(Stroke. 1999;30:2212-2222.)
© 1999 American Heart Association, Inc.
Original Contributions |
From the Department of Radiology (A.J.de C., J.R., C.B., M.E.M.), Stanford University, Palo Alto, Calif, and the Department of Neurology (J.R.), Friedrich Schiller University, Jena, FRG.
Correspondence to Alex de Crespigny, PhD, Stanford University School of Medicine, Lucas MRS Imaging Center, 1201 Welch Rd, Mail Code 5488, Stanford, CA 94305-5488.. E-mail alex{at}s-word.stanford.edu
| Abstract |
|---|
|
|
|---|
MethodsRats were divided into groups: normoglycemic, hypoglycemic, and hyperglycemic, and those given local tetrodotoxin (TTX) application. Cardiac arrest was effected by intravenous KCl injection during serial high-speed diffusion and blood oxygenationsensitive gradient-recalled echo MRI. Brain DC potential was recorded simultaneously. Serial ADC maps were calculated from the diffusion-weighted data and fitted to a model function to measure the delay between cardiac arrest and rapid ADC decrease.
ResultsThe time of anoxic depolarization indicated by DC change agreed well with the rapid drop in ADC in all groups; both were accelerated with hypoglycemia and delayed by hyperglycemia. A more gradual ADC decline occurred before anoxic depolarization, which was more pronounced in hyperglycemic animals and less pronounced in hypoglycemic animals. Rapid drop in ADC was also delayed by local TTX application. Changes in gradient-recalled echo image intensity were not significantly different among groups.
ConclusionsWhile much of the ADC decrease in ischemia occurs during anoxic depolarization, significant but gradual ADC changes occur earlier that may not be due to a massive loss in ion homeostasis.
Key Words: magnetic resonance imaging cerebral ischemia, global membrane potentials rats
| Introduction |
|---|
|
|
|---|
Recently studies of global15 and focal16 cerebral ischemia using rapid diffusion-weighted line scanning17 in normoglycemic and hyperglycemic rats have found that the initial rapid decrease in ADC is not affected by increased preischemic plasma glucose levels, but that the subsequent ADC decline is prolonged in the hyperglycemic group. These findings are difficult to explain and seem to be in contrast to our own studies of remotely induced focal cerebral ischemia, which showed a delayed ADC decline in hyperglycemic rats compared with normoglycemic controls.18 An earlier study by Hansen19 that measured extracellular potassium concentrations ([K+]e) showed that the time from cardiac arrest to a dramatic rise in [K+]e (indicating anoxic depolarization) is significantly lengthened by hyperglycemia and reduced by hypoglycemia. With this in mind, one might expect similar changes in the ADC curves after cardiac arrest, if cell swelling due to anoxic depolarization is indeed a major mechanism behind the ischemic changes in water diffusion. In the present study, we have performed simultaneous rapid measurements of ADC (using echo-planar imaging), relative blood oxygenation level (from gradient recalled echo images), and brain DC potential (to indicate anoxic depolarization) during cardiac arrestinduced global ischemia at different preischemic plasma glucose levels. Cardiac arrest provides a convenient and simplified cerebral ischemia model, because CBF is known to go to zero at a precisely defined time. Varying plasma glucose levels from hypoglycemia to hyperglycemia have a well-known and measurable effect on the delay to anoxic depolarization. In addition, we performed experiments on normoglycemic animals by application of tetrodotoxin (TTX) topically to the cortex. TTX specifically blocks voltage-dependent sodium channels20 and delays the onset of anoxic depolarization and large-scale loss in ion homeostasis in regions into which the TTX has diffused.21
| Subjects and Methods |
|---|
|
|
|---|
DC potential, blood pressure, temperature, heart rate, and capillary oxygen saturation were recorded and displayed continuously on a Macintosh computer connected to a computerized chart recorder system (MacLab, CB Sciences Inc). In addition, a spare digital line on the scanner, programmed to pulse at the start of each image set, was connected to the data-recording system to allow accurate temporal correlation of the MRI data, the DC potential, and the mean arterial blood pressure (MABP) recordings.
Four groups of rats were defined: group I, normoglycemic (n=7); group II, hypoglycemic (n=5); group III, hyperglycemic (n=5); and group IV, normoglycemic given topical TTX (n=3). Animals in group II were made hypoglycemic by intraperitoneal injection of 3 international units (IU)/kg of insulin 2 hours before the experiment. Animals in group III were made hyperglycemic by intraperitoneal injection of streptozotocin 36 hours before the experiment followed by intravenous injection of 1 mL of 50% glucose solution 1 hour before imaging. For group IV animals, symmetrical apertures were opened in the skull to either side of midline, and the dura was removed in these regions to expose 2 approximately 5-mm-diameter regions of cortical tissue. About 1 hour before scanning, a solution of 10-4 mol/L TTX was applied to the left cortex and NaCl solution was applied to the right cortex. The DC recording electrode was placed ipsilateral to the site of TTX application through a separate burr hole; care was taken to avoid leakage of any fluid onto the electrode. Samples of arterial blood were drawn for blood gas analysis and glucose measurement shortly before initiation of global ischemia inside the magnet.
MR Measurements
MR experiments were performed on a 2.0-T GE/Bruker CSI Omega
system (Bruker Instruments Inc) using a spin-echo echo-planar imaging
(EPI) technique. All studies used a home-built 2.7-cm-diameter
transmit/receive surface coil placed on top of the head. Multislice
T1-weighted gradient-echo scout images were first acquired to localize
the position of the DC electrode by means of its small susceptibility
artifact. Next, the 2 coronal EPI imaging slices were positioned so
that the anterior slice included the DC recording electrode.
