CT-NIHSS Mismatch Does Not Correlate With MRI
Diffusion-Perfusion Mismatch
Steven R. Messé, MD; Scott E. Kasner, MD; Julio A. Chalela, MD;
Brett Cucchiara, MD; Andrew M. Demchuk, MD; Michael D. Hill, MD; Steven Warach, MD
Downloaded from http://stroke.ahajournals.org/ by guest on June 18, 2017
Background and Purpose—MRI diffusion-perfusion mismatch may identify patients for thrombolysis beyond 3 hours.
However, MRI has limited availability in many hospitals. We investigated whether mismatch between the Alberta
Stroke Program Early CT Score (ASPECTS) and the NIH Stroke Scale (NIHSS) correlates with MRI diffusionperfusion mismatch.
Methods—We retrospectively analyzed a cohort of consecutive acute ischemic stroke patients who underwent MRI and CT
at admission. NIHSS was performed by the admitting physician. MRI and CT were reviewed by 2 blinded expert raters.
Degree of MRI mismatch was defined as present (⬎ 25%) or absent (⬍25%). Univariate and multivariate analyses were
performed to determine characteristics associated with MRI mismatch. Probability of MRI mismatch was calculated for
all combinations of ASPECTS and NIHSS cutoff scores.
Results—Included in the analysis were 143 patients. Median NIHSS on admission was 4 (IQR, 2 to 10); median ASPECTS
was 10 (IQR, 9 to 10). Median time to completion of MRI and CT was 4.5 (2.5 to 13.9) hours after onset. CT and MRI
were separated by a median of 35 (IQR, 29 to 44) minutes. MRI mismatch was present in 41% of patients. In
multivariate analysis, only shorter time-to-scan (OR, 0.96 per hour; 95% CI, 0.92 to 1.0; P⫽0.043) was associated with
MRI mismatch. There was no combination of NIHSS and ASPECTS thresholds that was significantly associated with
MRI mismatch.
Conclusions—ASPECTS-NIHSS mismatch did not correlate with MRI diffusion-perfusion mismatch in this clinical
cohort. MRI mismatch was associated with decreasing time from stroke onset to scan. (Stroke. 2007;38:2079-2084.)
Key Words: cerebral infarct 䡲 computed tomography 䡲 ischemic penumbra 䡲 magnetic resonance imaging
䡲 mismatch 䡲 neuroradiology 䡲 thrombolysis
A
central premise of acute stroke treatment is the rapid
restoration of blood flow to hypoperfused brain tissue
that has not yet been irreversibly damaged. The only FDAapproved medical treatment at this time is tissue plasminogen
activator (tPA), which is limited to a 3-hour time window.
Unfortunately, the majority of stroke patients are not eligible
for treatment because they present at the hospital too late.1
MRI diffusion-perfusion mismatch may be able to define a
subset of patients with clinically meaningful ischemic penumbra beyond 3 hours, thereby extending the time window
for safe and effective thrombolytic treatment.2–7 However,
MRI has limited availability at many institutions, and there
are inherent difficulties in acquiring rapid MRI scans in acute
stroke patients.8,9 Thus, alternative strategies for identifying
potentially salvageable brain tissue are desirable.
A mismatch between clinical deficit and CT findings has
been suggested as a possible alternative approach.10,11 Specifically, a severe deficit in a patient with a normal or
near-normal CT might be indicative of viable tissue. In this
study we sought to determine whether a mismatch between
the Alberta Stroke Program Early CT Score (ASPECTS) and
the National Institutes of Health Stroke Scale (NIHSS)
correlates with concurrent MRI diffusion-perfusion
mismatch.
Materials and Methods
We retrospectively analyzed a cohort of consecutive ischemic stroke
patients who presented to the National Institutes of Health stroke
program at Suburban Hospital in Bethesda, Maryland. All patients in
the acute stroke clinical database, which included all patients who
were admitted to the hospital with the diagnosis of an acute ischemic
stroke, were eligible for this analysis. Multimodal MRI and noncontrast CT were attempted in all patients at admission as part of the
routine imaging protocol. Patients were examined by the admitting
stroke neurologist and the NIHSS was recorded. Stroke severity was
determined using the NIHSS and categorized by approximate tertiles
as 0 to 3, 4 to 9, or ⱖ10.
