(Stroke. 2001;32:1140.)
© 2001 American Heart Association, Inc.
Original Contributions |
From the Department of Neuroradiology (L.R., L.Ø., C.Z.S., P.V.-P., C.G.) and the Department of Neurology (G.A.), Aarhus University Hospital, Aarhus, Denmark; the Department of Neurosurgery (M.S.), University of Ehime, Ehime, Japan; and SHFJ (D.L.B.), CEA, Orsay, France.
Correspondence to Lisbeth Røhl, MD, Department of Neuroradiology, Aarhus University Hospital, Nørrebrogade 44, DK-8000 Aarhus C, Denmark. E-mail Lisbeth{at}pet.auh.dk
| Abstract |
|---|
|
|
|---|
MethodsDWI and PWI
were performed in 11 patients
6 hours after the onset of symptoms of
acute ischemic stroke. Regions of interest (ROIs) were placed
covering the ischemic core (ROI 1), the penumbra that
progressed to infarction on the basis of follow-up scans (ROI 2), and
the penumbra that recovered (ROI 3). The ratios of relative cerebral
blood flow (rCBF), relative cerebral blood volume (rCBV), mean transit
time (MTT), and apparent diffusion coefficient were calculated as
lesion ROIs relative to the contralateral mirror
ROIs.
ResultsThe post hoc analysis showed that the penumbra progressed to infarction at the following cutoff values: rCBF <0.59 and MTT >1.63. Higher sensitivity and accuracy in predicting outcome of the penumbra were obtained from the rCBF maps compared with the rCBV and MTT maps. The initial rCBV and apparent diffusion coefficient ratios did not differentiate between the part of the penumbra that recovered and the part that progressed to infarction. The mean rCBF ratio was optimal in distinguishing the parts of the penumbra recovering or progressing to infarction.
ConclusionsThe thresholds found in this study by combined DWI/PWI might aid in the selection of patients suitable for therapeutic intervention within 6 hours. However, these hypothesized thresholds need to be prospectively tested at the voxel level on a larger patient sample before they can be applied clinically.
Key Words: MRI, diffusion-weighted MRI, perfusion-weighted penumbra stroke, acute
| Introduction |
|---|
|
|
|---|
The definition of the penumbra is important in selecting patients suitable for therapeutic intervention.10 Several studies have indicated that for the purpose of defining the tissue at risk of infarction, the penumbra can be operationally defined as the mismatch between the lesion volume detected by PWI and DWI.11 12 Preliminary studies have already used this mismatch as a guideline for therapeutic intervention in ischemic stroke within 6 hours, with promising results.11 13 However, studies investigating the discrimination between potentially salvageable tissue from tissue that would recover spontaneously within the perfusion/diffusion mismatch are scarce.14 Most studies have determined thresholds between all ischemic tissue progressing to infarct (including the ischemic core) from tissue recovering spontaneously on the basis of cerebral blood flow (CBF) and cerebral blood volume (CBV)12 15 16 17 or the decrease in apparent diffusion coefficient (ADC), which reflects early cytotoxic edema.12 18 19
The purpose of the present study was to define
viability thresholds in the ischemic penumbra, operationally
defined as the perfusion/diffusion mismatch, in hyperacute stroke
patients (
6 hours of symptom onset) by the use of combined DWI and
PWI.
| Subjects and Methods |
|---|
|
|
|---|
MRI Protocol
MRI was performed by use of a GE Signa 1.0-T Imager
(GE Medical Systems) retrofitted with a 1-MHz receiver. The entire
protocol consisted of a sagittal scout, an axial DWI, an axial
T1-weighted 3D scan, an axial T2-weighted scan, and an axial PWI. Total
examination time was 30 minutes, which included preparation of the
patient with the insertion of a venous catheter in a cubital
vein.
Diffusion-Weighted MRI
Multislice DWI using spin-echo, single-shot,
echo-planar imaging was performed by acquiring an unweighted image
(S0, b
factor 0 s/mm2, neglecting the contribution
of the imaging gradients to the diffusion weighting), as well as 3
diffusion-weighted images with diffusion gradients in orthogonal
directions: Sx, Sy, and
Sz (b
factor 1000 s/mm2). Fourteen to 16 axial
slices were acquired, covering the entire brain. The acquisition
parameters used for DWI were as follows: repetition
time/echo time (TR/TE) 5000/109 ms, 96x96 matrix, 22x16.5-cm field of
view (FOV), 5-mm slice thickness, and 2-mm slice gap. The
acquisition time was 20 seconds. An average diffusion-weighted image
was calculated from the diffusion-weighted images as the mean intensity
of the 3 images. ADC was estimated as the mean diffusivity in the
3 orthogonal directions (derived from Le Bihan et
al20 ):
ADC=-[ln(Sx/S0)+ln(Sy/S0)+ln(Sz/S0)]/3b,
where Si (i=x, y, z, 0) denotes DWI signal
intensities for the 3 orthogonal directions and the unweighted image,
respectively.
Perfusion-Weighted MRI
PWI was performed by dynamic gradient-echo
echo-planar imaging, tracking a bolus of 0.1 mmol/kg gadodiamide
(Omniscan, Nycomed Imaging), injected at a rate of 5 mL/s, by use of a
magnetic resonancecompatible power injector (Medrad). This bolus was
immediately followed by injection of an equal volume of
physiological saline, also at a rate of 5 mL/s.
Five slices (5 patients) or 10 slices (6 patients) covering the lesion
on the diffusion-weighted images (pulse sequences were optimized after
the first 5 patients, allowing acquisition of 10 slices) were obtained.
