Predicting Tissue Viability in Ischemic Stroke
with Diffusion and Perfusion MRI
Yu Xie1,2, Liang Liao1,3, Francis Guillemin4, Bailiang Chen1,5, Jacques Felblinger1,5, Gabriela Hossu1,5, Serge Bracard1,3*
1Université de Lorraine, Inserm, IADI, France
2Department of Neurology, Zhongnan Hospital of Wuhan University, China
3Department of Diagnostic and Interventional Neuroradiology, France
4CHRU-Nancy, Inserm, Université de Lorraine, France
5CHRU-Nancy, Inserm, Université de Lorraine, France
Submission: April 22, 2019; Published: May 16, 2019
*Corresponding author: Serge Bracard, Department of Diagnostic and Interventional Neuroradiology, University Hospital of Nancy, 54035 Nancy, France
How to cite this article: Yu Xie, Liang Liao, Francis Guillemin, Bailiang Chen, Jacques Felblinger, Gabriela Hossu, Serge Bracard. Predicting Tissue Viability
in Ischemic Stroke with Diffusion and Perfusion MRI. Open Access J Neurol Neurosurg. 2019; 10(5): 555799.DOI:
Background: Identification of salvageable tissue is crucial for acute ischemic stroke evaluation. Magnetic resonance imaging (MRI) could be very useful but its role has not been fully established.
Objectives: We aimed to assess whether parameters of diffusion-weighted imaging and perfusion-weighted imaging could predict tissue viability.
Methods: 36 ischemic stroke patients who underwent baseline MRI and day-7 images were included. Both initial abnormal diffusion areas and perfusion-diffusion mismatch areas were separated into parts which presented as normal tissue on day-7 images and those which evolved into infarction. The roles of diffusion and perfusion parameters in predicting tissue viability were analyzed at region-of-interest level. Receiving operating characteristic curves were performed to select appropriate parameters and determine the optimal thresholds.
Results: 7/36 patients presented normalized tissue in initial abnormal diffusion areas. 34/36 patients had normalized tissue in perfusion-diffusion mismatch areas. In initial abnormal diffusion areas, the area under the curve of mean apparent diffusion coefficient (ADCmean), relative apparent diffusion coefficient (rADC), relative cerebral blood flow (rCBF) and relative cerebral blood volume (rCBV) were 0.79, 0.81, 0.76 and 0.75; the thresholds of 623×10-6 mm2/s, 0.80, 0.47 and 0.82 were selected to identify salvageable tissue, respectively. In mismatch areas, the area under the curve of ADCmean, rADC and rCBF were 0.75, 0.72 and 0.68, with thresholds of 785×10-6 mm2/s, 0.98 and 0.63 selected, respectively.
Conclusion: Our study suggested that ADC and rCBF were optimal candidates for tissue viability prediction in acute ischemic stroke, in both initial abnormal diffusion areas and perfusion-diffusion mismatch areas.
