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Clinical and Radiological Correlates of Reduced Cerebral Blood Flow Measured Using Magnetic Resonance Imaging
Vincent N. Thijs, MD;
Alessandro Adami, MD;
Tobias Neumann-Haefelin, MD;
Michael E. Moseley, PhD;
Gregory W. Albers, MD
Arch Neurol. 2002;59:233-238.
ABSTRACT
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Background Methods for determining cerebral blood flow (CBF) using bolus-tracking
magnetic resonance imaging (MRI) have recently become available. Reduced apparent
diffusion coefficient (ADC) values of brain tissue are associated with reductions
in regional CBF in animal stroke models.
Objectives To determine the clinical and radiological features of patients with
severe reductions in CBF on MRI and to analyze the relationship between reduced
CBF and ADCs in acute ischemic stroke.
Design Case series.
Setting Referral center.
Methods We studied 17 patients with nonlacunar acute ischemic stroke in whom
perfusion-weighted imaging (PWI) and diffusion-weighted imaging (DWI) were
performed within 7 hours of symptom onset. A PWI-DWI mismatch of more than
20% was required. We compared patients with ischemic lesions that had CBF
of less than 50% relative to the contralateral hemisphere with patients with
lesions that had relative CBF greater than 50%. Characteristics analyzed included
age, time to MRI, baseline National Institutes of Health Stroke Scale score,
mean ADC, DWI and PWI lesion volumes, and 1-month Barthel Index score.
Results Patients with low CBF (n = 5) had lower ADC values (median, 430 x
10 -6 mm2/s vs 506 x 10 -6 mm2/s; P = .04),
larger DWI volumes (median, 41.8 cm3 vs 14.5 cm3; P = .001) and larger PWI lesions as defined by the mean
transit time volume (median, 194.6 cm3 vs 69.3 cm3; P = .01), and more severe baseline National Institutes
of Health Stroke Scale scores (median, 15 vs 9; P
= .02).
Conclusion Ischemic lesions with severe CBF reductions, measured using bolus-tracking
MRI, are associated with lower mean ADCs, larger DWI and PWI volumes, and
higher National Institutes of Health Stroke Scale scores.
INTRODUCTION
ALTHOUGH CEREBRAL blood flow (CBF) has traditionally been measured using
positron emission tomography, single-photon emission computed tomography,
or xenon computed tomography, there is great interest in developing magnetic
resonance imaging (MRI) methods to determine CBF in patients with acute ischemic
stroke. Perfusion-weighted imaging (PWI) using MRI seems more attractive than
traditional methods because of its widespread availability and its ability
to be combined with other MRI techniques, such as diffusion-weighted imaging
(DWI), magnetic resonance angiography, or magnetic resonance spectroscopy.1-3 Within minutes, an integrated
MRI examination can provide information on the extent of cytotoxic edema on
DWI, the changes in metabolites via magnetic resonance spectroscopy, and the
state of the vasculature using magnetic resonance angiography. It is thought
that the information provided by MRI will benefit clinical trial design and
individual patient management.4
Diffusion-weighted imaging assesses the mobility of water protons within
brain parenchyma. Extensive animal and human experimental data3, 5-6
show that diffusion of protons is restricted after ischemic stroke. This reduction
of water movement is probably due to cytotoxic edema associated with energy
failure caused by reductions in CBF. The apparent diffusion coefficient (ADC)
is a quantitative parameter that reflects the degree of mobility of water
within brain parenchyma. Experimental data7-8
show an association between reductions in CBF and reductions in the ADC. A
regional correspondence is found between areas with the most severe CBF reduction
and areas with the lowest ADC. Regions with less severe reductions in CBF
show either normal ADC or only mild reductions. For example, Dijkhuizen et
al9 reported that after a 1-hour middle cerebral
artery (MCA) occlusion in rats, the ADC was severely reduced in areas where
CBF was reduced to less than 20% of normal. A modest reduction or no reduction
at all was observed in areas where CBF was reduced to 40% to 60% of normal.9
Bolus-tracking MRI is the most commonly used method of obtaining PWI
in clinical situations. After administration of a bolus of intravenous contrast,
a series of multislice T2-weighted images covering the brain are acquired.