Fifty single-shot, gradient-echo, echo-planar images were obtained in
each of the slices during the bolus passage, and accordingly, 250 or
500 images were obtained during the 1.16-minute acquisition time. The
acquisition parameters were as follows: TR/TE 1500/45 ms,
flip angle 60°, 96x96 matrix, 22x16.5-cm FOV, 5-mm slice thickness,
and 2-mm slice gap. Maps of rCBV were calculated by integrating the
first-pass concentration time
curve.21 22 The
rCBF and MTT maps were calculated by using a noninvasively determined
arterial input function and singular value decomposition
deconvolution, as described
previously.23 24
Postprocessing was performed on a SUN SPARC 60
workstation.
T2-Weighted MRI
Approximately 30 days after acute stroke, a
T2-weighted MRI scan was performed with the following acquisition
parameters: TR/TE 4000/102 ms, 256x256 matrix, 22x22-cm
FOV, 5-mm slice thickness, 2-mm slice gap, and 2.08-minute acquisition
time.
Data Analysis
The DWI and ADC images, the maps of rCBF, rCBV, and
MTT, and the final T2-weighted images were all transferred to a
personal computer. Measurements of all the lesion volumes were
performed by a planimetric technique using a commercially available
software package (ALICE, Hayden Image Processing Solutions). This
program has an autothreshold function, which we used to determine the
borders of the ischemic core (on DWI) and final infarction (on
chronic T2-weighted imaging), as described previously by Sorensen et
al.3 We defined the penumbra
as the difference between the volume with reduced blood flow, as shown
at the maps of rCBF, and the ischemic lesion volume at the
initial DWI image (ie, the perfusion/diffusion mismatch). Then, 3
regions of interest (ROIs) were placed manually on the rCBF maps as
shown in
Figure 1
. ROI 1 covered the ischemic core, as
detected from the diffusion-weighted images. ROI 2 covered the
diffusion/perfusion mismatch volume that (by visual inspection)
progressed to infarction, as defined by the final unaligned T2-weighted
image. ROI 3 covered the mismatch volume that appeared normal on
follow-up images. The ROIs were applied at all the affected rCBF
slices, with a maximum number of 5 slices (5 patients) or 10 slices (6
patients). All 3 ROIs were mirrored to the contralateral unaffected
hemisphere. Finally, all ROIs were copied to rCBV, MTT, and ADC maps.
The ratios between physiological estimates (rCBF,
rCBV, MTT, and ADC) of the lesion and of the contralateral mirror ROI
were then determined. In 1 patient, the calculation of an ADC image
failed, because DWI in only 1 direction was obtained, and accordingly,
there were only 10 patients in the analysis of ADC.
|
Statistical Analysis
Two-way ANOVA was used to compare mean ratios within
the ROIs of the 11 patients. Comparisons between the ROIs were
performed by paired t test,
with the Bonferroni correction for multiple tests on the same sample.
Receiver operating characteristic (ROC) curves were used to define the
optimal cutoff ratio, which was chosen as the ratio that resulted in
the highest possible sensitivity and specificity. ROC curves were also
used to compare the performance of rCBF, rCBV, and MTT ratios
in terms of predicting viable and nonviable tissue by comparison of the
areas with Wilcoxon
statistics.25 A
multivariate (rCBF ratio, rCBV ratio, and MTT ratio)
discriminant analysis was performed to obtain a cutoff
function.
| Results |
|---|
|
|
|---|
|
Mean ratios for the 3 ROIs determined from the different
perfusion and ADC maps are shown in
Table 2
. All lesion/contralateral ratios of the ROIs
for the rCBF, rCBV, MTT, and ADC maps are shown in
Figure 2
. A low mean rCBF ratio of 0.26 was found in
the ischemic core; a ratio of 0.42, in the penumbra progressing
to infarction; and a ratio of 0.62, in the penumbra that recovered
(Figure 2A
). The 2-way ANOVA showed a highly significant
difference between these 3 ratios (F=60.83,
P<0.001), and the following
t test also demonstrated a
significant difference between all 3 ROIs (ie, the core, the penumbra
that recovered, and the penumbra that progressed to infarction).
From the ROC curve, we found the optimal cutoff value between the 2
parts of the penumbra to an rCBF ratio of 0.59
(Table 3
), and with this ratio, the sensitivity was
0.91, the specificity was 0.73, and the accuracy was 0.82 (calculated
as
0.5 · sensitivity+0.5 · specificity).26
|
|
|
The mean ratio of rCBV in the 3 ROIs showed markedly less
reduction but followed the same pattern as rCBF
(Figure 2B
), and the difference was also highly significant
(2-way ANOVA: F=20.77,
P<0.001). The mean rCBV ratio
was 0.55 in the core, 0.84 in the penumbra progressing to infarction,
and 0.94 in the penumbra that recovered. However, there was no
statistical difference between the part of the penumbra that recovered
and the part that went on to infarction, by the use of the paired
t test
(P=0.023; the level of
significance with Bonferroni correction is
P=0.05/12=0.004). From the ROC
curves, the optimal cutoff value between the 2 parts of the penumbra
was found to be an rCBV ratio of 0.85
(Table 3
), with an accuracy of 0.68. Finally, there was a
longer MTT ratio for the more severe ischemia
(Figure 2C
). The mean ratios of the 3 ROIs on the maps of MTT
differed significantly (2-way ANOVA: F=14.67,
P<0.001); however, there was
no statistical difference between the core and the penumbra that
progressed to infarction
(P=0.054). The cutoff value
between the 2 parts of the penumbra was an MTT ratio of 1.63
(Table 3
), with an accuracy of 0.68.