Received December 19, 2006; final revision received February 16, 2007; accepted March 8, 2007.
From Department of Neurology (S.R.M., S.E.K., B.C.), University of Pennsylvania Medical Center, Philadelphia; Departments of Neurology and
Neurosurgery (J.A.C.), Medical University of South Carolina, Charleston; Department of Clinical Neurosciences (A.M.D., M.D.H.), University of
Calgary, Alberta, Canada; National Institutes of Health (S.W.), Bethesda, MD.
Correspondence to Steven R. Messé, MD, Department of Neurology, Comprehensive Stroke Center, University of Pennsylvania Medical Center, 3W
Gates Building, 3400 Spruce Street, Philadelphia, PA 19104. E-mail [email protected]
© 2007 American Heart Association, Inc.
Stroke is available at http://www.strokeaha.org
DOI: 10.1161/STROKEAHA.106.480731
2079
2080
Stroke
July 2007
TABLE 1.
Patient Characteristics
Complete Data
n⫽143
Incomplete Data*
n⫽135
P
71⫾17
73⫾17
0.22
Hypertension
68%
59%
0.14
Diabetes
26%
19%
0.19
Mean age (⫾SD), yr
History of
Coronary artery disease
22%
15%
0.11
Atrial fibrillation
20%
19%
0.71
Smoking
16%
19%
0.60
Hypercholesterolemia
27%
28%
0.77
4.5 (2.5–13.9)
4.3 (2.6–14.3)
0.99
18%
15%
0.33
4%
0.42
Median time to complete scanning in hours (IQR)
Received IV tPA
Received IA tPA
Median NIHSS (IQR) on admission
Mean NIHSS (⫾SD) on admission
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Median ASPECTS (IQR)
2%
4 (2–10)
7.5⫾8.5
10 (9–10)
5 (2–12)
8.2⫾8.8
10 (9–10)
0.34
0.48
0.57
*Subjects with incomplete data were missing CT, MRI, time of onset, or admission NIHSS.
CT Data
CT scans were performed on a fourth-generation Somatom Plus
(Siemens) or Lightspeed (General Electric) scanner. Images were
acquired after the orbito-meatal plane with 5-mm thickness for the
entire examination. Conventional brain window images were used.
Each head CT was evaluated independently by 2 expert raters
blinded to clinical information using the ASPECTS system.12 The
ASPECTS scale divides the middle cerebral artery (MCA) territory
into 10 divisions; 1 point is subtracted for each division that
demonstrates ischemic changes. Vascular territories other than the
MCA are not scored. A score of 10 indicates no early ischemic
change and a lower score indicates greater changes. To increase the
sensitivity of ASPECTS for identifying early ischemic change on
head CT, disagreements in ASPECTS rating were resolved by
averaging the 2 scores and rounding down. For the primary analysis,
ASPECTS of 10 (ie, a completely normal MCA territory on CT scan)
was compared with all other scores. Subsequent analyses assessed all
other ASPECTS thresholds (9 and 10 versus lower scores, etc).
MRI Data
MRI was performed using a 1.5-T (Twinspeed XL; General Electric)
system. The protocol consisted of diffusion-weighted imaging,
fluid-attenuated inversion recovery, gradient recall echo, and
perfusion-weighted imaging series, with a 24-cm field of view,
7-mm-thick axial-oblique slices aligned with the anterior–posterior
commissure, and 20 contiguous slices interleaved, and colocalized.
Diffusion-weighted images were acquired with repetition time/echo
time⫽6,00/72 msec, an acquisition matrix of 128⫻128, and with
both b⫽0 and b⫽1000 isotropically weighted, using fluid-attenuated
inversion recovery T2-weighted imaging with a fast-spin echo
sequence having TR/TE⫽9000/85msec, TI⫽1750 msec and a
256⫻128 matrix, and using gradient recall echo T2* imaging with
TR/TE⫽800/20 msec and a 256⫻192 matrix. Perfusion-weighted
images were obtained by injecting gadolinium (0.1 mmol/kg dose via
power injector) with gradient-echo echo planar imaging, a TE of 45
msec; 25 phases with 2 seconds per phase, and a matrix of 64⫻64.