The loss of signal intensity induced by gadolinium on the T2-weighted images
is proportional to the concentration of intravenous contrast.1
Curves that reflect the concentration of gadolinium on a pixel-by-pixel basis
are then analyzed to generate maps of CBF, cerebral blood volume (CBV), and
mean transit time (MTT). Methods for quantitatively determining CBF using
bolus-tracking MRI have been proposed based on the indicator dilution theory
for nondiffusible tracers.2 These methods typically
perform a deconvolution of the tissue concentration time curve with the arterial
input function.10-12
Ostergaard et al13-14 proposed
a nonparametric singular value decomposition (NP-SVD) approach. Although direct
validation using positron emission tomography would be desirable, practical
difficulties in obtaining hyperacute positron emission tomography studies
and MRI make this difficult. We attempted to validate the CBF measurement
indirectly by comparing CBF with other accepted and easily measured markers
of stroke severity.
Clinical studies15-16 have
shown a high correlation between the volumes of DWI and PWI lesions and clinical
impairment scales such as the National Institutes of Health Stroke Scale (NIHSS).
These volumes also seem to partially predict functional outcome.17
Because the primary consequence of a vessel obstruction due to clot is a reduction
in CBF, we studied the impact of a severe reduction in CBF, measured using
dynamic susceptibility contrast imaging, on the size of DWI and PWI lesions
and on clinical stroke severity and functional outcome. We tested the hypothesis
that in acute human ischemic stroke, low CBF values were associated with lower
ADC values, larger DWI and PWI lesion volumes, and higher baseline NIHSS scores.
PATIENTS AND METHODS
PATIENTS
We retrospectively identified patients with acute ischemic stroke entered
into the Stanford Stroke Center database in whom DWI and PWI were obtained
within 7 hours of symptom onset. Patients had to have an acute PWI lesion
volume (defined as the MTT lesion, see the "Postprocessing of Perfusion Images"
section) that was 20% larger than the volume of the acute DWI lesion. We excluded
patients without a PWI-DWI mismatch because it is thought that these patients
have spontaneous or treatment-induced reperfusion, and their PWI variables
do not reflect values before reperfusion. Treatment with recombinant tissue
plasminogen activator and enrollment in trials of neuroprotective agents vs
placebo were allowed. The following clinical characteristics were recorded:
age, NIHSS score, time from symptom onset to MRI, and functional outcome measured
using the Barthel Index 1 month after stroke onset. Patients who died during
the first month of follow-up were assigned a Barthel Index score of zero.
The study was approved by the Stanford University institutional review board.
MAGNETIC RESONANCE IMAGING
Magnetic resonance imaging was performed using echoplanar imaging on
a 1.5-T magnet (Signa; General Electric, Milwaukee, Wis). Multislice whole-brain
DWI was performed using the following variables: 16 slices; repetition time,
8100 milliseconds; echo time, 110 milliseconds; slice thickness, 5 mm; gap,
2.5 mm; matrix, 128 x 128; and field of view, 24 cm. B values were 0
and 829 s/mm2. Diffusion-weighted images were acquired in the x,
y, and z directions. The x-, y-, and z-direction DWI scans were averaged to
minimize hyperintensities due to anisotropic water diffusion. Echoplanar diffusion
images were processed to generate average (trace) ADC maps using a computer
program (MRVision; MRVision Co, Winchester, Mass).