The comparison of the areas of the ROC curves of each
of the 3
parameters25
showed that only the difference between the rCBF area (mean±SE
0.85±0.08) and the rCBV area (mean±SE 0.67±0.12) reached a
statistically significant level
(z=2.19,
P=0.028). This suggests that
rCBF is a better separator of viable and nonviable tissue than is rCBV.
Furthermore, higher sensitivity and accuracy were obtained from the
rCBF maps than from the rCBV and MTT maps
(Table 3
).
Including all hemodynamic
parameters (rCBF ratio, rCBV ratio, and MTT ratio) in a
multivariate discriminant function did not improve the
sensitivity, specificity, or accuracy
(Table 3
).
The ratios of the ADC maps are shown in
Figure 2D
. The mean ADC ratio of the core was 0.62, and the
mean ADC ratios of the parts of the penumbra that recovered or
progressed to infarction were 0.89 and 0.93, respectively. There was a
statistically significant difference between the mean ratios of the 3
ROIs according to the 2-way ANOVA (F=27.87,
P<0.001), but no significant
difference was found between the part of the penumbra that recovered
and the part that progressed to infarction
(P=0.47). From
Figure 2
, it appears that ADC ratios less than
0.75
predict irreversible damage (ie, the core), because only 1 value below
this range was seen in the penumbra.
In
Figure 2A
through 2D, there was a large overlap between
individual values of ROI 1, ROI 2, and ROI 3.
Figure 3
illustrates the relationship between
rCBF and MTT for the part of the penumbra that progressed to infarction
(filled circles) and the part that recovered (open circles). The cutoff
ratios for the rCBF and the MTT ratios are shown.
|
| Discussion |
|---|
|
|
|---|
Our results are in accord with similar human studies on CBF thresholds that used PET, single-photon emission CT (SPECT), and functional MRI as well as with experimental studies. Shimosegawa et al16 performed SPECT on patients within 6 hours of onset of stroke and found mean CBF ratios for infarct and peri-infarct regions to be 0.48 and 0.75, respectively. Because follow-up CT was used in their study for morphological changes, the infarct area in the hyperacute phase could not be detected. Thus, the infarct region was a mixture of the core and penumbra progressing to infarction, and consequently, their mean ratios are somewhat higher. Using PWI and DWI, Schlaug et al12 found the mean rCBF ratio in the core and the penumbra (operationally defined as tissue that later went on to infarction) to be 0.11 and 0.37, respectively, in rough agreement with our results (0.26 and 0.42, respectively).
In a rat model of stroke, Hoehn-Berlage et
al18 found absolute CBF
thresholds at 2 hours after the infarct of the core (18 mL/100 g per
minute) and the penumbra (31 mL/100 g per minute). By using the mean
value of CBF for mixed gray/white matter in humans (50 mL/100 g per
minute),27 our mean ratios of
the core and the penumbra progressing to infarction correspond to 13
and 21 mL/100 g per minute, respectively (Table 2
). These small
discrepancies between their values and ours could be due to differences
between species.
Using the stable xenon CT technique28 or PET,29 others have found very low absolute CBF thresholds for irreversible damage (from 6 to 8.43 mL/100 mL per minute). These low values can be explained by longer inclusion periods (from 5 to 18 hours) in 1 study29 (because ischemic flow thresholds decline with time) and by differences in methodology (steal phenomenon due to CBF increase in nonischemic tissue caused by xenon inhalation) in the other study.30
In view of acute stroke management, it is essential to be able to discriminate mildly hypoperfused tissue that recovers spontaneously and more seriously hypoperfused tissue that may escape infarction if treated. Furlan et al7 found that it was not possible to discriminate between the 2 parts of the penumbra on the basis of CBF levels, as opposed to the present study and the study of Liu et al.14 According to our findings, the tissue at risk in the penumbra is characterized by an rCBF ratio of less than roughly 0.59.
In ischemic cerebrovascular disease, the initial
event is reduction of the cerebral perfusion pressure. Compensatory
vasodilation occurs, and the increase of CBV thereby increases the
CBV/CBF ratio, ie, the MTT.31
With further reduction of the perfusion pressure, the limit of cerebral
autoregulation is reached as vasodilation becomes maximal and the CBF
begins to decrease; finally, CBV also declines, with a gradual collapse
of the vessels.32
Accordingly, as CBF declines, there is a period when CBV is increased.
Because of this bimodal behavior, the CBV ratio may be difficult to
interpret in terms of prognostic value. This may explain the finding
that CBV is a poor predictor of the fate of the operationally defined
penumbra found in the present study. With the use of different
investigatory methods (PET, SPECT, and PWI), increased CBV in
ischemic tissue has been demonstrated in experimental
studies33 34 35
as well as in human
studies.3 12 15 36 37 38
In the present study, the mean rCBV value of the penumbra that
recovered was 0.94, and accordingly, we found that an unaffected CBV in
the penumbra to be a good prognostic sign, in accordance to previous
findings.39 In the
literature, the prognostic importance of a high CBV is uncertain. In a
combined PWI/SPECT study of Hatazawa et
al,15 increased rCBV had a
protective effect on the evolving infarction, but rCBV reduction <0.70
predicted irreversible damage, as in our findings. This is in conflict
with the studies of others, who found an increased rCBV ratio
(calculated as the integral under the total tissue concentration-time
curve) in the penumbra, which they defined as the hypoperfused tissue
that later progressed to
infarction.12 Accordingly,
they concluded that increased rCBV is a predictor of stroke evolution.