Maps of normalized mean transit time (MTT) were calculated using
concentration–time curves obtained from the perfusion-weighted
imaging time series. The first moment of the concentration–time
curve divided by the zero moment was directly normalized by a
similarly calculated reference, providing an estimate of a relative
fractional change in MTT that does not depend on cerebral blood
flow or volume. The reference was obtained by averaging the
concentration–time data for all voxels in the brain. The resulting
MTT images had nominal values of 1 for normal tissue, and ⬎1 for
ischemic tissue (where 1.5 corresponds to a 50% increase in MTT).
Each MRI was evaluated by 2 expert raters blinded to clinical
information for diffusion and perfusion defects, the latter defined by
MTT. The vascular territory for each stroke was determined by each
reviewer based on diffusion imaging analysis. Degree of mismatch
was qualitatively determined based on simultaneous visual inspection of the 2 scans, a method that has been previously described and
validated.13 Mismatch was defined as absent if the perfusion defect
was ⬍25% larger than diffusion abnormality. If MRI mismatch was
present, the degree was noted as ⬎25%, ⬎50%, ⬎75%, or 100%.
Disagreement between the 2 MRI raters was resolved by consensus
determination.
Statistical Analysis
Logistic regression was performed to determine which clinical
characteristics were associated with MRI mismatch. Univariate
analysis was performed to identify the relationships between MRI
mismatch and the following variables: NIHSS, ASPECTS, and time
to scan. Multivariate analysis was performed to determine the
independent effect of each of these parameters on the likelihood of
identifying MRI mismatch. From the multivariable models, the
probability of mismatch could be estimated for each NIHSS and
ASPECTS category with adjustment for time to scan. A Wald test
was used to determine if each set of NIHSS and ASPECTS
categories were associated with MRI mismatch after adjustment for
time to scan. To confirm the findings of the Wald test, a likelihood
ratio test was performed by comparing full models including NIHSS,
ASPECTS, and time to scan with simpler models including only
NIHSS and time to scan. All statistical analyses were performed
using Stata statistical software, version 8.0 (Stata Corp). Results
were considered statistically significant if P⬍0.05.
Results
Two-hundred seventy-eight consecutive stroke patients from
a 15-month period ending in 2002 were evaluated for inclusion in this study. Complete data were available for 143
patients (51%). Sixty-five patients were missing adequate
MRI data, 79 were missing CT data, 29 were missing the time
they were last known normal, and 13 were missing NIHSS
information. Clinical characteristics of patients included in
the analysis compared with those without complete data were
not significantly different and are displayed in Table 1. The
distribution of ASPECTS and NIHSS scores at baseline are
Messé et al
CT-NIHSS Mismatch Does Not Identify MRI Mismatch
2081
Figure 1. Distribution of ASPECTS and
NIHSS scores at baseline.
Downloaded from http://stroke.ahajournals.org/ by guest on June 18, 2017
depicted graphically in Figure 1. Among patients included in
the analysis, the median NIHSS on admission was 4, IQR, 2
to 10). The median ASPECTS was 10 (IQR 9 to 10). The
median time to completion of scanning was 4.5 (IQR 2.5 to
13.9) hours after onset. CT and MRI were separated by a
median of 35 (IQR 29 to 44) minutes. The inter-rater
reliability was good for ASPECTS score, with a quadraticweighted kappa of 0.75 (95% CI, 0.59 to 0.90). Inter-rater
reliability was excellent for determination of MRI mismatch,
with a quadratic-weighted kappa of 0.95 (95% CI, 0.82 to
1.0). Overall, MRI mismatch was present in 58 of 143 (41%)
of patients. Based on diffusion MRI review, 104 of 143
(73%) of strokes in this cohort occurred within the MCA
territory.
