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REPORT
Identifying the ischaemic penumbra using
pH-weighted magnetic resonance imaging
George W. J. Harston,
1
Yee Kai Tee,
2,3
Nicholas Blockley,
4
Thomas W. Okell,
4
Sivarajan Thandeswaran,
1
Gabriel Shaya,
1
Fintan Sheerin,
5
Martino Cellerini,
5
Stephen Payne,
2
Peter Jezzard,
4
Michael Chappell
2
and James Kennedy
1
The original concept of the ischaemic penumbra suggested imaging of regional cerebral blood flow and metabolism would be required
to identify tissue that may benefit from intervention. Amide proton transfer magnetic resonance imaging, a chemical exchange satur-
ation transfer technique, has been used to derive cerebral intracellular pH in preclinical stroke models and has been proposed as a
metabolic marker of ischaemic penumbra. In this proof of principle clinical study, we explored the potential of this pH-weighted
magnetic resonance imaging technique at tissue-level. Detailed voxel-wise analysis was performed on data from a prospective cohort of
12 patients with acute ischaemic stroke. Voxels within ischaemic core had a more severe intracellular acidosis than hypoperfused tissue
recruited to the final infarct (P50.0001), which in turn was more acidotic than hypoperfused tissue that survived (P50.0001). In
addition, when confined to the grey matter perfusion deficit, intracellular pH (P50.0001), but not cerebral blood flow (P= 0.31),
differed between tissue that infarcted and tissue that survived. Within the presenting apparent diffusion coefficient lesion, intracellular
pH differed between tissue with early apparent diffusion lesion pseudonormalization and tissue with true radiographic recovery. These
findings support the need for further investigation of pH-weighted imaging in patients with acute ischaemic stroke.
1 Acute Stroke Programme, Radcliffe Department of Medicine, University of Oxford, UK
2 Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, UK
3 Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku
Abdul Rahman, Malaysia
4 Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
5 Department of Neuroradiology, Oxford University Hospitals NHS Trust, Oxford, UK
Correspondence to: Dr James Kennedy,
Acute Vascular Imaging Centre, University of Oxford, Level 2,
John Radcliffe Hospital, Headington, Oxford, OX3 9DU, UK
E-mail: james.kennedy@rdm.ox.ac.uk
Keywords: ischaemic stroke; magnetic resonance imaging; chemical exchange saturation transfer; acidosis; pH-weighted imaging
Abbreviations: ADC = apparent diffusion coefficient; APTR* = amide proton transfer ratio; ASL = arterial spin labelling;
CBF = cerebral blood flow; PWI = perfusion weighted imaging
Introduction
The original concept of the ischaemic penumbra suggested
that concurrent imaging of regional cerebral blood flow
(CBF) and metabolism would be required to identify
tissue at risk that may benefit from intervention (Astrup
et al., 1981). Although there have been major technological
advances in acute stroke imaging since this was proposed,
the search for robust evidence to support individual ima-
ging-guided treatment decisions is ongoing (Kidwell, 2013;
Wintermark et al., 2013). A contributing factor may be
that, aside from PET imaging, the development of
doi:10.1093/brain/awu374 BRAIN 2015: 138; 36–42 |36
Received May 15, 2014. Revised September 8, 2014. Accepted October 1, 2014
ßThe Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits
non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
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metabolic imaging markers has been limited when com-
pared to the focus on methods to assess perfusion.
Cerebral intracellular pH is maintained until CBF drops
to levels associated with irreversible infarction (Hossmann,
1994). Amide proton transfer MRI, a chemical exchange
saturation transfer imaging technique, can be used to gen-
erate a pH-weighted imaging signal through the assessment
of the base-catalyzed and, hence, pH-dependent intracellu-
lar transfer of protons between amide groups and water
(Zhou et al., 2003). It has been proposed that pH-weighted
imaging may improve the delineation of tissue at risk by
separating benign oligaemia from an acidotic ischaemic
penumbra (Zhou and van Zijl, 2011). Preclinical studies
have supported this potential as a biomarker of the ischae-
mic penumbra (Cho et al., 2007; Sun et al., 2007, 2011),
but to date the limited clinical application of pH-weighted
imaging has not systematically demonstrated its potential in
patients exclusively with acute stroke (Sun et al., 2010;
Zhao et al., 2011; Tee et al., 2014; Tietze et al., 2014).