ADC was measured with a sequence of 3 diffusion-weighted EPI images
(TE, 50 milliseconds; TR, 2 seconds; field of view, 40 mm; 1.5-mm
slice thickness; 64x64 matrix; 2 coronal slices 3.5 mm apart; 1
average; diffusion weighting along the Z direction; and a
low b value of 30 s/mm2 and a high
b value of 1300 s/mm2 acquired
twice).13 This was followed by gradient-recalled echo
(GRE)-EPI imaging with a 30-millisecond echo time. This set of 4 images
per slice was repeated continuously for up to 25 minutes. After 50
baseline image sets ( approximately 6.7 minutes), cardiac arrest was
induced by an intravenous bolus injection of KCl solution.
Data Processing
Image analysis and display were performed using
custom-written software (MRVision Co). The diffusion-weighted data were
processed to generate serial ADC maps.22 The T2*-weighted
GRE-EPI images were normalized to create images of the percentage
change in image intensity from the baseline. The temporal resolution of
the ADC and GRE measurements was 8 seconds, whereas the nominal spatial
resolution was 1.5x0.63x0.63 mm over 2 coronal slices, with a
nominal voxel volume of 0.6 µL.
As has been pointed out previously,17 an important factor to consider when making such serial diffusion measurements is the stability of the ADC value over time, which determines the smallest ADC change that can be detected. This can be quantified by the coefficient of variation (CV), defined as the standard deviation (SD) of a series of images divided by the mean, times 100%. Therefore, we calculated CV on a pixel-by-pixel basis using the 50 baseline ADC images acquired in each experiment; this indicates the sensitivity for detecting small ADC changes and the stability of the ADC measurements from day to day under the influence of small variations in surface coil positioning, scanner stability, noise, etc.
The ADC versus time curves at each pixel position were analyzed
by fitting a model function to the data to extract relevant
parameters that characterize acute ADC changes after global
ischemia. The model function consisted of 3 segments: an
exponential decay, a more-rapid linear decline, and then another slower
exponential decay to the final ADC value. This function, described in
detail in Figure 1
, was not intended to
model any particular underlying physiological
process, but simply provides a convenient way of describing the data in
terms of a reduced number of parameters. The 3 segments of
the model function were chosen to be the simplest mathematical
description of what we have observed to be the time course of acute ADC
change in ischemia. The model function was fitted to the
measured ADC time course for each pixel position in each slice with the
use of an iterative nonlinear least-squares minimization procedure
(simplex algorithm.23 ). The following subset of the model
parameters was chosen and mapped over both imaging slices
for all animals:
|
1: duration of exponential
segment I (up to the more rapid drop).
dM1: fractional ADC decrease
during exponential segment I (relative to baseline).
c1: time constant of initial
exponential segment I.
M3: final plateau ADC
values (as a fraction of baseline ADC).
The
1 parameter is
particularly important, because it may be compared with the time of the
DC potential change due to anoxic cell membrane depolarization. The
T2*-weighted GRE-EPI image intensity versus time data were
analyzed by measuring regions of interest (ROIs) in different
anatomical areas and fitting the curves to a fifth-order polynomial
function. From the fitted function, values for the time from cardiac
arrest until the maximum signal decrease (
GRE)
and also the relative image intensity at this point
(MGRE) were calculated.
Timing parameters from the ADC and GRE data (measured relative to the start of the MRI scan) were corrected to be relative to the actual time of cardiac arrest by comparing the MABP traces and the scan synchronization pulses recorded on the MacLab machine. The MacLab device records each data point (ie, digitized physiological measurement or scan synchronization pulse) along with the exact time of day (to the nearest millisecond) of that measurement at a rate of 40 values per second for each channel. The time axis for all the plots of the physiological variables was calculated by subtracting the time of day of the first scan synchronization pulse (indicating the start of MRI data acquisition) from the time of day of each of the recorded data points. Subsequent visual observations of these plots of the time point of the sudden MABP drop at cardiac arrest and the time point of DC potential drop gave timing values as offsets from the start of MRI data acquisition. All timing parameters in the present article are shown after subtraction of the time point of sudden MABP drop for each animal.
The parametric maps resulting from the ADC curve-fitting
procedure were further analyzed in 2 ways. First, all pixels
within the brain on the
1 parametric
maps for both imaging slices for which the baseline CV was less than
approximately 5% were collected for groups I through III and displayed
as histograms of the
1 parameter.
Second, ROIs were defined in the cortex, subcortical white matter, deep
gray (basal ganglia) matter, and cortex beneath the DC
recording electrode. These ROIs were transferred to the
calculated parameter images, and the regional average
values of baseline CV, ADC, and the fitting coefficients
1, dM1,
c1, and M3
were measured. The ROI measurements were made on parameter
maps formed by pixel-by-pixel fitting of the model function rather than
by being averaged before the fitting procedure, to reduce the effects
of partial volume averaging on the accuracy of the fitted curves.
For each anatomic region, the measured values for groups II and III
were compared individually with group I by use of Student's
t test. Also, the values for
1
measured in the cortex under the DC electrode were compared with the
time of rapid DC potential drop within each group.
| Results |
|---|
|
|
|---|
MABP and DC Potential
Blood pressure began to decrease immediately after the end
of the KCl injection and took 6.4±2.9 seconds to fall to <10% of the
starting value. Overall, usable DC recordings were obtained
from 13 of the 20 animals studied. In 7 animals, disruption of the DC
trace occurred as a result of electrical interference from the gradient
and radiofrequency pulses of the MRI scanner, despite heavy
filtering, and also as a result of degradation of the electrode-brain
contact during the experiment. Nevertheless, on 65% of the traces, a
rapid drop in DC was observed after cardiac arrest, attributable to
anoxic cell membrane depolarization. The size of this DC change was
4.7±2.4 mV, and it lasted 12±7 seconds. EEG traces were obtained from
13 of the 20 animals studied. Despite much interference, we were able
to estimate the times at which the EEG fell to zero after cardiac
arrest to be 9.0±4.2, 7.7±3.1, 12.5±4.5 seconds for groups I, II,
and III respectively. The difference among the groups was not
statistically significant.
Magnetic Resonance Imaging
The surface coil probe gave images with good signal-to-noise ratio
over the whole brain. The CV of the ADC data measured over the 50
baseline images was consistently <5% except at the very edge
of the brain and at the base of the brain because of increased distance
from the NMR surface coil (which reduces the signal-to-noise ratio in
that region).