Keywords: Stroke; Magnetic resonance imaging; Diffusion Magnetic Resonance Imaging; Cerebrovascular Circulation; Tissue survival
Abbrevations: DWI: Diffusion-weighted Imaging; PWI: Perfusion-Weighted Imaging; ADC: Apparent Diffusion Coefficient; CBF: Cerebral Blood Flow; MTT: Mean Transit Time; NIHSS: National Institutes of Health Stroke Scale; CPP: Comitéde Protection des Personnes; CT: Computed Tomography
MRI is increasingly used in ischemic stroke assessment. Diffusion-weighted Imaging (DWI) has been established as the most accurate technique for acute ischemic stroke diagnosis . Perfusion-Weighted Imaging (PWI) may complete the stroke evaluation by providing tissue microcirculation information . Ischemic penumbra is a region at the risk of infarction but
still has the potential to be salvaged . As the target of acute phase treatment, penumbra evaluation is of great clinical importance. PWI-DWI mismatch has been assumed to represent the penumbra and has been included as an evaluation index for patient selection in several clinical trials [4-7]. However, the substitution of penumbra by PWI-DWI mismatch remains uncertain. On the one hand, the initial DWI hyperintensity area
consists not only the irreversibly damaged “core”, but also tissue
at risk which could be salvaged if blood flow is restored at an
early time point . On the other hand, PWI abnormality often
overestimate the penumbra by including oligemia . Therefore,
tissue viability should be assessed more precisely other than
Apparent Diffusion Coefficient (ADC) has been proposed to
differentiate tissue at risk and the ischemic core. Purushotham et
al.  suggested a threshold of 620×10-6 mm2/s for delineation
of ischemic core. However, this point of view was challenged,
previous study has demonstrated that the fate of tissue could not
be predicted based on the ADC value alone . Widely varied
thresholds of different perfusion parameters were presented to
evaluate tissue viability. Cerebral Blood Flow (CBF) ranged from
18 to 37 mL/100g/min and Mean Transit Time (MTT) ranged
from 1.8 to 8.3 seconds relative to the contralateral side were
reported to identify the tissue at risk . A threshold of Tmax >
2s delay was demonstrated to be a reliable estimate of ischemic
penumbra . Currently, there is no consensus on MRI-based
tissue viability thresholds in ischemic stroke.
In our study, we sought proper diffusion and perfusion
parameters which could predict tissue viability in both initial
abnormal diffusion areas and PWI-DWI mismatch areas.
We analyzed acute ischemic stroke patients due to proximal
intracranial arterial occlusion. These patients generally present
more severe clinical symptoms and carry a worse prognosis,
thus the treatment decision needs to be made properly and
We analyzed patients in the THRACE study (Clinical Trial
Registration-URL: http://www.clinicaltrials.gov. Unique identifier
NCT01062698), a multicentric study in France underwent
from 2009 to 2015, comparing intravenous thrombolysis plus
mechanical thrombectomy and intravenous thrombolysis alone
in patients with acute ischemic stroke due to proximal arterial
occlusion, aged 18 to 80 years, and with a National Institutes of
Health Stroke Scale (NIHSS) score of 10 to 25. The study design
and patient inclusion criteria have been described in detail previously
. The study protocol was approved by the Comité de
Protection des Personnes (CPP) III Nord Est Ethics Committee
and the research boards of the participating centers. All patients
or their legal representatives provided written informed consent.
In this study, we included patients who received baseline
MRI exam, including DWI, PWI, Fluid Attenuation Inversion Recovery
(FLAIR) and time-of-flight MR angiography, followed by
MRI or Computed Tomography (CT) on day-7. In 412 patients
included in the THRACE study, 36 patients finally met the inclusion
criteria of our work (Figure 1). Compare to the final sample,
excluded patients were similar in terms of age, sex, baseline NIHSS
score and time from stroke onset to imaging. All the included
patients received intravenous thrombolysis; 12 patients also
received an additional mechanical thrombectomy.
Imaging was performed according to the established local
routine. MRI was performed on 1.5T MR Scanners (Signa HDxt,
General Electric Healthcare, WI, USA; Intera/Achieva, Philips
medical systems, Best, the Netherlands). The baseline DWI
was performed using a single-shot, pulsed gradient spin echo
sequence with echo planar imaging (EPI) read-out (b-value
0 and 1000s/mm2). The baseline PWI data were acquired
after a bolus of intravenous gadolinium by using the dynamic
susceptibility contrast technique and a single-shot, gradient
echo EPI sequence. Day-7 FLAIR sequence was performed in 7
patients to assess the final infarction. The rest 29 patients were
evaluated by CT. CT images were non-contrast-enhanced with
reconstruction matrix 512×512, resolution 0.4×0.4×1.0mm3 ~
0.4×0.4×2.5mm3. (LightSpeed VCT, GE medical system, WI, USA;
SOMATOM Sensation 16, Siemens AG, Forchheim, Germany;
Aquilion ONE, Toshiba, Japan). More details about MRI sequence
parameters are listed in Table 1.