Finally, Liu et al,14 who
used a design similar to ours, found mean rCBV ratios of the core, the
area of infarct growth, and the eventually viable tissue of 0.25, 0.69,
and 1.13, respectively, which are in good agreement with the
present study. In summary, it remains uncertain whether increased
CBV has a protective or destructive effect on the penumbra, whereas
reduced CBV <0.70 indicates irreversible damage, according to the
present study
(Figure 2B
) and
others.39 40
We found a longer MTT with more severe ischemia, in accordance with MTT being inversely related to the perfusion pressure.34 35 37 41 42 This may be because MTT increases monotonically with perfusion pressure even though the CBV changes are bimodal with a decrease in perfusion pressure.31 MTT is regarded an excellent measure of perfusion pressure34 35 37 42 and has potential as the parameter from which patients are selected for treatment. This has recently been demonstrated by Sunshine et al,11 who used combined DWI and maps of time to peak (which has a very similar appearance to maps of "true" MTT) to select patients for intravenous or intra-arterial thrombolytic therapy. We predict that patients potentially benefiting from treatment are those in whom the MTT ratio exceeds roughly 1.63.
We found a very low mean ADC ratio in the ischemic
core (0.62). In the penumbra that recovered or progressed to
infarction, the mean ADC ratios were almost identical (0.89 and 0.93,
respectively). However, there was a remarkable resemblance between the
thresholds found in animal studies and our thresholds. In an
experimental rat study of middle cerebral artery occlusion, an ADC
reduction to 77% was found in the core (defined as tissue ATP
depletion), and a reduction to 90% was found in the penumbra (defined
as tissue acidosis). In other experimental studies, the ADC of the core
was reduced to 0.60.43 In
humans, ADC in ischemic tissue has been shown to decrease to
minimum values of
50% to 60% of the contralateral side within the
first 96 hours.2 44
Schlaug et al12 found that
ADC was reduced in the ischemic core and in the penumbra (that
latter went on to infarction) to 0.56 and 0.91, respectively.
Liu et al45 found ADC
reductions in the core, in the irreversibly damaged penumbra, and in
the reversibly damaged penumbra of 0.53, 0.98, and 1.00, respectively.
We conclude that it may not be possible to discriminate reversible and
irreversible parts of the penumbra by the use of ADC.
There are some drawbacks of the present study. The most serious is that we used large ROIs instead of a voxel-based image analysis to determine the thresholds in the study. This is unfortunate, because therapeutic decisions would be based on voxel values, not on large ROIs as applied in the present study. Voxel-based analysis requires coregistration, possibly obscuring possible thresholds because of alignment inaccuracies and tissue shrinkage. Although promising progress has been made in this respect,29 in the present study, we chose a global ROI approach to establish the existence of perfusion thresholds. However, in future studies, the hypothesized thresholds found in the present study need to be prospectively tested at voxel level on a larger patient sample before they can be applied clinically.
The fact that we used DWI abnormality to determine the ischemic core might not be correct. However, although reversal of diffusion changes has been demonstrated in animals,43 46 this has not yet been proven in humans.
Finally, recent studies on the prediction of stroke outcome have used statistical models combining SPECT and PWI15 or all PWI, DWI, and structural images.47 This approach may prove to be necessary to predict the outcome after ischemic stroke in single patients.
In conclusion, the thresholds for rCBF (<0.59) and MTT (>1.63) found in the present study might guide the selection of patients suitable for therapeutic intervention within 6 hours, such as thrombolytic therapy. These are patients in whom considerable parts of the penumbra around the ischemic core (detected on DWI) will deteriorate spontaneously without treatment. Because these thresholds are hypothesized thresholds on a limited patient sample, they need to be prospectively tested at voxel level on a larger patient sample before they can be applied clinically.
| Acknowledgments |
|---|
Received October 18, 2000; revision received January 31, 2001; accepted February 14, 2001.
| References |
|---|
|
|
|---|
2.
Warach S, Chien D,
Li W, Ronthal M, Edelman RR. Fast magnetic resonance diffusion-weighted
imaging of acute human stroke.
Neurology. 1992;42:17171723.
3.
Sorensen AG, Copen
WA, Ostergaard L, Buonanno FS, Gonzalez RG, Rordorf G, Rosen BR,
Schwamm LH, Weisskoff RM, Koroshetz WJ. Hyperacute stroke:
simultaneous measurement of relative cerebral blood volume,
relative blood volume, and mean tissue transit time.
Radiology. 1999;210:519527.
4.
Astrup J, Siesjo BK,
Symon L. Thresholds in cerebral ischemia: the ischemic
penumbra. Stroke. 1981;12:723725.
5. Hossmann KA. Viability thresholds and the penumbra of focal ischemia. Ann Neurol. 1994;36:557565.[Medline] [Order article via Infotrieve]
6.
The National
Institute of Neurological Disorders and Stroke rt-PA Stroke Study
Group. Tissue plasminogen activator for acute
ischemic stroke. N Engl
J Med. 1995;333:15811587.
7. Furlan M, Marchal G, Viader F, Derlon JM, Baron JC. Spontaneous neurological recovery after stroke and the fate of the ischemic penumbra. Ann Neurol. 1996;40:216226.[Medline] [Order article via Infotrieve]
8.
Marchal G, Beaudouin
V, Rioux P, de-la Sayette V, Le Doze F, Viader F, Derlon JM, Baron JC.
Prolonged persistence of substantial volumes of potentially viable
brain tissue after stroke: a correlative PET-CT study with voxel-based
data analysis. Stroke. 1996;27:599606.
9. Baird AE, Benfield A, Schlaug G, Siewert B, Lovblad KO, Edelman RR, Warach S. Enlargement of human cerebral ischemic lesion volumes measured by diffusion-weighted magnetic resonance imaging. Ann Neurol. 1997;41:581589.[Medline] [Order article via Infotrieve]
10. Beaulieu C, de Crespigny A, Tong DC, Moseley ME, Albers GW, Marks MP. Longitudinal magnetic resonance imaging study of perfusion and diffusion in stroke: evolution of lesion volume and correlation with clinical outcome. Ann Neurol. 1999;46:568578.[Medline] [Order article via Infotrieve]
11.