Perfusion-weighted imaging was performed using dynamic susceptibility
contrast-enhanced MRI. Gradient-echo, single-shot echoplanar imaging was used
during injection of 20 mL of gadolinium (0.2 mmol/kg). Perfusion-weighted
imaging acquisition values were repetition time, 2000 milliseconds; and echo
time, 60 milliseconds, with 40 time points obtained over 12 slices. Other
variables were the same as for DWI. The 12 PWI slices were obtained at the
same level as the 12 central slices on the DWI scans. The raw images were
transferred to a computer workstation (Sun Ultrasparc; Sun Microsystems, Palo
Alto, Calif) for further analysis.
POSTPROCESSING OF PERFUSION IMAGES
Calculation of relative MTT, relative CBF, and relative CBV maps was
performed using the model-independent NP-SVD method described by Ostergaard
et al.13-14 The tissue concentration
curve was deconvolved with the arterial input function using SVD. We determined
the arterial input function by manually choosing 5 to 8 pixels over the MCA
of the unaffected hemisphere. These pixels had to show an earlier increase
in intensity and a 3- to 9-fold larger peak on the tissue concentration time
curve compared with the curves obtained from normal brain parenchyma. To determine
relative CBV, the tissue concentration over time curve was numerically integrated
between bolus arrival and the moment at which the tissue concentration curve
in affected tissue had again completely or almost completely returned to baseline.
Mean transit time was calculated from these measurements as CBV/CBF according
to the central volume principle.
VOLUMETRICS AND INTENSITY MEASUREMENTS
Lesion volume measurements were performed by manually outlining the
lesions on the DWIs and the MTT maps. The regions of interest (ROIs) identified
on the MTT maps were transferred to the CBF and CBV maps (Figure 1). Mean intensities were measured in the MTT, CBV, and CBF
ROIs and compared with reference values. The reference MTT value was obtained
by manually outlining a large part of the contralateral MCA on 3 central slices
of the MCA and calculating the mean intensity within these regions. The same
ROIs were chosen to determine the reference CBV and CBF values. To obtain
lesion volumes, the abnormal areas on the images were summed and multiplied
with the slice thickness plus interslice gap.
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Figure 1. Hemodynamic maps from a patient
who underwent imaging 5 hours after stroke onset and who had a National Institutes
of Health Stroke Scale score of 22. The hemodynamic map was outlined on the
mean transit time map (A) and transferred to the cerebral blood flow (B) and
cerebral blood volume (C) maps. The area of increase on the cerebral blood
flow and cerebral blood volume maps is not included in the area with an apparent
diffusion coefficient decrease below 550 x 10 -6mm2/s (D), representing an overlay of the apparent diffusion coefficient
lesion from Figure 2 onto the cerebral blood flow map.
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To test interobserver variability, 2 observers (V.N.T., A.A.) independently
drew ROIs in 17 randomly sampled MTT images and measured their mean intensity.
The interobserver reliability of the measurement of the intensity of the MTT
and the volume of the MTT lesions was excellent (r>0.95).
The DWI lesion volumes were measured by 2 independent observers (V.N.T., A.A.)
and were averaged. High interobserver reliability was found (r>0.95).
ADC MEASUREMENTS
The abnormality outlined on the DWIs was subsequently transferred to
the corresponding ADC map (Figure 2).
The ADC550 was determined by identifying all the pixels below the
threshold of 550 x 10 -6 mm2/s
and calculating the mean ADC value within these pixels. The threshold of 550
x 10 -6 mm2/s corresponds approximately
to a 40% reduction in the normal ADC (880 x 10-6 mm2/s).18 The ADC550 was ranked in ascending order. Patients without DWI lesions or in whom
no pixels were found below the threshold of 550 x 10 -6 were assigned the highest rank. Nonparametric statistics, based on
rank order, were used for all statistical calculations.
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Figure 2. Diffusion-weighted imaging and
apparent diffusion coefficient (ADC) maps from the patient shown in Figure
1. A, Diffusion-weighted imaging map showing a right middle cerebral artery
distribution lesion. B, An ADC map with the region of interest transferred
from part A. C, An ADC map. Highlighted pixels within the region of interest
represent pixels with an ADC value of less than 550 x 10 -6mm2/s (mean, 342 x 10 -6mm2/s).