Images and curves for a group I animal (normoglycemic) are shown
in Figure 2
. The blood pressure rapidly
fell to zero immediately on KCl injection, whereas the drop in DC
potential associated with anoxic depolarization occurred about 1.5
minutes later. Single-voxel curves are shown from 4 different
locations, as indicated on the ADC map. Figure 2
, plot 1, was
measured from the edge of the brain beneath the DC recording
electrode. As expected, the ADC curve is similar in shape to the model
function shown in Figure 1
, with the steepest part of the decay
coincident with the sudden drop in DC potential. The gradient-echo
signal was noisy here because of the susceptibility artifact from the
electrode. A similarly shaped ADC curve is seen in Figure 2
, plot 2, from another cortical area with the same gradual ADC decline
followed by a rapid drop and a slow final decline. In contrast, the GRE
signal intensity dropped immediately on KCl injection, quickly reached
a minimum value, and then slowly climbed back toward baseline. A voxel
located in the deeper structures (Figure 2
, plot 3) showed a
much more gradual ADC decline without a clear drop; however, the GRE
signal curve is similar to that seen in the cortical region. Another
type of curve seen in a few voxels is shown in Figure 2
, plot 4:
in this voxel, the ADC appeared to drop rapidly on KCl injection (as
indicated by an arrow on the plot) to an intermediate plateau value
followed by another steep decline coincident with the DC change.
However, the GRE signal was the same as in other cortical areas. This
type of ADC curve, with an early, rapid drop, has been reported
previously15 but was observed in only a minority of voxels
in the present study.
|
Diffusion Changes
Although some variation in the ADC traces was observed in
different brain regions, a more striking difference was seen among the
groups. Examples of the ADC versus time curves for each of the 3 groups
are graphed in Figure 3
. The plots are
from a single voxel in a similar location in the cortex of the anterior
slice (contralateral to the recording electrode) in each
animal. The general characteristics of the ADC traces are the same, as
described by the model in Figure 1
; however, the rapid drop in
ADC occurs much earlier in the hypoglycemic animal and much later in
the hyperglycemic animal.
|
Observations regarding the shape of the ADC curves are more accurately
parameterized by the curve-fitting procedure. Figure 3
also shows parametric maps resulting from fitting the
ADC curves for both slices from a representative animal
in each of groups I to III, whereas Table 1
shows ROI values measured from these
maps averaged over all animals in each group. The baseline CV was <5%
in all ROIs measured and did not show any significant variation among
groups. The baseline (preischemic) ADC values were similar
across groups, although they varied anatomically, as illustrated by the
relatively constant pixel values in the ADC maps (Fig. 3
, left)
and similar ROI values in Table 1
. Thus, any potential osmotic
effects of varying plasma glucose concentration on brain-water
diffusion were not significant.
|
The maps of
1 (Figure 3
, right side,
middle images) show markedly lower pixel intensities in group II and
markedly higher intensities in group III compared with normoglycemic
group I, which indicates that the rapid drop in ADC occurs sooner with
hypoglycemia and later with hyperglycemia. In addition, significant
structure is found within each
1 map, with a
tendency towards higher values in pixels containing more white matter
and in areas close to the base of the brain. This finding is supported
by the ROI measurements, which show significantly reduced
1 for hypoglycemic animals in all brain
regions in increased
1 for hyperglycemic
animals. Subcortical white matter (Table 1
, region C) also shows
longer
1 values than gray-matter regions for
all groups. A similar but more striking regional variation of the ADC
profile in global ischemia has also been reported in neonatal
rat brain.12 Most importantly, however, there is good
agreement between the onset of rapid ADC decline indicated by
1 and the DC potential decrease; this holds
true for all 3 groups, as seen in Table 1
, region B.
The other 2 parameters describing the initial gradual
decline in ADC show a trend similar to that of
1 with hypoglycemia and hyperglycemia, as
shown in Table 1
. The values of dM1
were lower in group II and higher in group III, which indicates that
less initial ADC decline precedes the rapid drop in hypoglycemic
animals but that the ADC declines further in hyperglycemic animals
compared with the normoglycemic controls. The
c1 of the initial ADC decline segment is also
lower in group II and higher in group III than in group I, which
indicates a more-rapid initial decay with hypoglycemia and a
more-gradual decay with hyperglycemia. The maps of
M3 shows little variation across the
groups, except for a slight reduction in the cortex of group III.
However, the ROI measurements indicate a small but significantly lower
final relative ADC in the cortex of group II and in all brain regions
of group III compared with group I.
A histogram analysis of the
1 values of all brain voxels in groups I
through III is shown in Figure 4
, which shows our own DC measurements and the previously reported
[K+]e measurements
relative to the distribution of
1 and the
dependence of these quantities on preischemic blood glucose
levels. In groups I and II, the width of the distribution of
1 values is mostly due to anatomic variation
of the time of onset of the rapid ADC decrease; whereas in group III,
the tails of the distribution are increased because of fitting errors.
(In pixels in which the ADC decline does not show a well-defined
"sudden drop," the fitting algorithm generally picks a value of
1 around the midpoint of the time course of
the ADC decline.) The vertical lines passing through each plot indicate
the mean and SD of the time of the DC potential drop measured in the
present study, which agrees well with the onset of anoxic
depolarization as measured previously by Hansen19 and
shown at the top of each graph. The onset of anoxic depolarization, as
indicated by both DC and [K+]e, falls within 1
SD of the means of the distributions of
1 for
each group.
|
GRE Signal Changes
In contrast, the GRE signal intensity curves show the same
rapid drop and gradual return toward baseline in all 3 groups, as can
be seen in the graphs in Figure 3
. Table 2
shows data from the GRE images at the
same ROI locations. Analysis of the GRE-EPI signal intensity
curves showed little variation from group to group. The time between
cardiac arrest and the maximum decrease in signal intensity,
GRE, was around 30 seconds overall and did not
vary significantly between groups (except for slightly decreased
GRE in the cortex in group III). In addition,
the relative signal intensity at the minimum, about 0.92, was not
significantly different between groups or between brain regions.