Using detailed voxel-wise analysis to understand tissue-
level effects, this proof of principle clinical study assesses
the relationship between intracellular pH and final tissue
outcome in data from a prospective cohort of patients
with acute ischaemic stroke. In doing so, this study ex-
plores how pH-weighted imaging may be used in conjunc-
tion with the established acute stroke imaging modalities,
diffusion and perfusion weighted imaging, to define the
ischaemic penumbra.
Materials and methods
Patients
Patients presenting with ischaemic stroke within 12 h of symp-
tom onset (using the last seen well principle) regardless of age or
stroke severity were recruited into a prospective observational
cohort study following informed consent or agreement from a
representative according to protocols approved by UK National
Research Ethics Service committees (ref: 12/SC/0292 and 13/SC/
0362). Exclusion criteria included the presence of a contraindi-
cation for MRI and a diffusion weighted imaging or arterial spin
labelling perfusion weighted imaging (ASL-PWI) lesion 55mm
in axial diameter. MRI was performed at presentation, 24 h, 1
week, and 1 month. All clinical decisions, for example to throm-
bolyze the patient if indicated, were made prior to enrolment in
order not to introduce any delay to best clinical care. The re-
search scanning often took place while thrombolysis was
taking place (Table 1).
Image acquisition
A Siemens 3 T Verio scanner was used at all time points.
Scanning protocols included diffusion weighted imaging
(three directions, 1.8 1.8 2.0 mm, field of view = 240 mm,
four averages, b = 0 and 1000 s/mm
2
, repetition time =
9000 ms, echo time = 98 ms, 50 slices, 2 min 53 s) with appar-
ent diffusion coefficient (ADC) calculation; T
1
-weighted MP-
RAGE (1.8 1.8 1.0 mm, field of view = 228 mm, repetition
time = 2040 ms, echo time = 4.55 ms, inversion time = 900 ms,
3 min 58 s); vessel-encoded pseudocontinuous ASL-PWI
(3.4 3.4 4.5 mm, field of view = 220mm, repetition
time = 4080 ms, echo time = 14ms, echo planar imaging,
24 slices, 5 min 55 s) with multiple post-labelling delays (six
delays: 0.25 s, 0.5 s, 0.75 s, 1 s, 1.25 s, 1.5 s) (Okell et al.,
2013); and T
2
-weighted FLAIR turbo spin echo
(1.9 1.9 2.0 mm, field of view = 240 mm, repetition
time = 9000 ms, echo time = 96 ms, inversion time = 2500 ms).