Sunshine JL, Tarr
RW, Lanzieri CF, Landis DM, Selman WR, Lewin JS. Hyperacute stroke:
ultrafast MR imaging to triage patients prior to therapy.
Radiology. 1999;212:325332.
12.
Schlaug G,
Benfield A, Baird AE, Siewert B, Lovblad KO, Parker RA, Edelman RR,
Warach S. The ischemic penumbra: operationally defined by
diffusion and perfusion MRI.
Neurology. 1999;53:15281537.
13. Jansen O, Schellinger P, Fiebach J, Hacke W, Sartor K. Early recanalisation in acute ischaemic stroke saves tissue at risk defined by MRI. Lancet. 1999;353:20362037.[Medline] [Order article via Infotrieve]
14. Liu Y, Karonen JO, Vanninen RL, Ostergaard L, Roivainen R, Nuutinen J, Perkio J, Kononen M, Hamalainen A, Vanninen EJ, et al. Cerebral hemodynamics in human acute ischemic stroke: a study with diffusion- and perfusion-weighted magnetic resonance imaging and SPECT. J Cereb Blood Flow Metab. 2000;20:910920.[Medline] [Order article via Infotrieve]
15.
Hatazawa J,
Shimosegawa E, Toyoshima H, Ardekani BA, Suzuki A, Okudera T, Miura Y.
Cerebral blood volume in acute brain infarction: a combined study with
dynamic susceptibility contrast MRI and 99 mTc-HMPAO-SPECT.
Stroke. 1999;30:800806.
16.
Shimosegawa E,
Hatazawa J, Inugami A, Fujita H, Ogawa T, Aizawa Y, Kanno I, Okudera T,
Uemura K. Cerebral infarction within six hours of onset: prediction of
completed infarction with technetium-99 m-HMPAO SPECT.
J Nucl Med. 1994;35:10971103.
17. Baron JC, Rougemont D, Bousser MG, Lebrun-Grandie P, Iba-Zizen MT, Chiras J. Local CBF, oxygen extraction fraction (OEF), and CMRO2: prognostic value in recent supratentorial infarction in humans. J Cereb Blood Flow Metab. 1983;3(suppl 1):S1S2. Abstract.
18. Hoehn-Berlage M, Norris DG, Kohno K, Mies G, Leibfritz D, Hossmann KA. 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]
19. Hoehn-Berlage M, Eis M, Back T, Kohno K, Yamashita K. Changes of relaxation times (T1, T2) and apparent diffusion coefficient after permanent middle cerebral artery occlusion in the rat: temporal evolution, regional extent, and comparison with histology. Magn Reson Med. 1995;34:824834.[Medline] [Order article via Infotrieve]
20.
Le Bihan D, Breton
E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M. MR imaging of
intravoxel incoherent motions: application to diffusion and perfusion
in neurologic disorders.
Radiology. 1986;161:401407.
21. Rosen BR, Belliveau JW, Aronen HJ, Kennedy D, Buchbinder BR, Fischman A, Gruber M, Glas J, Weisskoff RM, Cohen MS, et al. Susceptibility contrast imaging of cerebral blood volume: human experience. Magn Reson Med. 1991;22:293299.[Medline] [Order article via Infotrieve]
22. Rosen BR, Belliveau JW, Buchbinder BR, Buchbinder BR, McKinstry RC, Porkka LM, Kennedy DN, Neuder MS, Fisel CR, Aronen HJ, et al. Contrast agents and cerebral hemodynamics. Magn Reson Med. 1991;19:285292.[Medline] [Order article via Infotrieve]
23. Ostergaard L, Sorensen AG, Kwong KK, Weisskoff RM, Gyldensted C, Rosen BR. High resolution measurement of cerebral blood flow using intravascular tracer bolus passages, II: experimental comparison and preliminary results. Magn Reson Med. 1996;36:726736.[Medline] [Order article via Infotrieve]
24. Ostergaard L, Weisskoff RM, Chesler DA, Gyldensted C, Rosen BR. High resolution measurement of cerebral blood flow using intravascular tracer bolus passages, I: mathematical approach and statistical analysis. Magn Reson Med. 1996;36:715725.[Medline] [Order article via Infotrieve]
25.
Hanley JA, McNeil
BJ. A method of comparing the areas under receiver operating
characteristic curves derived from the same cases.
Radiology. 1983;148:839843.
26. Metz CE. Basic principles of ROC analysis. Semin Nucl Med. 1978;8:283298.[Medline] [Order article via Infotrieve]
27. Lassen NA. Normal average value of cerebral blood flow in younger adults is 50 ml/100 g/min. J Cereb Blood Flow Metab. 1985;5:347349.[Medline] [Order article via Infotrieve]
28.
Kaufmann AM,
Firlik AD, Fukui MB, Wechsler LR, Jungries CA, Yonas H.
Ischemic core and penumbra in human stroke.
Stroke. 1999;30:9399.
29.
Marchal G, Benali
K, Iglesias S, Viader F, Derlon JM, Baron JC. Voxel-based mapping of
irreversible ischaemic damage with PET in acute stroke.
Brain. 1999;122:23872400.
30.
Hartmann A,
Dettmers C, Schuier FJ, Wassmann HD, Schumacher HW. Effect of stable
xenon on regional cerebral blood flow and the electroencephalogram in
normal volunteers. Stroke. 1991;22:182189.