|
TTX Application
Results from group IV animals, which received TTX, are shown
in Figure 5
. The TTX was applied directly
to the brain surface through an opening in the skull posterior and
ipsilateral to the DC electrode, at approximately the position of the
posterior slice. Some distortions are apparent in the ADC maps; these
are susceptibility artifacts from the aperture in the skull. The
baseline ADC value was not affected by the surgery or the TTX
application (ipsilateral,
0.78x10-3±0.08x10-3
mm2/s versus contralateral,
0.76x10-3±0.06x10-3
mm2/s). However, a local increase in
1 was observed in all animals; it extended
about 2.5 mm into the brain below the site of TTX application
(indicated by arrows in Figure 5
). The mean value of
1 here was 118±4 seconds, which is
significantly longer (P<0.01) than the value measured at
the corresponding contralateral location: 75±7 seconds. The drop in DC
potential occurred at 71±2 seconds. The local delay in rapid ADC
decrease is clearly seen in the plots (Figure 5
, right side),
which were measured from single voxels in animal 1. The ADC trace
measured just below the electrode (Figure 5
, trace 2) shows a
rapid decrease coincident with the DC drop (Figure 5
, trace 1).
In contrast, the ADC drop is delayed by about 50 seconds close to the
site of TTX application (Figure 5
, trace 3) in the cortex of the
posterior slice, whereas at a similar contralateral location (Figure 5
, trace 4), the ADC drop is again coincident with the DC
change. Unlike
1, the size of the
predepolarization ADC decline was the same when measured in a small ROI
in the TTX region (dM1, 0.14±0.04%) and
contralateral cortex (dM1,
0.14±0.03%).
|
| Discussion |
|---|
|
|
|---|
Rapid diffusion measurements of rat brain during permanent global ischemia were fitted to a model function on a pixel-by-pixel basis to extract the major characteristics of the ADC change throughout the brain. In particular, the time point of rapid ADC drop after cardiac arrest was significantly accelerated in hypoglycemic animals but delayed in hyperglycemic animals compared with the normoglycemic control group.
The onset of the rapid change in ADC after cardiac arrest exactly coincides with a sudden drop in DC potential in all groups and is probably due to anoxic cell membrane depolarization.
A significant but more gradual decrease in ADC precedes the rapid drop associated with anoxic depolarization. Both the duration and magnitude of this predepolarization ADC decrease increase with hyperglycemia but decrease with hypoglycemia. These ADC changes are probably due to oncotic water shifts after progressive ion accumulation combined with intracellular lactacidosis as a consequence of anaerobic glycolysis.
Application of 10-4 mol/L TTX to the cortex of normoglycemic animals locally delays rapid ADC decrease and anoxic depolarization by approximately 50 seconds.
The time course of blood-oxygenation changes, as measured with gradient-echo MRI by the blood oxygen leveldependent (BOLD) effect, is not affected by variation in preischemic blood glucose levels and simply reflects the rapid exhaustion of the oxygen store of the blood after cardiac arrest.
The use of the noninvasive MRI methodology provides both the time resolution required to follow the dynamic metabolic changes in ischemia and a spatial resolution good enough to allow measurements from different anatomic regions and to detect spatially variable effects, as in the focal TTX application.
Parameterization of Water Diffusion Changes
The ADC traces for all brain voxels were fitted to a model
function. This function generally fitted well to the data and gave
1 values (time to rapid ADC drop) close to
those determined by visual inspection of the curves. Regional
measurements on the parametric maps of
1 show a significant delay in rapid drop in
ADC in hyperglycemic animals in all brain areas, consistent
with a picture of delayed anoxic depolarization due to increased
substrate availability; conversely, the reduced energy availability
after cardiac arrest in hypoglycemic animals leads to earlier mass cell
depolarization and an earlier rapid drop in ADC (ie, reduced
1). The overall distribution of
1 values for all brain voxels shows the same
effect, with a shift of the distribution towards lower
1 with hypoglycemia and higher
1 with hyperglycemia, as seen in the
histograms in Figure 4
, right side. The width of the
distributions of
1 (see Figure 4
)
reflects the spread in
1 values over the brain
and was mainly due to anatomic variation in the ADC time course during
global ischemia in different brain regions (group III animals
had a wider distribution because of the smoother ADC decay curves,
which caused increased fitting error). Nevertheless, pixels with
1 values close to the median value displayed a
distinct but delayed rapid drop in ADC, which was correctly measured by
the curve-fitting procedure.
Other parameters characterizing the ADC changes for
each pixel were also measured and highlight the aspects of
postischemia water diffusion that change in response to
altered plasma glucose concentration (specifically,
1, dM1, and
c1).
Comparison of Potential Drop in ADC and DC
The onset of potential change in DC was accelerated with
hypoglycemia and delayed with hyperglycemia; the exact timing of the
changes agreed well with the timing of anoxic cell membrane
depolarization determined by previous measurements of
[K+]e19 (see also
Figure 4
). More importantly, the time of decrease in DC was the
same as the time of rapid ADC drop,
1, when
measured from beneath the electrode for groups I through III. This
strongly supports the notion that the rapid decrease in ADC during
ischemia is caused by rapid cell swelling that occurs as a
result of anoxic depolarization.