In univariate analysis, MRI mismatch was associated with
higher NIHSS scores (referent group NIHSS 0 to 3: OR, 1.0
[referent]; NIHSS 4 to 10: OR, 2.2 [95% CI, 1.1 to 4.3;
P⫽0.03]; NIHSS ⱖ10: OR, 2.2 [95% CI, 1.1 to 4.4; P⫽0.03)
and shorter time to scan (OR, 0.97 per hour [95% CI, 0.94 to
1.0; P⫽0.03]), but there was no association with ASPECTS
10 versus ⬍10 (OR, 0.80 [95% CI, 0.42 to 1.53; P⫽0.51]) or
with any other ASPECTS threshold. Figure 2 displays the
decreasing predicted probability of MRI mismatch with
longer time to scan.
In multivariate analysis, only shorter time to scan (OR,
0.96 per hour; 95% CI, 0.92 to 1.0; P⫽0.043) was associated
with MRI mismatch. Neither NIHSS nor ASPECTS was
associated with MRI mismatch after adjustment for time to
scan. Consequently, there was no combination of NIHSS and
ASPECTS thresholds that was significantly associated with
MRI mismatch. Table 2 displays the time-adjusted predicted
probabilities of MRI mismatch using NIHSS cutoffs for mild,
Figure 2. Predicted probability of MRI mismatch over time. Univariate logistic regression demonstrated that MRI mismatch was
significantly less likely with later time to
scan (OR, 0.96 per hour; 95% CI, 0.92 to
1.0). Probabilities and 95% CIs were determined from this univariate model to generate this figure.
2082
Stroke
July 2007
TABLE 2A. Predicted Probability of MRI Mismatch by NIHSS
and ASPECTS Cutoffs, Adjusted for Time to Scan
ASPECTS 10
(n⫽86)
ASPECTS 0 –9
(n⫽57)
NIHSS 0 –3 (n⫽68)
0.31 (0.20–0.44)
0.31 (0.17–0.50)
NIHSS 4–9 (n⫽36)
0.49 (0.30–0.67)
0.49 (0.31–0.68)
NIHSS ⱖ10 (n⫽39)
0.38 (0.22–0.58)
0.39 (0.23–0.58)
Wald test P⫽0.38 for entire sample, P⫽0.23 for those scanned within 6
hours. Likelihood ratio test P⫽0.95.
B. Predicted Probability of MRI Mismatch by NIHSS and
ASPECTS Cutoffs, Adjusted for Time to Scan
ASPECTS 9 or 10
(n⫽111)
ASPECTS 0 – 8
(n⫽32)
NIHSS 0 –3 (n⫽68)
0.31 (0.21–0.44)
0.29 (0.14–0.51)
NIHSS 4–9 (n⫽36)
0.50 (0.33–0.67)
0.47 (0.25–0.70)
NIHSS ⱖ10 (n⫽39)
0.40 (0.23–0.59)
0.37 (0.20–0.58)
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Wald test P⫽0.37 for entire sample, P⫽0.19 for those scanned within 6
hours. Likelihood ratio test P⫽0.79.
C. Predicted Probability of MRI Mismatch by NIHSS and
ASPECTS Cutoffs, Adjusted for Time to Scan
ASPECTS 8 –10
(n⫽124)
ASPECTS 0 –7
(n⫽19)
NIHSS 0 –3 (n⫽68)
0.31 (0.21–0.44)
0.22 (0.08–0.49)
NIHSS 4–9 (n⫽36)
0.50 (0.34–0.67)
0.39 (0.16–0.68)
NIHSS ⱖ10 (n⫽39)
0.43 (0.25–0.62)
0.32 (0.14–0.56)
Wald test P⫽0.29 for entire sample, P⫽0.11 for those scanned within 6
hours. Likelihood ratio test P⫽0.41.
moderate, and severe strokes, dichotomizing ASPECTS
scores into normal or abnormal based on a score of 10 versus
0 to 9; 9 or 10 versus 0 to 8; and 8 to 10 versus 0 to 7.
Restricting the sample to only those patients scanned within
6 hours yielded similar results without significant improvement in the identification of MRI mismatch. All other
ASPECTS cutoffs were evaluated and similarly did not
demonstrate any ability to further discriminate patients with
MRI mismatch. Further analyses were performed, including
redefining MRI mismatch as ⬎50% difference between
perfusion and diffusion volume, and limiting the analysis to
include only those patients with MCA territory infarcts on
MRI diffusion imaging. Neither of these analyses found any
significant associations (data not shown).