31. Powers WJ. Cerebral hemodynamics in ischemic cerebrovascular disease. Ann Neurol. 1991;29:231240.[Medline] [Order article via Infotrieve]
32.
Sette G, Baron JC,
Mazoyer B, Levasseur M, Pappata S, Crouzel C. Local brain haemodynamics
and oxygen metabolism in cerebrovascular disease: positron
emission tomography. Brain. 1989;112:931951.
33. Pappata S, Fiorelli M, Rommel T, Hartmann A, Dettmers C, Yamaguchi T, Chabriat H, Poline JB, Crouzel C, Di Giamberardino L, et al. PET study of changes in local brain hemodynamics and oxygen metabolism after unilateral middle cerebral artery occlusion in baboons. J Cereb Blood Flow Metab. 1993;13:416424.[Medline] [Order article via Infotrieve]
34.
Ferrari M, Wilson
DA, Hanley DF, Traystman RJ. Effects of graded hypotension on cerebral
blood flow, blood volume, and mean transit time in dogs.
Am J Physiol. 1992;262:H1908H1914.
35.
Zaharchuk G,
Mandeville JB, Bogdanov AAJ, Weissleder R, Rosen BR, Marota JJ,
Iadecola C, Kim SG. Cerebrovascular dynamics of autoregulation and
hypoperfusion: an MRI study of CBF and changes in total and
microvascular cerebral blood volume during hemorrhagic hypotension.
Stroke. 1999;30:21972205.
36. Powers WJ, Grubb RLJ, Raichle ME. Physiological responses to focal cerebral ischemia in humans. Ann Neurol. 1984;16:546552.[Medline] [Order article via Infotrieve]
37. Gibbs JM, Leenders KL, Wise RJ, Jones T. Evaluation of cerebral perfusion reserve in patients with carotid-artery occlusion. Lancet. 1984;1:182186.[Medline] [Order article via Infotrieve]
38.
Nighoghossian N,
Berthezene Y, Philippon B, Adeleine P, Froment JC, Trouillas P.
Hemodynamic parameter assessment with
dynamic susceptibility contrast magnetic resonance imaging in
unilateral symptomatic internal carotid artery occlusion.
Stroke. 1996;27:474479.
39.
Sakoh M, Rohl L,
Gyldensted C, Gjedde A, Ostergaard L. Cerebral blood flow and blood
volume measured by magnetic resonance imaging bolus tracking after
acute stroke in pigs: comparison with [(15)O]H(2)O positron emission
tomography. Stroke. 2000;31:19581964.
40.
Rother J, Guckel
F, Neff W, Schwartz A, Hennerici M. Assessment of regional cerebral
blood volume in acute human stroke by use of single-slice dynamic
susceptibility contrast-enhanced magnetic resonance imaging.
Stroke. 1996;27:10881093.
41. Heiss WD, Podreka I. Cerebrovascular disease. In: Wagner HN, Szabo Z, Buchanan JW, eds. Principles of Nuclear Medicine. Philadelphia, Pa: WB Saunders Co; 1995:531548.
42.
Schumann P,
Touzani O, Young AR, Baron JC, Morello R, MacKenzie ET. Evaluation of
the ratio of cerebral blood flow to cerebral blood volume as an index
of local cerebral perfusion pressure.
Brain. 1998;121:13691379.
43. Busch E, Kruger K, Allegrini PR, Kerskens CM, Gyngell ML, Hoehn Berlage M, Hossmann KA.. Reperfusion after thrombolytic therapy of embolic stroke in the rat: magnetic resonance and biochemical imaging. J Cereb Blood Flow Metab. 1998;18:407418.[Medline] [Order article via Infotrieve]
44.
Schlaug G, Siewert
B, Benfield A, Edelman RR, Warach S. Time course of the apparent
diffusion coefficient (ADC) abnormality in human stroke.
Neurology. 1997;49:113119.
45. Liu Y, Karonen J, Vanninen R, Ostergaard L, Nuutinen J, Perkio J, Kononen M, Vanninen E, Soimakallio S, Kuikka J, et al. Cortical cerebral hemodynamics in human acute ischemic stroke: a study with combined diffusion weighted and perfusion weighted MRI. In: Proceedings of the ISMRM Eighth Scientific Meeting; April 17, 2000; Denver, Colo. 2000:449. Abstract.
46. Davis D, Ulatowski J, Eleff S, Izuta M, Mori S, Shungu D, van Zijl PC. 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]
47. Wu O, Sorensen AG, Bakker D, Bakker D, Buonanno F, Copen WA, Gonzalez RG, Harmath C, Ostergaard L, Rosen BR, et al. Evaluation of diffusion- and perfusion-based predictive models of tissue outcome in hyperacute human cerebral ischemia. In: Proceedings of the ISMRM Sixth Scientific Meeting; April 1824, 1998; Sydney, Australia. 2000;1:235. Abstract.