ADC Changes Preceding Anoxic Depolarization
In addition to the rapid drop in ADC, significant declines in ADC
occurred at a more gradual rate (but clearly preceding anoxic
depolarization). This predepolarization ADC decrease,
dM1, scaled with plasma glucose
concentration from 10% to 14% to 19% (expressed as a percentage of
the baseline ADC value) and occurred more slowly;
c1 varied from 40 to 50 to 260 seconds
in cortex for groups II, I, and III, respectively. Increasing plasma
glucose levels delay anoxic depolarization; however, the degree of ATP
depletion at depolarization has been shown to remain constant at about
30% of baseline.24 The slowed ATP reduction in
hyperglycemia may prolong ion pump activity and result in a slowed
accumulation of [K+]e and
a slower rate of water shift into the cells. This may explain the
slower predepolarization ADC reductions (longer
c1) as the plasma glucose level
increases. It may also explain the larger
dM1 value: increased plasma glucose
concentration may simply allow more time (longer
1) for osmotically driven water to enter the
cells, so that the total accumulation of intracellular water at the
point of anoxic depolarization is greater, although this accumulation
seems to occur more slowly.
Although predepolarization K+ leakage may be the cause of some gradual water shifts into the cells, the slow change in [K+]e is still much smaller than the rapid increase that occurs with membrane depolarization.19 25 Hyperglycemia is known to dramatically increase the accumulation of lactate to the point of anoxic depolarization,24 and this suggests that an additional cause of water shift into the cells may be a rise in the intracellular osmolarity in the vicinity of anaerobic glycolysis and, consequently, lactacidosis.26 Lactacidosis is known to increase cell volume,27 and rapid lactate increase has been measured soon after ischemia in vivo.28 In dynamic spectroscopy and diffusion measurements in cat brain with 36-second time resolution, Decanniere et al10 found that decreased diffusion coincided with increased lactate concentration for about the first 2 to 2.5 minutes after cardiac arrest, after which the diffusion decreased faster, presumably due to anoxic depolarization. Interestingly, in a previous study that compared ADC and metabolic changes in a rat model of focal ischemia,29 tissue acidosis was shown to correspond to an ADC reduction threshold of 10%, whereas ATP depletion occurred at a larger ADC reduction of at least 23% from baseline. The fact that 2 different thresholds seem to exist for ADC decrease due to acidosis and energy failure is in line with the biphasic nature of the time-resolved ADC changes in our global ischemia model, although the size of the ADC changes is somewhat larger in our model. Although lactacidosis is unlikely to be the only cause of slow decrease in ADC before anoxic depolarization (hyperglycemia accelerates the rate of acid accumulation,24 but we observed a slower rate of ADC change), it may well be a significant contributor to the total intracellular water shifts that precede membrane depolarization.
Comparison With Earlier Studies
The findings of this study appear to be inconsistent with
earlier work by Huang et al,15 16 which showed large ADC
changes that preceded anoxic depolarization. This
inconsistency is not easy to explain, but it may be related
to 2 differences in the methods used. First, Huang and
colleagues17 used a 1-dimensional line-scan
method17 at 4.7 T with pixels positioned reproducibly at
particular anatomical sites but did not measure DC potential in the
same animals. They relied instead on literature values for the timing
of anoxic depolarization. The present study at 2 T used multislice
echo-planar imaging to obtain cross-sectional views of the brain with a
5-fold smaller voxel volume than in the earlier works and measured DC
potential simultaneously. This mapping method demonstrated
variation in the exact timing of the rapid drop in ADC, both in
different brain regions and among individual animals, and it was
important to compare the DC potential traces with the ADC profiles
measured close to the recording electrode. Thus, regional
variation among the ADC changes combined with the 5-fold larger voxels
used in the work of Huang et al17 (giving a greater
chance of partial volume averaging) may account for some of the
apparent discrepancy between the studies.
In the present study, we occasionally observed a 5% to 10% drop
in ADC within 30 seconds of cardiac arrest (Figure 2
, right,
trace 4) in only a few pixels and in only some animals. This
observation is similar to the group mean ADC change previously
reported.15 One possible explanation is that the very
early ADC changes may be partly caused by magnetic susceptibility
effects30 from increased deoxyhemoglobin in pixels
containing veins or larger venules. (Our susceptibility-weighted GRE
data also showed a rapid drop within 30 seconds of cardiac arrest.)
Such susceptibility effects would be more pronounced with larger voxels
and a higher magnetic field.
The second important difference between this work and earlier studies by Huang et al is the method of data analysis. Previously, the time of initial ADC decline was defined as the time point at which ADC fell to <2 SD of the baseline value,15 and this was not found to vary between normal and hyperglycemic animals. In the present study, we used a model function constructed by following observations of the shape of typical ADC curves during cardiac arrest. In this model, ADC begins to decline immediately after KCl injection, as a slowly decaying exponential function. The time point at which ADC decline is first detected depends on the noise in the baseline ADC value, which is a strong function of the experimental parameters. Therefore, we chose to characterize the ADC curves in terms of more obvious features such as the rapid drop, although we acknowledge that ADC probably does begin to decline, slowly, immediately after cardiac arrest.
TTX Application
TTX application caused delayed drop in ADC only in a localized
region of cortex beneath the application site. Again, this finding
supports the hypothesis that the rapid drop in ADC is caused by anoxic
depolarization that is locally delayed in the area into which TTX has
diffused in the interval between application and imaging. The time
point of rapid ADC drop,
1, was similar to the
time of DC change in the contralateral hemisphere (NaCl application) as
before. One exception to this was the third animal in group IV, which
showed decreased
1 anterior to the site of the
trepanation for TTX application. The cause of this is uncertain but may
be due to a degree of local ischemia resulting from the
surgery.
Because the main effect of TTX is the blockade of sodium channels, it is likely that reduced sodium influx in the region of TTX infusion reduces the amount of ATP used by Na+-K+-ATPase, which thus reduces the overall rate of ATP depletion so that it takes longer to reach the critical threshold of 30% ATP level for anoxic depolarization. Another effect of TTX is the suppression of neuronal activity, which results in reduced glycolysis and a reduction in lactic acid production.21 Both reduced Na+ influx and reduced lactate production may slow the rate of water shift into the cells. The observation that the size of gradual ADC decrease (dM1) is the same with or without TTX infusion, despite the fact that anoxic depolarization is significantly delayed by TTX, indicates that the rate of ADC decline is reduced, consistent with a slower shift of water into the cells.