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STATISTICS
We compared age, time to MRI, NIHSS scores, initial DWI volumes, initial
PWI volumes, and the mean ADC as well as the absolute mismatch volume, CBF,
and CBV between patients with severe reductions in CBF (CBF <50%) and patients
with moderate to mild CBF reductions (CBF >50%). The Mann-Whitney test was
used for these calculations. We correlated the total distribution of CBF with
the same clinical and radiological characteristics using the Spearman rank
correlation coefficient. Statistical analysis was performed using a computer
program (SPSS 10.0; SPSS Inc, Chicago, Ill).
RESULTS
Twenty-nine patients were identified who underwent DWI and PWI within
7 hours of symptom onset between August 1, 1996, and August 1, 2000. Eight
patients did not have a PWI-DWI mismatch. In 4 patients, poor image quality
due to motion artifact or inadequate bolus delivery prevented analysis of
the perfusion images. This left 17 patients for analysis. Median age was 73
years (25th-75th percentile, 65-79 years). Nine patients were women (53%).
The clinical and radiological characteristics of the patients are given in Table 1. The median baseline NIHSS score
was 10 (25th-75th percentile, 8-15). Three patients died within the first
month of stroke onset. The median Barthel Index score at follow-up was 70
(25th-75th percentile, 15-95). The median time between symptom onset and MRI
examination was 5.0 hours (25th-75th percentile, 4.5-6.0 hours). Median DWI
lesion volume was 24.7 cm3 (25th-75th percentile, 6.5-35.5 cm3). Two patients did not have a baseline DWI lesion. The median PWI
lesion volume, was 93.0 cm3 (25th-75th percentile, 54.2-177.7 cm3). The mismatch volume, defined as the difference between the baseline
PWI and DWI lesion volume, was a median of 71.0 cm3 (25th-75th
percentile, 41.0-114.8 cm3). The median ADC550 was 436
x 10 -6mm2/s (25th-75th percentile, 408-505
x 10 -6mm2/s), excluding patients in whom
ADC values could not be calculated because of absence of DWI lesions (n =
2), or in whom there was a DWI lesion present but no pixels were found below
the threshold of 550 x 10 -6mm2/s (n = 1).
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Clinical and Radiological Features of Patients in Groups 1 and 2*
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The CBF measured in the region with MTT abnormalities was decreased
in all patients except 1 (median, 58% of the reference value; 25th-75th percentile,
49%-70%). In this patient, CBF was 116% of the reference value. Heterogeneity
was found within the MTT abnormality: areas with CBF decrease were found and
areas with CBF increase compared with the reference value. Cerebral blood
volume values were increased in all patients but 1 (median, 1.6; 25th-75th
percentile, 1.3-2.1).
Patients were divided into 2 groups based on CBF values. Group 1 (n
= 5) comprised patients with CBF values less than 50% of the contralateral
side (range, 27% 49%), and group 2 (n = 12) comprised patients with CBF values
greater than 50% (range, 52%-116%). Comparison of the 2 groups is detailed
in Figure 3 and Figure 4.
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Figure 3. Comparison of ADC550
between patients with cerebral blood flow values less than 50% (group 1, n
= 5) and patients with cerebral blood flow values greater than 50% (group
2, n = 12). The ADC550 is the mean apparent diffusion coefficient
of all pixels with values of less than 550 x 10 -6mm2/s.Thick horizontal rules represent the median; boxes, 25th-75th percentile;
and the whiskers of the box plot, the extremes.