MRI: Magnetic Resonance Imaging; DWI: Diffusion-Weighted Imaging; PWI: Perfusion-Weighted Imaging; FLAIR: Fluid Attenuation Inversion
Recovery. *: ranges of parameter values are presented.
Baseline MRI and day-7 images from the same patient were
co-registered by ORS® (Object Research Systems) Visual® (Montreal,
Canada). An experienced neuroradiologist (with experience
of reading stroke imaging >5 years, reader 1) checked all
the registration results in order to ensure adequate alignment.
Post processing of DWI and PWI data was performed in Olea
Sphere® (Olea Medical SAS, La Ciotat, France). ADC maps were
calculated based on DWI data. MTT, CBF, Cerebral Blood Volume
(CBV) and Tmax (time to peak of the deconvolved tissue residue
function) maps were calculated from PWI data. The experienced
neuroradiologist (reader 1) and a junior neurologist (with experience
of reading stroke imaging <5 years) (reader 2), blind
to the clinical information, read all the images separately, and
manually outlined the 2D abnormal regions on all the pathological
slices of the post processed DWI and PWI data as well as registered
day-7 images. The window level was set to its maximal
visual extent of each volume. The criteria to define the abnormal
regions in the images were
I. The abnormal hyperintense areas on baseline DWI
which correspond to a decreased ADC value;
II. The hypo perfused tissue on baseline Tmax maps
(Tmax > 6s), as proposed by previous study ;
III. The abnormal hyperintensity on day-7 FLAIR images
or hypodense areas on day-7 CT data. Baseline FLAIR images
were used as references to solve the confusion brought by
the “T2 shine-through” effect when delineating abnormal
hyperintense areas on baseline DWI.
The PWI-DWI mismatch profile criteria corresponded to
VolumePWI/VolumeDWI > 1.2 and VolumePWI - VolumeDWI ≥ 10mL,
according to the criteria used in DEFUSE and EPITHET studies
Four types of Regions Of Interest (ROIs) were derived from
the above mentioned abnormal regions the initial abnormal
diffusion areas which appeared as normal tissue on day-7 image
(DN) and which evolved into infarction (DI), the PWI-DWI
mismatch areas which appeared as normal tissue on day-7 image
(MN) and which evolved into infarction (MI). For each types of
ROI, mirror regions were drawn in the contralateral hemisphere.
All the voxels with ADC < 200×10-6 mm2/s or > 1200×10-6 mm2/s
were considered as artifacts or cerebrospinal fluid and were
eliminated. Examples of the ROIs were illustrated in (Figure 2).
Mean value of ADC (ADCmean), MTT (MTTmean), CBV (CBVmean)
and CBF (CBFmean) were calculated for each ROI and the
symmetric regions. By dividing the values in each ROI and their
corresponding symmetric region, the lesion-contralateral ratios
(rADC, rMTT, rCBV and rCBF) were obtained. Parameters in ROIs
evolving into infarction on day-7 image were compared with
those which did not.
ROC curves of parameters which presented significant difference
in ROI-based comparison were plotted, in initial abnormal
diffusion areas and in mismatch areas separately. Area under the
ROC curve (AUC) was calculated for each parameter. The optimal
parameter thresholds distinguishing the regions evolved into infarction
and which normalized were selected.
Categorical variables were presented as proportions; continuous
variables were tested for normality and presented as
mean ± SD if normally distributed, or as median and interquartile
range (IQR) if not. Comparisons of ROI-based parameter
values were performed by Wilcoxon test. P-values were two-sided
and p=0.05 was chosen as the significance level. ROC curves
were plotted by R package pROC . The optimal parameter
thresholds were determined by Youden index . To evaluate
the reproducibility of two readers, we calculated the intraclass
correlation coefficient of ADCmean in each category of ROI. Statistical
analyses were performed using statistical software R (R
Foundation for Statistical Computing, Vienna, Austria).