pH-weighted images were acquired by estimating amide
proton transfer effect using single-slice chemical exchange sat-
uration transfer echo planar imaging localized to the lesion on
diffusion weighted imaging (3.0 3.0 5.0 mm, field of
view = 240 mm, repetition time = 5000 ms, echo time = 28 ms,
echo planar imaging, 1 slice, 2 min 45 s). The chemical
exchange saturation transfer preparation consisted of a 2 s
train of 50 Gaussian pulses (flip angle = 184, power =
0.55 mT, duration = 20 ms, delay time = 20 ms) over 32
Table 1 Patient characteristics
Patient Stroke
syndrome
Hemisphere Sex Age NIHSS Thrombolysed Onset to scan,
(h:min)
24 h MRI Follow-up
MRI (days)
1 LACS Left F 84 3 N 03:25 Y 1 month (37)
2 TACS Left M 92 25 Y 02:50 Y 1 week (7)
3 PACS Right M 64 3 N 01:41 Y 1 month (37)
4 POCS Left M 80 3 N 11:06 N 1 month (37)
5 TACS Left F 86 27 N 03:09 Y 1 month (25)
6 TACS Left F 81 21 N 03:25 Y 1 week (4)
7 PACS Left M 95 19 Y* 04:14 Y 1 month (47)
8 TACS Left F 53 13 Y 02:48 Y 1 month (34)
9 LACS Right M 57 7 N 01:43 Y 1 month (67)
10 TACS Right F 79 14 Y* 09:50 N 1 month (27)
11 PACS Left F 78 9 Y 02:50 Y NA
12 PACS Left F 55 7 Y 01:35 Y 1 month (31)
NIHSS = National Institute for Health Stroke Scale; LACS = lacunar stroke; TACS = total anterior circulation stroke; PACS = partial anterior circulation stroke; POCS = posterior
circulation stroke; NA = not available.
*Patients 7 and 10 received thrombolysis prior to the MRI scan rather than during it. Patient 7 finished thrombolysis immediately prior to imaging. Patient 10 was imaged 6 h after
thrombolysis.
pH-weighted MRI in acute stroke BRAIN 2015: 138; 36–42 |37
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frequency offsets with an optimized sampling schedule from
4.5 to 4.5 ppm (Tee et al., 2013, 2014).
Postprocessing
All image analysis was performed using FSL (Jenkinson et al.,
2012) and MATLAB (The Mathworks Inc.). Following
brain extraction and automated tissue segmentation of the
T
1
-weighted image to define grey matter, white matter and
CSF, registration within participants used a six degrees-of-free-
dom rigid body linear transformation to the T
1
-weighted
image (Zhang et al., 2001; Jenkinson et al., 2002; Smith,
2002). ASL-PWI was processed using a non-linear fit to the
general arterial spin labelling (ASL) kinetic model for all voxels
within a brain mask to quantify CBF (Chappell et al., 2010;
Okell et al., 2013). Perfusion maps were registered to the
T
1
-weighted image as above. pH-weighted imaging was
retrospectively motion corrected using the MCFLIRT tool,
registered to the first slice acquired (Jenkinson et al., 2002).
pH-weighted signal was quantified using amide proton transfer
ratio (APTR*) (Chappell et al., 2013; Tee et al., 2014) where
low values represent intracellular acidosis. pH-weighted images
were then co-registered with the corresponding T
1
-weighted
image slice, to which it was aligned at the time of acquisition,
using the 2D registration schedule within FSL (Jenkinson et al.,
2012) and checked for accuracy by a clinician.
Amide proton transfer ratio analysis
APTR* is a metric combining the effect of amide-proton
exchange rate, which is directly related to pH, and relative
concentration of amide-bearing molecules. APTR* does not
rely upon data from saturation frequencies on the opposite
site of the water resonance as a reference unlike conventional
APTR, avoiding changes that might occur in ischaemia unre-
lated to pH, such as B
0
inhomogeneity (Chappell et al., 2013).
APTR* has been found to be more homogenous than APTR in
healthy subjects and acute stroke patients producing better
contrast-to-noise ratio between ischaemic and normal tissue
(Tee et al., 2014).
APTR* is derived from model-based analysis of the amide
proton transfer z-spectrum and controls for the effects of B
0
inhomogeneity, T
1
and T
2
. APTR* is calculated using the
fitted model parameters from a three-pool exchange model;
APTR* = [S
w
(3.5 ppm) – S
w+a
(3.5 ppm)] / M
w0
, where S refers
to the simulated signal at 3.5 ppm using the fitted model par-
ameters, subscripts w and w + a refer to water pool and both
water and amide pools, and M
w0
is the fitted unsaturated
signal. The three-pool exchange model used for the data fit-
ting was water, amide and asymmetry magnetization transfer.
