studies with of velocity
phase-sensitive
in Figure 2. Both (in millimeters
profiles
were
b and c show per second).
derived
cephalic
December
1992
(18,19)
and
nal cord
diseases
involving
the
plexuses as the generator of the force for flow of the fluid and ventricular enlargement. J Neurosurg 1962; 19:405-413.
spi-
(20,21). 2.
APPENDIX In the presence with
zero
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net moment,
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G(t)
=
that
G(t)dt
0,
pulse
4.
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+ -1 fT[ft
v(t’)dt’}}G(t)dt
lion (Al),
That
and
=
--YfoT
[ft
=
-1
w(t)v(t)dt.
IT
Jo
is, the phase
weighted dient-encoding
by using
Equa-
G(t’)dt’]v(t)dt
7. on the
velocity
during
period.
R, Greitz of pulsatile
imaging
discussions
David shy,
sion
with
Mikulis,
Gilberto
Gonzalez,
MD. We thank
Robert
the gra-
8.
Enzmann surement trast cine
grateful
for the support
MD,
9.
and
McKin-
an initial especially ofThomas J. Brady,
ver-
and
Bering
EA.
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20.
Bevington
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Data
reduction
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+
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Bradley
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#{149} 651