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Figure 4. Comparison of National Institutes
of Health Stroke Scale (NIHSS) scores (A) and diffusion-weighted image (DWI)
(B) and perfusion-weighted image (PWI) (C) lesion volumes between patients
with cerebral blood flow values <50% (group 1, n = 5) and patients with
cerebral blood flow values >50% (group 2, n = 12). Thick horizontal rules
represent the median; boxes, 25th-75th percentile; the whiskers of the box
plot, the extremes; and the dot, an outlier.
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Patients in group 1 had lower ADC550 (median, 430 x
10 -6mm2/s; 25th-75th percentile, 349-430 x
10 -6mm2/s vs median, 506 x 10 -6mm2/s; 25th-75th percentile, 427-550 x 10 -6mm2/s; P = .04) values than patients
in group 2. Group 1 patients had larger DWI volumes (median, 41.8 cm3; 25th-75th percentile, 35.1-131.1 cm3 vs median, 14.5 cm3; 25th-75th percentile, 1.7-26.9 cm3; P = .001) and PWI volumes (median, 194.6 cm3; 25th-75th
percentile, 121.5-250.0 cm3 vs median, 69.3 cm3; 25th-75th
percentile, 41.6-118.1 cm3; P = .01) and
had more severe clinical strokes (NIHSS score: median, 15; range, 9-23 vs
median, 9; range, 4-22; P = .02). Their MTT and CBV
values were not significantly different. The functional outcome between the
2 groups was not significantly different, although there was a trend of worse
functional outcomes in group 1 (Barthel Index score: median, 20; 25th-75th
percentile, 5-80 vs median, 85; 25th-75th percentile, 45-100; P = .16).
We did not find a correlation between the total distribution of CBF
and the ADC550 (P = .24), NIHSS score
(P = .42), or Barthel Index score (P = .18). The CBF was significantly correlated only with DWI lesion
volume (Spearman  = -0.555; P = .02).
A nonsignificant correlation was found between CBF and PWI lesion volume (Spearman
= -0.446; P = .08).
COMMENT
Our findings suggest that low CBF values, measured with bolus-tracking
MRI, are associated with lower ADC values, larger DWI and PWI lesion volumes,
and more severe NIHSS scores. The association between CBF and the ADC or NIHSS
scores was not evident when comparing CBF with ADCs and NIHSS scores across
the whole range of CBF values.
We did not measure CBF directly in our study. The ROIs used to measure
CBF were derived from the areas of hyperintensity measured on the MTT maps.
Choosing the MTT as the ROI probably causes overestimation of CBF. The MTT
lesion includes areas that vasodilate in response to decreasing cerebral perfusion
pressure and, therefore, have increased MTT but have not reached the threshold
for a reduction in CBF. The finding of CBV increases, rather than decreases,
in our ROI suggests that vasodilatation often occurred within the studied
ROI. The overestimation of CBF due to our measurement method might explain
the absence of an overall relationship between CBF and the ADC. Another explanation
might be that ADC reductions are only associated with CBF reductions below
a certain threshold. This explanation is backed by experimental data demonstrating
that DWI hyperintensities, or ADC reductions, occur only at specific levels
of CBF reduction that persist over certain amounts of time. The information
gained from PWI and DWI represents an evaluation of the cerebral ischemic
process at a single time point, and this might also explain the lack of correlation
between these variables.19-20
We chose MTT maps to measure the ROI because the borders of MTT lesions
are easier to delineate on PWI than CBF or CBV maps. Differences in CBF and
CBV between gray and white matter, combined with the presence of only mild
changes in CBF and CBV, compared with MTT, make visual delineation of the
border of the lesions on CBF and CBV more difficult, especially in white matter
and at the gray/white matter junction.21
The results of our study confirm the relationship between reductions
in CBF and low ADC values found in animal models of ischemic stroke.7-9,22 Sorensen
et al23 assessed the relationship between hemodynamic
factors and the ADC in 23 patients with acute ischemic stroke studied within
12 hours of symptom onset. This study did not find a correlation between the