This article has been cited by other articles:
![]() |
O. Zaro-Weber, W. Moeller-Hartmann, W.-D. Heiss, and J. Sobesky The Performance of MRI-Based Cerebral Blood Flow Measurements in Acute and Subacute Stroke Compared With 15O-Water Positron Emission Tomography: Identification of Penumbral Flow Stroke, July 1, 2009; 40(7): 2413 - 2421. [Abstract] [Full Text] [PDF] |
||||
![]() |
B. D. Murphy, A. J. Fox, D. H. Lee, D. J. Sahlas, S. E. Black, M. J. Hogan, S. B. Coutts, A. M. Demchuk, M. Goyal, R. I. Aviv, et al. White Matter Thresholds for Ischemic Penumbra and Infarct Core in Patients with Acute Stroke: CT Perfusion Study Radiology, June 1, 2008; 247(3): 818 - 825. [Abstract] [Full Text] [PDF] |
||||
![]() |
K. A. Strauss, J. Lazovic, M. Wintermark, and D. H. Morton Multimodal imaging of striatal degeneration in Amish patients with glutaryl-CoA dehydrogenase deficiency Brain, July 1, 2007; 130(7): 1905 - 1920. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. Kawata, M. Sekino, S. Takamoto, S. Ueno, S. Yamaguchi, K. Kitahori, H. Tsukihara, Y. Suematsu, M. Ono, N. Motomura, et al. Retrograde cerebral perfusion with intermittent pressure augmentation provides adequate neuroprotection: Diffusion- and perfusion-weighted magnetic resonance imaging study in an experimental canine model J. Thorac. Cardiovasc. Surg., October 1, 2006; 132(4): 933 - 940. [Abstract] [Full Text] [PDF] |
||||
![]() |
E. Bandera, M. Botteri, C. Minelli, A. Sutton, K. R. Abrams, and N. Latronico Cerebral Blood Flow Threshold of Ischemic Penumbra and Infarct Core in Acute Ischemic Stroke: A Systematic Review Stroke, May 1, 2006; 37(5): 1334 - 1339. [Abstract] [Full Text] [PDF] |
||||
![]() |
R.G. Gonzalez Imaging-guided acute ischemic stroke therapy: From "time is brain" to "physiology is brain". AJNR Am. J. Neuroradiol., April 1, 2006; 27(4): 728 - 735. [Abstract] [Full Text] [PDF] |
||||
![]() |
Y.W. Kim, H.J. Kim, B.M. Cho, T.Y. Moon, and C.K. Eun The study of cerebral hemodynamics in the hyperacute stage of fat embolism induced by triolein emulsion. AJNR Am. J. Neuroradiol., February 1, 2006; 27(2): 398 - 401. [Abstract] [Full Text] [PDF] |
||||
![]() |
P.W. Schaefer, L. Roccatagliata, C. Ledezma, B. Hoh, L.H. Schwamm, W. Koroshetz, R.G. Gonzalez, and M.H. Lev First-Pass Quantitative CT Perfusion Identifies Thresholds for Salvageable Penumbra in Acute Stroke Patients Treated with Intra-arterial Therapy AJNR Am. J. Neuroradiol., January 1, 2006; 27(1): 20 - 25. [Abstract] [Full Text] [PDF] |
||||
![]() |
C.S. Rivers, J.M. Wardlaw, P.A. Armitage, M.E. Bastin, T.K. Carpenter, V. Cvoro, P.J. Hand, and M.S. Dennis Do Acute Diffusion- and Perfusion-Weighted MRI Lesions Identify Final Infarct Volume in Ischemic Stroke? Stroke, January 1, 2006; 37(1): 98 - 104. [Abstract] [Full Text] [PDF] |
||||
![]() |
R. J. Seitz, S. Meisel, P. Weller, U. Junghans, H.-J. Wittsack, and M. Siebler Initial Ischemic Event: Perfusion-weighted MR Imaging and Apparent Diffusion Coefficient for Stroke Evolution Radiology, December 1, 2005; 237(3): 1020 - 1028. [Abstract] [Full Text] [PDF] |
||||
![]() |
P.-S. Loh, K. S. Butcher, M. W. Parsons, L. MacGregor, P. M. Desmond, B. M. Tress, and S. M. Davis Apparent Diffusion Coefficient Thresholds Do Not Predict the Response to Acute Stroke Thrombolysis Stroke, December 1, 2005; 36(12): 2626 - 2631. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. Koga, D. C. Reutens, P. Wright, T. Phan, R. Markus, B. Pedreira, G. Fitt, I. Lim, and G. A. Donnan The Existence and Evolution of Diffusion-Perfusion Mismatched Tissue in White and Gray Matter After Acute Stroke Stroke, October 1, 2005; 36(10): 2132 - 2137. [Abstract] [Full Text] [PDF] |
||||
![]() |
T. Kucinski, D. Naumann, R. Knab, V. Schoder, S. Wegener, J. Fiehler, A. Majumder, J. Rother, and H. Zeumer Tissue at Risk Is Overestimated in Perfusion-Weighted Imaging: MR Imaging in Acute Stroke Patients without Vessel Recanalization AJNR Am. J. Neuroradiol., April 1, 2005; 26(4): 815 - 819. [Abstract] [Full Text] [PDF] |
||||
![]() |
L Derex, M Hermier, P Adeleine, J-B Pialat, M Wiart, Y Berthezene, F Philippeau, J Honnorat, J-C Froment, P Trouillas, et al. Clinical and imaging predictors of intracerebral haemorrhage in stroke patients treated with intravenous tissue plasminogen activator J. Neurol. Neurosurg. Psychiatry, January 1, 2005; 76(1): 70 - 75. [Abstract] [Full Text] [PDF] |
||||
![]() |
C. S. Kidwell, J. R. Alger, and J. L. Saver Evolving Paradigms in Neuroimaging of the Ischemic Penumbra Stroke, November 1, 2004; 35(11_suppl_1): 2662 - 2665. [Abstract] [Full Text] [PDF] |
||||
![]() |