Discussion
Within this cohort of acute stroke patients seen in clinical
practice, systematically interpreted head CT and clinical
examination findings could not be validated as a means to
identify ischemic penumbra as defined by MRI diffusionperfusion mismatch. There have been a number of efforts to
determine which patients may benefit from late thrombolysis.
MRI has been used extensively to characterize the ischemic
penumbra by identifying regions of brain with reduced blood
flow, defined by perfusion-weighted imaging, and regions
with irreversible neuronal injury, approximated by diffusionweighted imaging. A mismatch between the volume of
abnormality on diffusion and perfusion imaging appears to
indicate viable penumbral tissue. MRI mismatch has been
shown to correlate with favorable outcomes following late
treatment with intravenous tPA up to 6 hours from symptom
onset.2,3,6,7 The Desmoteplase in Acute Ischemic Stroke
(DIAS) and Dose Escalation of Desmoteplase for Acute
Ischemic Stroke (DEDAS) trials demonstrated that
thrombolysis may be effective up to 9 hours from the onset of
symptoms in patients selected using MRI mismatch.4,5
Following-up on these promising preliminary data, there are
currently at least 4 ongoing trials using MRI to select patients
for thrombolysis beyond the 3-hour window, including Desmoteplase in Acute Ischemic Stroke-2 (DIAS-2), Echoplanar
Imaging Thrombolysis Evaluation Trial (EPITHET), ReoPro
Retavase Reperfusion of Stroke Safety Study—Imaging
Evaluation (ROSIE), and MR and Recanalization of Stroke
Clots Using Embolectomy (MR RESCUE).
Unfortunately, while hyperacute MRI is a powerful tool, a
large number of hospitals do not have the resources to obtain
emergent MRI. A comprehensive survey of 180 hospitals in
Illinois in 2002 found that only 73.9% had MRI availability,
whereas only 25% and 17.2% were performing diffusionweighted and perfusion-weighted imaging, respectively.8
Further, there are inherent difficulties in obtaining MRI from
the emergency department in acute stroke patients. In 141
consecutive acute stroke patients, 19.9% were not able to
undergo MRI.9 Half of these patients had MRI contraindications such as cardiac pacemakers, while the other half of
patients were excluded from MRI because of decreased
level of consciousness, vomiting, agitation, or hemodynamic compromise. A more practical alternative to determining the volume of ischemic penumbra would be tremendously valuable.
This study reports one of the largest series of acute stroke
patients to undergo diffusion and perfusion MRI as part of a
routine clinical practice. In multivariable analysis, we found
that MRI mismatch correlated with time from symptom onset
to scanning. Other studies of MRI mismatch have also found
that time to scanning significantly impacts the presence of
mismatch. A neuroprotectant study of 81 acute stroke patients
reported that 83% had MRI mismatch if scanned within 3
hours of symptom onset, whereas only 43% had mismatch at
24 hours.14 Overall, we found a relatively lower prevalence of
MRI mismatch than has been reported in other series. This
was most likely to be caused by the fact that we did not
exclude patients based on stroke severity (milder strokes are
presumably less likely to have a mismatch) or time to
scanning (those who presented to the emergency room later,
were less likely to have a mismatch). This relatively lower
prevalence of MRI mismatch in our consecutive series of
stroke patients is an important finding because it provides a
more realistic assessment of how many patients may eventually be eligible for consideration of late thrombolysis if
patient selection by MRI is determined to be beneficial.