Blood Oxygenation Changes
Gradient-echo MRI has been shown to be uniquely sensitive to
changes in microvascular blood oxygenation in the
brain.31 32 This BOLD image contrast arises as a result of
the paramagnetic nature of deoxyhemoglobin.33 Increased
deoxyhemoglobin concentration in tissue leads to reduced T2* relaxation
times34 and, hence, signal decrease in a GRE MRI. During
ischemia, a rapid increase in deoxyhemoglobin concentration
occurs, which causes immediate signal drop in T2*-weighted image
intensity in global35 and focal
ischemia,36 as a result of the BOLD effect. In
general, the BOLD effect is a complex function of arterial
blood oxygenation, cerebral blood flow, cerebral blood
volume, and cerebral oxygen utilization. In our study, the GRE signal
intensity dropped to a minimum of about 92% within 30 seconds of
cardiac arrest and then slowly returned to baseline. Because CBF is
zero, cells will continue to extract oxygen from the blood until
virtually all the hemoglobin is deoxygenated (after
approximately 30 seconds). Thus, the time from arrest to this maximum
GRE signal change simply reflects the delay until the start of
anaerobic glycolysis.37
Once all of the hemoglobin in the blood has been deoxygenated, the slow return of GRE signal intensity may be explained by a gradual decrease in CBV as blood is forced out of the cranial cavity by hydrostatic pressure (due to the lack of incoming perfusion pressure). The available oxygen in the blood remaining in the brain after cardiac arrest is used up so rapidly that there is no time for the effects of differing plasma glucose concentration to become apparent. Thus, no variation in the BOLD signal would be expected or was observed among groups I , II, and III.
Magnetic Resonance Imaging
High-speed MRI provides sufficient temporal resolution to
follow the changes in water diffusion and hemodynamics
during global ischemia. The data clearly show the importance of
imaging studies, because significant variation was observed between the
ADC time courses on individual slices, most notably between voxels
containing mostly gray matter and voxels containing mostly white
matter. In particular, imaging allows for measurement of spatially
varying effects such as that observed in animals receiving topical TTX
and will be important in future studies that involve focal cerebral
ischemia.
| Acknowledgments |
|---|
Received April 26, 1999; revision received June 29, 1999; accepted July 21, 1999.
| References |
|---|
|
|
|---|
2.
Sorensen AG, Buonanno FS, Gonzalez RG, Schwamm LH, Lev
MH, Huang-Hellinger FR, Reese TG, Weisskoff RM, Davis TL, Suwanwela N,
Can U, Moreira JA, Copen WA, Look RB, Finklestein SP, Rosen BR,
Koroshetz WJ. Hyperacute stroke: evaluation with combined
multisection diffusion- weighted and hemodynamically
weighted echo-planar MR imaging. Radiology. 1996;199:391401.
3.
Marks MP, de Crespigny A, Lentz D, Enzmann DR, Albers
GW, Moseley ME. Acute and chronic stroke: navigated spin-echo
diffusion-weighted MR imaging. Radiology. 1996;199:403408.
Published erratum appears in Radiology. 1996;200:289.
4. Moseley ME, Cohen Y, Mintorovitch J, Chileuitt L, Shimizu H, Kucharczyk J, Wendland MF, Weinstein PR. Early detection of regional cerebral ischemia in cats: comparison of diffusion- and T2-weighted MRI and spectroscopy. Magn Reson Med. 1990;14:330346.[Medline] [Order article via Infotrieve]
5. Helpern J, Ordidge R, Knight R. The effect of cell membrane water permeability on the apparent diffusion coefficient of water. Paper presented at: Society of Magnetic Resonance in Medicine, 11th Annual Meeting; 1992; Berlin, Germany: 1201.
6. Moseley ME, Kucharczyk J, Mintorovitch J, Cohen Y, Kurhanewicz J, Derugin N, Asgari H, Norman D. Diffusion-weighted MR imaging of acute stroke: correlation with T2-weighted and magnetic susceptibility-enhanced MR imaging in cats. AJNR. 1990;11:423429.[Abstract]
7. Knight R, Dereski M, Helpern J, Ordidge R, Chopp M. Magnetic resonance imaging assessment of evolving focal cerebral ischemia. Stroke. 1994;25:12521262.[Abstract]
8.
van Bruggen N, Cullen BM, King MD, Doran M, Williams
SR, Gadian DG, Cremer JE. T2- and diffusion-weighted magnetic resonance
imaging of a focal ischemic lesion in rat brain.
Stroke. 1992;23:576582.
9. Davis D, Ulatowski J, Eleff S, Izuta M, Mori S, Shungu D, van Zijl P. Rapid monitoring of changes in water diffusion coefficients during reversible ischemia in cat and rat brain. Magn Reson Med. 1994;31:454460.[Medline] [Order article via Infotrieve]
10. Decanniere C, Eleff S, Davis D, van Zijl PC. Correlation of rapid changes in the average water diffusion constant and the concentrations of lactate and ATP breakdown products during global ischemia in cat brain. Magn Reson Med. 1995;34:343352.[Medline] [Order article via Infotrieve]
11. Pierpaoli C, Alger JR, Righini A, Mattiello J, Dickerson R, Des Pres D, Barnett A, Di Chiro G. High temporal resolution diffusion MRI of global cerebral ischemia and reperfusion. J Cereb Blood Flow Metab. 1996;16:892905.[Medline] [Order article via Infotrieve]
12. van der Toorn A, Sykova E, Dijkhuizen RM, Vorisek I, Vargova L, Skobisova E, van Lookeren Campagne M, Reese T, Nicolay K. Dynamic changes in water ADC, energy metabolism, extracellular space volume, and tortuosity in neonatal rat brain during global ischemia. Magn Reson Med. 1996;36:5260.[Medline] [Order article via Infotrieve]
13. Röther J, de Crespigny A, D'Arceuil H, Moseley ME. MRI detection of cortical spreading depression immediately after focal ischemia in the rat. J Cereb Blood Flow Metab. 1996;16:214220.[Medline] [Order article via Infotrieve]
14.