overall ADC and CBF. The authors did not compare the association between the
lowest CBF values and the ADC. The association of low CBF with other indicators
of stroke severity, such as a low ADC, large DWI lesion volumes, and higher
NIHSS scores, provides partial concurrent validation of the MRI method for
measuring relative CBF. Our findings suggest that in future studies, low ADC
values could be used as surrogates for low CBF values. Other studies have
compared this NP-SVD MRI method of measuring hemodynamics with noninvasive
CBF measurements in humans. Lie et al24 compared
the NP-SVD MRI method with a spin-labeling MRI technique in healthy volunteers
and found good agreement between both techniques. Liu et al25
found a curvilinear relationship between relative CBF values obtained using
single-photon emission computed tomography and the NP-SVD MRI method in 11
patients with acute ischemic stroke. The same group26
also reported a high correlation between hypoperfusion volumes obtained using
single-photon emission computed tomography and the NP-SVD MRI method in 23
patients. A nonsignificant trend of worse functional outcome in patients with
low CBF values was found. The absence of a significant association is probably
related to the small sample size, although this hypothesis should be confirmed
in further studies. Van Everdingen et al27
reported significant correlations between ADC values and indicators of functional
outcome in 38 patients with acute ischemic stroke.
The limitations of our study are related to the small sample size and
the performance of multiple-hypothesis testing. We arbitrarily chose a reduction
in CBF of greater than 50% to distinguish between severe CBF reduction and
less severe CBF reduction. We were not able to analyze the spatial correspondence
between a low ADC and reduced CBF values in individual voxels because the
baseline DWIs and PWIs were not coregistered. The bolus-tracking MRI technique
has some inherent limitations. Absence of contrast delivery in nonperfused
regions makes accurate measurement of CBF within these areas impossible. Delays
in contrast arrival through collateral vessels or dispersion of contrast through
a stenosis may mimic decreases in CBF, although beneficial perfusion is present.
Accurate determination of the arterial input function required to perform
deconvolution with the tissue concentration time curve is subject to errors
caused by partial volume artifacts.2, 23, 28-30
In conclusion, we found an association between reduced CBF measured
using MRI and clinical and radiological markers of stroke severity. This association
was present only with severe reductions in CBF.
AUTHOR INFORMATION
Accepted for publication September 19, 2001.
Author contributions: Study concept and design (Drs Thijs, Moseley, and Albers); acquisition of data (Drs Thijs and Adami); analysis and interpretation of data (Drs Thijs, Neumann-Haefelin, and Moseley); drafting of
the manuscript (Dr Thijs); critical revision of the
manuscript for important intellectual content (Drs Adami,
Neumann-Haefelin, Moseley, and Albers); statistical expertise (Dr Thijs); obtained funding (Dr Moseley); administrative, technical, and material support (Drs Adami and Moseley); study supervision (Drs Neumann-Haefelin,
Moseley, and Albers).
This study was supported in part by grants NS-34088-03 and 1R01NS35959
from the National Institutes of Health, Bethesda, Md (Dr Moseley).
Corresponding author and reprints: Vincent N. Thijs, MD, Department
of Neurology, UZ Gasthuisberg, Katholieke Universiteit Leuven, Herestraat
49, 3000 Leuven, Belgium (e-mail: vincent.thijs{at}uz.kuleuven.ac.be).
From the Department of Neurology and Neurological Sciences, Stanford
Stroke Center (Drs Thijs, Adami, and Albers), and the Section of Neuroradiology,
Department of Radiology (Dr Moseley), Stanford University Medical Center,
Palo Alto, Calif; the Department of Neurology, UZ Gasthuisberg, Katholieke
Universiteit Leuven, Leuven, Belgium (Dr Thijs); Clinica Neurologica, Universitá
di Verona, Verona, Italy (Dr Adami); and the Department of Neurology, Johann
Wolfgang-Goethe Universität, Frankfurt, Germany (Dr Neumann-Haefelin).
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