The third pool represents a combination of the saturation
effect observed at the negative frequency offsets and the con-
ventional magnetization transfer (Hua et al., 2007; Chappell
et al., 2013).
Regions of interest
Binary masks of presenting and 24-h ADC lesions (ADC
0
and ADC
24
) were automatically generated using a threshold-
defined (620 10
6
mm
2
/s) (Purushotham et al., 2013) clus-
ter-based analysis of the ADC data. Presenting perfusion def-
icits were defined using a threshold of 20 ml/100 g/min to
guide delineation of the region (Bristow et al., 2005). Both
ADC and perfusion region of interest clusters were identified
and smoothed [Gaussian kernel of standard deviation 1 mm
(ADC) and 2 mm (perfusion)], followed by repeat cluster ana-
lysis (http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Cluster). The auto-
mated ADC and perfusion masks were inspected to ensure
their accuracy and manually corrected when necessary. Final
infarct was preferentially defined manually on the 1-month
FLAIR image, or, if not available, on the 1-week image.
Non-linear registration was used to register the 1-week
images to the presenting T
1
-weighted image to minimize any
overestimation of final FLAIR infarct due to any oedema
still present at this time (Jenkinson et al., 2012; Rekik et al.,
2012). A representative contralateral region of interest was
defined manually on the FLAIR image and blind to the pro-
cessed APTR* data.
The following tissue outcome definitions were used in the
analysis: (i) ischaemic core: tissue present in both ADC
0
and
final FLAIR infarct; (ii) infarct growth: tissue present in the
final FLAIR infarct but not in the ADC
0
; (iii) oligaemia: tissue
present in the perfusion deficit but not the final FLAIR infarct;
(iv) diffusion lesion pseudonormalization: tissue present in
the ADC
0
but not ADC
24
; that is present in the final FLAIR
infarct; and (v) radiographic recovery: tissue present in the
ADC
24
but not the final FLAIR infarct (Supplementary Fig. 1).
Data extraction and analysis
Voxel-wise analysis was used to calculate mean presenting
APTR* for each region of interest mask transformed to
native amide proton transfer image space within a tissue
mask. To enable the secondary analysis of comparing present-
ing APTR*, grey matter perfusion and ADC directly, APTR*,
CBF and ADC were co-registered to T
1
-weighted image space.
Data were extracted from the regions of interest within a grey
matter mask. APTR*, CBF and ADC were calculated relative
to the contralateral region of interest enabling composite
voxel-wise analysis across patients. Statistical tests used were
unpaired t-tests for direct comparison between the means in
the regions of interest and using ANOVA for multiple region
of interest comparisons.
Results
Of 18 eligible patients recruited, 12 were included in the
analysis (Table 1). Three patients were excluded because of
motion corruption, two because of artefact in the APTR*
images (ringing and partial volume effects) and one de-
veloped secondary haemorrhage during the initial MRI.
The median symptom onset to MRI was 2 h 59 min
(range 1 h 35 min to 11 h 6 min) and the median National
Institute for Health Stroke Scale at presentation was 11
(minimum: 3, maximum: 27). Six patients received intra-
venous thrombolysis. Images from representative patients
are presented in Fig. 1.
Tissue in ischaemic core, infarct growth and oligaemia
regions of interest all demonstrated a reduced APTR* rela-
tive to the contralateral hemisphere [mean standard de-
viation (number of voxels); ischaemic core: 0.86 0.11
(636); infarct growth: 0.92 0.11 (912); oligaemia:
38 |BRAIN 2015: 138; 36–42 G. W. J. Harston et al.
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Figure 1 Images from representative patients. Regions of interest: green = oligaemia; blue = infarct growth; red = ischaemic core.
NA = not available. Scale for ASL-PWI = cerebral blood flow, ml/100g/min. Scale for pH-weighted imaging = APTR*, no units.
pH-weighted MRI in acute stroke BRAIN 2015: 138; 36–42 |39
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0.97 0.11 (592)] (Fig. 2 and Supplementary Table 1).