Benveniste H, Hedlund LW, Johnson GA. Mechanism of
detection of acute cerebral ischemia in rats by
diffusion-weighted magnetic resonance microscopy. Stroke. 1992;23:746754.
15. Huang NC, Yongbi MN, Helpern JA. The influence of preischemic hyperglycemia on acute changes in the apparent diffusion coefficient of brain water following global ischemia in rats. Brain Res. 1997;757:139145.[Medline] [Order article via Infotrieve]
16. Huang NC, Yongbi MN, Helpern JA. The influence of preischemic hyperglycemia on acute changes in brain water ADCw following focal ischemia in rats. Brain Res. 1998;788:137143.[Medline] [Order article via Infotrieve]
17. Yongbi MN, Huang NC, Branch CA, Helpern JA. The application of diffusion-weighted line-scanning for the rapid assessment of water ADC changes in stroke at high magnetic fields. NMR Biomed. 1997;10:7986.[Medline] [Order article via Infotrieve]
18. Els T, Rother J, Beaulieu C, de Crespigny A, Moseley M. Hyperglycemia delays terminal depolarization and enhances repolarization after peri-infarct spreading depression as measured by serial diffusion MR mapping. J Cereb Blood Flow Metab. 1997;17:591595.[Medline] [Order article via Infotrieve]
19. Hansen AJ. The extracellular potassium concentration in brain cortex following ischemia in hypo- and hyperglycemic rats. Acta Physiol Scand. 1978;102:324329.[Medline] [Order article via Infotrieve]
20. Prenen GH, Go KG, Postema F, Zuiderveen F, Korf J. Cerebral cation shifts in hypoxic-ischemic brain damage are prevented by the sodium channel blocker tetrodotoxin. Exp Neurol. 1988;99:118132.[Medline] [Order article via Infotrieve]
21. Xie Y, Dengler K, Zacharias E, Wilffert B, Tegtmeier F. Effects of the sodium channel blocker tetrodotoxin (TTX) on cellular ion homeostasis in rat brain subjected to complete ischemia. Brain Res. 1994;652:216224.[Medline] [Order article via Infotrieve]
22. Latour L, Hasegawa Y, Formato J, Fisher M, Sotak C. Spreading waves of decreased diffusion coefficient after cortical stimulation in the rat brain. Magn Reson Med. 1994;32:189198.[Medline] [Order article via Infotrieve]
23. Press WH, Flanner BP, Teukolsky SA, Vetterling WT. Minimization or maximumization of functions. In: Numerical Recipes in C: the Art of Scientific Computing. New York, NY: Cambridge University Press. 1988:chap 10.
24. Ekholm A, Katsura K, Siesjo BK. Coupling of energy failure and dissipative K+ flux during ischemia: role of preischemic plasma glucose concentration. J Cereb Blood Flow Metab. 1993;13:193200.[Medline] [Order article via Infotrieve]
25. Hansen AJ, Zeuthen T. Extracellular ion concentrations during spreading depression and ischemia in the rat brain cortex. Acta Physiol Scand. 1981;113:437445.[Medline] [Order article via Infotrieve]
26. Matsuoka Y, Hossmann KA. Cortical impedance and extracellular volume changes following middle cerebral artery occlusion in cats. J Cereb Blood Flow Metab. 1982;2:466474.[Medline] [Order article via Infotrieve]
27. Staub F, Baethmann A, Peters J, Weigt H, Kempski O. Effects of lactacidosis on glial cell volume and viability. J Cereb Blood Flow Metab. 1990;10:866876.[Medline] [Order article via Infotrieve]
28. Bizzi A, Righini A, Turner R, Le Bihan D, Bockhorst KH, Alger JR. Imaging focal reperfusion injury following global ischemia with diffusion-weighted magnetic resonance imaging and 1H-magnetic resonance spectroscopy. Magn Reson Imaging. 1996;14:581592.[Medline] [Order article via Infotrieve]
29. Hoehn-Berlage M, Norris DG, Kohno K, Mies G, Leibfritz D, Hossmann K-A. Evolution of regional changes in apparent diffusion coefficient during focal ischemia of rat brain: the relationship of quantitative diffusion NMR imaging to reduction in cerebral blood flow and metabolic disturbances. J Cereb Blood Flow Metab. 1995;15:10021011.[Medline] [Order article via Infotrieve]
30. Does MD, Zhong J, Gore JC. In vivo measurement of ADC change due to intravascular susceptibility variation. Magn Reson Med. 1999;41:236240.[Medline] [Order article via Infotrieve]
31. Ogawa S, Lee T, Barrere B. The sensitivity of magnetic resonance image signals of a rat brain to changes in the cerebral venous blood oxygenation. Magn Reson Med. 1993;29:205210.[Medline] [Order article via Infotrieve]
32.
Ogawa S, Lee T-M, Kay A, Tank D. Brain magnetic
resonance imaging with contrast dependent on blood
oxygenation. Proc Natl Acad Sci U S A. 1990;87:98689872.
33.
Pauling L, Coryell CD. The magnetic properties and
structure of hemoglobin, oxyhemoglobin and carbonmonoxyhemoglobin.
Proc Natl Acad Sci U S A. 1936;22:210216.
34. Thulborn K, Waterton J, Matthews P, Radda G. Oxygenation dependence of the transverse relaxation time of water protons in whole blood at high field. Biochem Biophys Acta. 1982;714:265270.[Medline] [Order article via Infotrieve]
35. Turner R, Bizzi A, Despres D, Alger J, Di Chiro G. Dynamic gradient-echo echo-planar imaging of deoxygenation in reversible global ischemia of cat brain. In: Program and abstracts of the Society of Magnetic Resonance in Medicine, Tenth Annual Scientific Meeting and Exhibition; August 1016, 1991; San Francisco, Calif. Abstract, p 1032.