D. G. Na, V. N. Thijs, G. W. Albers, M. E. Moseley, and M. P. Marks Diffusion-Weighted MR Imaging in Acute Ischemia: Value of Apparent Diffusion Coefficient and Signal Intensity Thresholds in Predicting Tissue at Risk and Final Infarct Size AJNR Am. J. Neuroradiol., September 1, 2004; 25(8): 1331 - 1336. [Abstract] [Full Text] [PDF] |
||||
![]() |
A. Davalos, M. Blanco, S. Pedraza, R. Leira, M. Castellanos, J. M. Pumar, Y. Silva, J. Serena, and J. Castillo The clinical-DWI mismatch: A new diagnostic approach to the brain tissue at risk of infarction Neurology, June 22, 2004; 62(12): 2187 - 2192. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. L. Bykowski, L. L. Latour, and S. Warach More Accurate Identification of Reversible Ischemic Injury in Human Stroke by Cerebrospinal Fluid Suppressed Diffusion-Weighted Imaging Stroke, May 1, 2004; 35(5): 1100 - 1106. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. Yamada, S. Yoshimura, Y. Kaku, T. Iwama, H. Watarai, T. Andoh, and N. Sakai Prediction of Neurologic Deterioration in Patients with Lacunar Infarction in the Territory of the Lenticulostriate Artery Using Perfusion CT AJNR Am. J. Neuroradiol., March 1, 2004; 25(3): 402 - 408. [Abstract] [Full Text] [PDF] |
||||
![]() |
S. Wegener, B. Gottschalk, V. Jovanovic, R. Knab, J. B. Fiebach, P. D. Schellinger, T. Kucinski, G. J. Jungehulsing, P. Brunecker, B. Muller, et al. Transient Ischemic Attacks Before Ischemic Stroke: Preconditioning the Human Brain?: A Multicenter Magnetic Resonance Imaging Study Stroke, March 1, 2004; 35(3): 616 - 621. [Abstract] [Full Text] [PDF] |
||||
![]() |
C. S. Kidwell, J. R. Alger, and J. L. Saver Beyond Mismatch: Evolving Paradigms in Imaging the Ischemic Penumbra With Multimodal Magnetic Resonance Imaging Stroke, November 1, 2003; 34(11): 2729 - 2735. [Abstract] [Full Text] [PDF] |
||||
![]() |
K. Butcher, M. Parsons, T. Baird, A. Barber, G. Donnan, P. Desmond, B. Tress, and S. Davis Perfusion Thresholds in Acute Stroke Thrombolysis Stroke, September 1, 2003; 34(9): 2159 - 2164. [Abstract] [Full Text] [PDF] |
||||
![]() |
B. F. Tomandl, E. Klotz, R. Handschu, B. Stemper, F. Reinhardt, W. J. Huk, K.E. Eberhardt, and S. Fateh-Moghadam Comprehensive Imaging of Ischemic Stroke with Multisection CT RadioGraphics, May 1, 2003; 23(3): 565 - 592. [Abstract] [Full Text] [PDF] |
||||
![]() |
P. W. Schaefer, Y. Ozsunar, J. He, L. M. Hamberg, G. J. Hunter, A. G. Sorensen, W. J. Koroshetz, and R. G. Gonzalez Assessing Tissue Viability with MR Diffusion and Perfusion Imaging AJNR Am. J. Neuroradiol., March 1, 2003; 24(3): 436 - 443. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. Eyding, W. Wilkening, M. Reckhardt, G. Schmid, S. Meves, H. Ermert, H. Przuntek, and T. Postert Contrast Burst Depletion Imaging (CODIM): A New Imaging Procedure and Analysis Method for Semiquantitative Ultrasonic Perfusion Imaging Stroke, January 1, 2003; 34(1): 77 - 83. [Abstract] [Full Text] [PDF] |
||||
![]() |
I. Fukuda and M. Wada Intraarterial thrombolysis for perioperative stroke in patients undergoing cardiac operations Ann. Thorac. Surg., December 1, 2002; 74(6): 2227 - 2228. [Full Text] [PDF] |
||||
![]() |
M. H. Lev, W. J. Koroshetz, L. H. Schwamm, R. G. Gonzalez, and T. Tatlisumak CT or MRI for Imaging Patients with Acute Stroke: Visualization of "Tissue at Risk"? Stroke, December 1, 2002; 33(12): 2736 - 2737. [Full Text] [PDF] |
||||
![]() |
D. G. Nabavi, S. P. Kloska, E.-M. Nam, M. Freund, C. G. Gaus, E. Klotz, W. Heindel, and E. B. Ringelstein MOSAIC: Multimodal Stroke Assessment Using Computed Tomography: Novel Diagnostic Approach for the Prediction of Infarction Size and Clinical Outcome Stroke, December 1, 2002; 33(12): 2819 - 2826. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. Fiehler, M. von Bezold, T. Kucinski, R. Knab, B. Eckert, O. Wittkugel, H. Zeumer, and J. Rother Cerebral Blood Flow Predicts Lesion Growth in Acute Stroke Patients Stroke, October 1, 2002; 33(10): 2421 - 2425. [Abstract] [Full Text] [PDF] |
||||
![]() |
F. Calamante, D.G. Gadian, and A. Connelly Quantification of Perfusion Using Bolus Tracking Magnetic Resonance Imaging in Stroke: Assumptions, Limitations, and Potential Implications for Clinical Use Stroke, April 1, 2002; 33(4): 1146 - 1151. [Abstract] [Full Text] [PDF] |
||||
![]() |
C. B. Grandin, T. P. Duprez, A. M. Smith, C. Oppenheim, A. Peeters, A. R. Robert, and G. Cosnard Which MR-derived Perfusion Parameters are the Best Predictors of Infarct Growth in Hyperacute Stroke? Comparative Study between Relative and Quantitative Measurements Radiology, May 1, 2002; 223(2): 361 - 370. [Abstract] [Full Text] [PDF] |
||||
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Stroke Home | Subscriptions | Archives | Feedback | Authors | Help | AHA Journals Home | Search Copyright © 2001 American Heart Association, Inc. All rights reserved. Unauthorized use prohibited. |