Relative APTR* within the ischaemic core was significantly
lower than within the infarct growth voxels (P50.0001,
unpaired t-test), which in turn had lower relative APTR*
than oligaemia regions (P50.0001, unpaired t-test).
Data from individual patients in Fig. 1 can be seen in
Supplementary Fig. 2.
Those voxels within the ADC lesions that demonstrated
diffusion lesion pseudonormalization [0.82 0.12 (47)
had significantly lower relative APTR* than the ischaemic
core (0.86 0.11 (636), P= 0.03, unpaired t-test] (Fig. 2).
In contrast, those regions undergoing radiographic recovery
had an APTR* greater than the contralateral hemisphere
[1.06 0.13 (129)] (Fig. 2). Within the ADC lesions, there
was a gradation of mean ADC by final tissue outcome
(Supplementary Fig. 3).
Within the grey matter, CBF did not distinguish between
regions of ischaemic core, infarct growth or oligaemia
(P= 0.31, ANOVA) although there was more variation in
CBF within the ischaemic core than infarct growth regions
(variance ratio = 2.5, P50.01) (Fig. 3 and Supplementary
Fig. 4). In contrast, there was a significant difference in rela-
tive APTR* between regions of infarct growth and oli-
gaemia within the grey matter (P50.0001, unpaired
t-test), and although the relative APTR* within the ischae-
mic core was lower than the regions of infarct growth, this
was not significant (P= 0.52). With the perfusion deficit,
the relative ADC value was reduced only in the ischaemic
core (Supplementary Fig. 4).
Figure 2 Mean relative APTR* of region of interest voxels
within the perfusion deficit (top) and within the ADC lesion
(bottom). Analysis in pH-weighted image space within a tissue
mask; error bars represent 95% confidence intervals.
****P50.0001; *P50.05.
Figure 3 Mean relative CBF (top) and relative APTR*
(bottom) for region of interest voxels within the perfusion
deficit, restricted to grey matter voxels only. Analysis in T
1
-
weighted image space within a grey matter mask; error bars rep-
resent 95% confidence intervals. ****P50.0001.
40 |BRAIN 2015: 138; 36–42 G. W. J. Harston et al.
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Discussion
Using detailed group-level voxel-wise analysis we demon-
strate the potential clinical use of pH-weighted MRI in
acute ischaemic stroke. This study builds on previous
work to optimize the generation of a pH-weighted signal
to show that intracellular pH at presentation is significantly
associated with final tissue outcome, providing complemen-
tary information to existing ASL-PWI and diffusion
weighted imaging sequences in the clinical setting of acute
stroke (Sun et al., 2010; Zhao et al., 2011; Tee et al., 2014;
Tietze et al., 2014). It entails the use of a sequence acqui-
sition that is clinically pragmatic (it is 3 min in duration),
and does not require contrast (e.g. gadolinium) or exogen-
ous stimulus (e.g. inhaled gas such as carbogen) to derive a
signal that is present in both grey and white matter
(Tee et al., 2014).
This study shows a biologically plausible signal of intra-
cellular acidosis associated with final tissue outcome.
Intracellular acidosis develops in part as a consequence of
unopposed anaerobic ATP hydrolysis, with hypoperfusion
and reduced bicarbonate buffering at acidic pH exacerbat-
ing the acidosis (Sun et al., 2011). Within a perfusion-
defined lesion, the ischaemic core is more acidotic than
tissue that is subsequently recruited to the final infarct.
Tissue within the region of interest of oligaemia that ultim-
ately does not infarct is significantly less acidotic than
either ischaemic core or infarct growth.