36. de Crespigny AJ, Wendland MF, Derugin N, Kozniewska E, Moseley ME. Real-time observation of transient focal ischemia and hyperemia in cat brain. Magn Reson Med. 1992;27:391397.[Medline] [Order article via Infotrieve]
37. Siesjö BK. Ischemia. In: Brain Energy Metabolism. New York, NY: John Wiley and Sons; 1978:chap 15.
Max-Planck-Institute for Neurological Research, Cologne, Germany
| Introduction |
|---|
|
|
|---|
This study is a demonstration of state-of-the-art experimental design. While many experimental studies rely exclusively on MRI signal changes for indirect interpretation, here the combination of MR data with independent techniques provides further information for the analysis of the pathological situation. But more importantly, it is this combination of MRI with independent, established techniques that allows evaluation of the observed MR changes and interpretation of them in terms of physiological alterations. It was only the simultaneous DC recording that enabled the authors to solve and explain the seeming discrepancy of their MRI results with those of Huang and colleagues.2
Upon cardiac arrest the authors described a biphasic behavior of the ADC change with a slight ADC decrease followed by a rapid and pronounced ADC drop. Via DC potential, recording the rapid ADC drop was convincingly related to the anoxic depolarization, in full temporal agreement with an earlier study by Hansen,3 who showed that the delay between cardiac arrest and increase of extracellular potassium concentration, as an indicator for anoxic depolarization, was increased by hyperglycemia but reduced by hypoglycemia.
The first phase of slight ADC alteration described by the authors was less pronounced in hypoglycemia animals. This gradual ADC decrease, preceding the rapid drop associated with anoxic depolarization, is interpreted as resulting from the intracellular lactacidosis as a consequence of anaerobic glycolysis. Its presence before the rapid ADC drop is rightly assumed to be due to increased substrate availability, thus supporting the energy metabolism and thereby delaying the breakdown of ion homeostasis. Interestingly, a similar amount of ADC decrease has been described in an earlier investigation on focal cerebral ischemia4 for the acidic but viable periphery of the ischemic territory. It would be of great interest to pursue this aspect further, as it appears to indicate a general correlation of slight ADC change with viable tissue of a disturbed metabolism.
Received April 26, 1999; revision received June 29, 1999; accepted July 21, 1999.
| References |
|---|
|
|
|---|
2. Huang NC, Yongbi MN, Helpern JA. The influence of preischemic hyperglycemia on acute changes in the apparent diffusion coefficient of brain water following global ischemia in rats. Brain Res.. 1997;757:139145.
3. Hansen AJ. The extracellular potassium concentration in brain cortex following ischemia in hypo- and hyperglycemia rats. Acta Physiol Scand.. 1978;102:324329.
4. Hoehn-Berlage M, Norris DG, Kohno K, Mies G, Leibfritz D, Hossmann K-A. Evolution of regional changes in apparent diffusion coefficient during focal ischemia of rat brain: the relationship of quantitative diffusion NMR imaging to reduction in cerebral blood flow and metabolic disturbances. J Cereb Blood Flow Metab.. 1995;15:10021011.
This article has been cited by other articles:
![]() |
J. Bottcher, A. Kunze, C. Kurrat, P. Schmidt, G. Hagemann, O.W. Witte, and W.A. Kaiser Localized Reversible Reduction of Apparent Diffusion Coefficient in Transient Hypoglycemia-Induced Hemiparesis Stroke, March 1, 2005; 36(3): e20 - e22. [Abstract] [Full Text] [PDF] |
||||
![]() |
R. Leigh, O. O. Zaidat, M. F. Suri, G. Lynch, S. Sundararajan, J. L. Sunshine, R. Tarr, W. Selman, D. M.D. Landis, and J. I. Suarez Predictors of Hyperacute Clinical Worsening in Ischemic Stroke Patients Receiving Thrombolytic Therapy Stroke, August 1, 2004; 35(8): 1903 - 1907. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. Fiehler Editorial Comment--ADC and Metabolites in Stroke: Even More Confusion About Diffusion? Stroke, July 1, 2003; 34 (7): e87 - e88. [Full Text] [PDF] |
||||
![]() |
T. Doczi, A. Schwarcz, T. Kucinski, O. Vaterlein, J. Fiehler, B. Eckert, H. Zeumer, V. Glauche, J. Rother, E. Klotz, et al. Correlation of Apparent Diffusion Coefficient and Computed Tomography Density in Acute Ischemic Stroke * Response Stroke, May 1, 2003; 34 (5): e17 - e18. [Full Text] [PDF] |
||||
![]() |
G.-F. Tian and A. J. Baker Protective Effect of High Glucose Against Ischemia-Induced Synaptic Transmission Damage in Rat Hippocampal Slices J Neurophysiol, July 1, 2002; 88(1): 236 - 248. [Abstract] [Full Text] [PDF] |
||||
![]() |
T. Kucinski, O. Vaterlein, V. Glauche, J. Fiehler, E. Klotz, B. Eckert, C. Koch, J. Rother, and H. Zeumer Correlation of Apparent Diffusion Coefficient and Computed Tomography Density in Acute Ischemic Stroke Stroke, July 1, 2002; 33(7): 1786 - 1791. [Abstract] [Full Text] [PDF] |
||||
![]() |
T. A. Kent, V. M. Soukup, and R. H. Fabian Heterogeneity Affecting Outcome From Acute Stroke Therapy: Making Reperfusion Worse Stroke, October 1, 2001; 32(10): 2318 - 2327. [Abstract] [Full Text] [PDF] |
||||
![]() |
S. Condette-Auliac, S. Bracard, R. Anxionnat, E. Schmitt, J. C. Lacour, M. Braun, J. Meloneto, A. Cordebar, L. Yin, and L. Picard Vasospasm After Subarachnoid Hemorrhage: Interest in Diffusion-Weighted MR Imaging Stroke, August 1, 2001; 32(8): 1818 - 1824. [Abstract] [Full Text] [PDF] |
||||
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Stroke Home | Subscriptions | Archives | Feedback | Authors | Help | AHA Journals Home | Search Copyright © 1999 American Heart Association, Inc. All rights reserved. Unauthorized use prohibited. |