We did not find any correlation between CT and NIHSS
mismatch and MRI diffusion-perfusion mismatch. These
results are generally consistent with other recent reports. In
the NINDS rt-PA Stroke Study, baseline ASPECTS score had
no effect on response to treatment with tPA given within 3
Messé et al
CT-NIHSS Mismatch Does Not Identify MRI Mismatch
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hours.15 A post-hoc analysis from the European-Australian
Acute Stroke Study II (ECASS II) found that the benefit from
tPA was not influenced by baseline ASPECTS.16 Similarly, a
pooled analysis of patients enrolled in tPA clinical trials
within 6 hours of symptom onset found that mismatch
between ASPECTS and NIHSS did not reliably identify
patients who were more or less likely to benefit from
thrombolysis.17 A recent study of 825 patients with anterior
circulation stroke treated with tPA did find a weak association with outcome.18 Our study is an important addition to the
literature because we included patients who presented well
beyond the 6-hour time window. Increased time from symptom onset is correlated with an increased likelihood of finding
ischemic change on head CT.19 Thus, as time from symptom
onset increases head CT becomes a more sensitive measure of
irreversible ischemic injury, and thus is more analogous to
diffusion MRI. The median time to presentation was 4.5
hours and 25% of patients presented after 14 hours, which
should have improved the likelihood that CT findings would
help to discriminate those patients with mismatch. Nevertheless, we did not find any utility of ASPECTS to determine
MRI mismatch. The ECASS II data suggested that a lower
ASPECTS was associated with a higher risk of
thrombolysis-related hemorrhagic conversion.16 However, we
did not study hemorrhage rates in our cohort as there were
very few.
There are a number of limitations to this study that deserve
mention. First, the median NIHSS was 4, and thus the
majority of strokes in this series would be considered mild.
As noted, milder strokes are probably less likely to have a
large ischemic penumbra, and this is reflected in our relatively low rate of MRI mismatch. While the distribution of
stroke severity in this cohort is consistent with what has been
reported in other series of patients seen in clinical practice,20
a large cohort of exclusively severe strokes may be more
likely to define an association. Second, the number of patients
with incomplete data may have led to a biased result,
although patient characteristics were similar whether the data
were complete. Another important limitation is the fact that
perfusion MRI remains an evolving and nonstandardized tool.
The method we used to calculate MTT has been demonstrated
to have the strongest association with clinical deficit in a
cohort of patients imaged within 24 hours of stroke onset.21
Nevertheless, it is not clear whether MTT is the optimal
measure of brain perfusion, particularly given the wide time
window in our study. Finally, ASPECTS was originally
designed to quantify ischemic change in MCA infarcts,
whereas we included all stroke types in our analysis. In a
retrospective analysis of the PROACT-2 study, which limited
inclusion to patients with MCA occlusions, ASPECTS score
was significantly associated with response to thrombolytic
therapy.22 Based on diffusion MRI review, the majority of
strokes occurred within the MCA territory in this cohort. This
agrees with larger series of stroke patients seen in clinical
practice.23 Limiting the analysis to those patients with stroke
in the MCA territory did not reveal any significant associations. Further, it can be challenging to clinically distinguish
between anterior and posterior circulation infarcts as well as
between large-vessel and lacunar infarcts.24,25 Thus, we felt it
2083
was appropriate to include all stroke patients in our primary
analysis.
In summary, mismatch between ischemic changes on head
CT and clinical examination findings did not correlate with
MRI diffusion-perfusion mismatch in this clinical cohort.
MRI mismatch was associated with earlier time to scan.
There are promising early data to suggest that MRI diffusionperfusion mismatch will effectively extend the time window
for thrombolysis in select patients and multiple ongoing
studies are attempting to confirm this approach. Alternative
methods to define the subset of acute stroke patients with
clinically meaningful ischemic penumbra may also be demonstrated to be effective. A mismatch between clinical
findings and diffusion MRI has been suggested as a means of
avoiding the nonstandardized and not widely available perfusion MRI.26 Imaging protocols that provide information
about the status of both the brain and the blood vessels such
as multimodal CT, incorporating CT angiogram and CT
perfusion, may also be demonstrated to be a practical
approach.
Acknowledgments
The authors acknowledge Patricia Lyall, Vickie Hynemann, and all
the members of the NIH Stroke Team for their invaluable assistance.
Sources of Funding
S.R.M. and this study were supported by an American Heart
Association Physician-Scientist Fellowship grant. S.E.K. was supported by NIH NS02147. This research was supported by the
Intramural Research Program of the National Institutes of Health,
National Institute of Neurological Disorders and Stroke.
Disclosures
None.
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Stroke. 2007;38:2079-2084; originally published online May 31, 2007;
doi: 10.1161/STROKEAHA.106.480731
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