The included 36 patients were composed of 14 women and
22 men with median age of 71 (IQR 59-77) years. The baseline
characteristics were presented in Table 2. 7/36 (19.4%) patients
had DN tissue, with a volume of 5.29 (IQR 3.35-8.39) mL (i.e.
5.6% of the initial diffusion abnormal areas). 34/36 (94.4%)
patients presented MN tissue, with a volume of 44.34 (IQR
31.02-61.22) mL (i.e. 72.6% of the mismatch areas).
Continuous variables are presented as median (interquartile range);
categorical variables are presented as no. (%). NIHSS: National
Institutes of Health Stroke Scale.
Intraclass correlation coefficient of ROI-based ADCmean
between two readers was 0.98 with 95% confidence interval
(CI) 0.96-0.99. Accordingly, the following results are based on
measurements obtained by reader 1. ADCmean, rADC, rCBF and
rCBV were significantly different between DI and DN: ADCmean
was 617.14±54.74×10-6 mm2/s in DI and 677.21±65.67×10-
6 mm2/s in DN (p=0.02); rADC was 0.76±0.05 and 0.84±0.08
respectively (p=0.01); rCBF was 0.49±0.15 and 0.63±0.14
respectively (p=0.03); rCBV was 0.80±0.32 and 1.04±0.28
respectively (p=0.04). ADCmean, rADC and rCBF were significantly
different in MI and MN: ADCmean was 783.04±37.40×10-6 mm2/s
in MI and 821.99±39.73×10-6 mm2/s in MN (p=0.001); rADC
was 0.95±0.05 and 0.99±0.04 respectively (p=0.01); rCBF was
0.63±0.18 and 0.71±0.16 respectively (p=0.02). The other
parameters showed no significant differences. Results are listed
in Table 3.
ROI: Region of interest; DI: the initial abnormal diffusion areas which evolved into infarction on day-7 image; DN: the initial abnormal diffusion areas which appeared as normal tissue on day-7 image; MI: the PWI-DWI mismatch areas which evolved into infarction on day-7 image; MN:the PWI-DWI mismatch areas which appeared as normal tissue on day-7 image; CI: confidence interval; Parameter values are presented asmean ± SD;*: p value<0.05.
ROC curves of parameters in initial abnormal diffusion areas
and PWI-DWI mismatch areas are presented in Figure 3 & Figure
4. AUC of each parameter and thresholds calculated by Youden
index for distinguishing the salvageable tissue are listed in Table
4 & Table 5.
AUC: Area under the ROC curve; CI: confidence interval.
AUC: Area under the ROC curve; CI: confidence interval
The role of MRI in tissue viability prediction in acute
ischemic stroke is promising. It can help the clinicians to select
appropriate patients for treatment. Our work investigated
tissue viability in both initial abnormal diffusion areas and PWIDWI
mismatch areas and suggested that ADC and rCBF may be
optimal candidate for tissue viability prediction.
Combined Positron Emission Tomography (PET)-MRI studies
have suggested that DWI lesions reflect variable metabolic
disruption, thus may not always represent irreversibly damaged
tissue . The proportion of patients presenting normalization
of abnormal diffusion areas (19.4%) was close to another study
(19.7%)8, but lower than 50% demonstrated by Labeyrie et
al.  and 67% reported by Loh et al. . The proportion of
initial diffusion abnormal area presenting normalization (5.6%)
was lower than 11% reported by Labeyrie et al.  Recent
animal study also demonstrated a higher proportion of diffusion
lesion reversal (8.3-51.9% for early reversal and 41.7-77.8% for
sustained reversal) .
Both diffusion and perfusion parameters showed relevance in
distinguishing the regions that evolved into infarction with those
which did not. The effective role of ADC value was in line with
the previous results [8,10,20] ROC analysis showed that rADC
and ADCmean are the most promising parameters. The optimal
ADCmean threshold was in accordance with Purushotham’s study
who proposed 620×10-6 mm2/s, although voxel-based method
was used by them . The rADC threshold of 0.80 determined
in our study was similar to the result of an animal study, in which
rADC of 0.77 was decided as a good estimate for the breakdown
of energy metabolism .
PWI parameters were investigated in previous studies for
their potential value to predict tissue viability in DWI lesions.
Carrera et al. proposed that MTT may improve infarction
prediction within DWI lesions  While another study
presented that CBV maps could not reliably substitute for DWI
in identifying the infarct core . Nevertheless, these studies
only assessed one parameter. Our results indicated that the
prediction of initial abnormal diffusion tissue destiny could be
improved by applying rCBF or rCBV thresholds. Voxel-based
analyses on large sample studies are needed to confirm the role
of PWI parameters in ischemic core assessment.
The introduction of PWI-DWI mismatch as a surrogate
marker of penumbra has opened a new perspective in stroke
imaging. Compared to initial abnormal diffusion areas, higher
frequency of normalization in mismatch areas in our cohort
could be explained by stroke pathophysiology. DWI lesions occurred in regions of maximal perfusion deficit and thus had
less opportunity for recovery . Previous comparative PETMRI
studies detected different PWI parameters for estimating
penumbral flow thresholds, Tmax (> 5.5 seconds), CBF (< 21.7
mL/100g/min) and time to peak (TTP, > 4.2 seconds) have been
proposed. [25,26] Numerous thresholds for distinguishing tissue
“at risk” and “not at risk” were presented without consensus,
with rCBF value ranged from 0.58 to 0.61,12 which was similar
with the value suggested in our study (0.63).
The role of ADC value was usually investigated within DWI
lesion. Our results revealed that ADC could also be implicated in
the prediction of tissue viability in mismatch area, even better
than perfusion derived parameters. Our results was similar with
previous study which proposed a ADC threshold of 803 ×10-6
mm2/s as the best discriminator for viable tissue in mismatch
area . ADC is a quantitative measurement of water diffusion,
which decreases at the acute phase of stroke because of a net
shift of water from the extracellular to intracellular space. We
could infer that PWI-DWI mismatch area also present various
degrees of decreased ADC value, but without evident intensity
alteration on DWI.
Our study has the following limitations. Firstly, CT was
used in the majority of our patients to evaluate the final infarct.
Although tracing the abnormal hypodensity manually on CT
was reported to be reproducible in measuring infarct volume,
 it would be more precise using MRI. Secondly, our sample
is rather small, and the imaging parameters are heterogeneous.
The primary objective of THRACE study was the evaluation
of stroke treatment and imaging was done according to the
established local routine. In our sub-study we only focused on
patients who had baseline DWI and PWI and follow-up day-7
images. The variation of imaging parameter could be a source
of bias; on the other hand, it approaches the real situation of
clinical practice. Thirdly, tissue viability was analyzed regardless
of other confounding factors, such as collateral circulation
and reperfusion status, due to the absence of angiography for
patients in intravenous thrombolysis group. Lastly, metabolic
status is different between brain compartments, with white
matter more resistant to ischemia than grey matter [28,29].
Considering them separately could improve the accuracy of
viable tissue identification.
Our study proposed that ADC and rCBF may be optimal
candidates in predicting tissue viability in acute ischemic stroke.
Tissue with higher ADC value and higher rCBF value tended to
normalize in initial abnormal diffusion areas and in PWI-DWI
YX, GH, SB contributed to the conception and design of the
study. Acquisition and analysis of data were performed by YX,
LL, FG, BC, JF, GH, SB. YX, LL, FG, BC, JF, GH, SB drafted text and/
or prepared figures.