The inherently low signal-to-noise ratio when using ASL
to measure CBF in white matter (van Gelderen et al., 2008;
Alsop et al., 2014), alongside the sensitivity of ASL to
delays in arterial arrival time, provide challenges in the
accurate determination of the perfusion deficit and may
affect reliable determination of CBF. This was overcome,
in part, by the use of multiple post-labelling delays (Okell
et al., 2013). Furthermore, when comparing pH-weighted
imaging to ASL-PWI within the regions of interest repre-
senting different tissue outcomes, analysis was confined to
grey matter to minimize any insensitivity introduced by
ASL-PWI. Within threshold-defined ischaemic grey matter,
pH-weighted imaging, but not ASL-PWI, differed between
tissues with different outcomes. Outside of the ischaemic
core, relative ADC values were not helpful in discriminat-
ing final tissue outcome. This supports the hypothesis that
pH-weighted imaging separates the diffusion-perfusion mis-
match into zones of acidotic ischaemic penumbra (low CBF
with evidence of metabolic stress) and benign oligaemia
(low CBF with minimal evidence of metabolic stress) in a
way consistent with the preclinical data (Sun et al., 2007;
Zhou and van Zijl, 2011).
pH-weighted MRI provides an insight into ADC lesion
reversal, which has variously been reported at 6.7% to
50% of the presenting ADC lesion (Inoue et al., 2014).
This study corroborates the PET imaging finding that
there is heterogeneity of metabolism within the ADC
lesion and that this seems to be linked to ADC reversal
(Guadagno et al., 2006). Tissue within regions of diffusion
lesion pseudonormalization is more severely acidotic at
presentation than the ischaemic core, consistent with
more aggressive tissue injury with vasogenic oedema and
early pseudonormalization of ADC by 24 h (Inoue et al.,
2014). In contrast, tissue with radiographic recovery has an
intracellular alkalosis. This is again a biologically plausible
signature of tissue maintaining ATP levels, and hence via-
bility, through the transfer of phosphate from phosphocrea-
tine to ADP (adenosine diphosphate) with resultant
intracellular alkalosis (Erecinska and Silver, 1989).
Further technical development, such as 3D image acqui-
sition to overcome challenges pertaining to single-slice data
(including registration errors), rapid image analysis and
improving signal-to-noise ratio, is required before pH-
weighted imaging becomes a widely clinically relevant
imaging modality influencing treatment decisions for indi-
viduals. In keeping with other acute stroke MRI modalities,
further work is required to limit issues related to motion
corruption and partial volume effects. Addressing these
will enable larger studies to assess the interaction of the
pH-weighted signal with physiological (e.g. glucose, tem-
perature), treatment, and imaging (e.g. perfusion dynamics)
parameters.
In conclusion, pH-weighted imaging may have a role in
improving the imaging definition of ischaemic penumbra,
and may also be useful in a better understanding of re-
gional vulnerability and secondary injury, addressing an
unmet need of MRI biomarkers in acute stroke (Kidwell,
2013). In addition, given pH is a physiological parameter
that can be manipulated, pH-weighted imaging has the
potential to meet the criteria of a treatment-relevant
acute imaging target (Wintermark et al., 2013). This
proof of principle study at a tissue level of analysis
strongly supports the further investigation of pH-weighted
imaging in patients with acute ischaemic stroke when
used in combination with diffusion and perfusion weighted
imaging.
Acknowledgements
We wish to acknowledge the facilities provided by the
Oxford Acute Vascular Imaging Centre and the staff of
the Oxford Acute Stroke Programme.
Funding
This study was supported by the National Institute for
Health Research Oxford Biomedical Research Centre
Programme, the National Institute for Health Research
Clinical Research Network, the Dunhill Medical Trust
[grant number: OSRP1/1006] and the Centre of
Excellence for Personalized Healthcare funded by the
Wellcome Trust and Engineering and Physical Sciences
Research Council [grant number WT088877/Z/09/Z].
pH-weighted MRI in acute stroke BRAIN 2015: 138; 36–42 |41
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Supplementary material
Supplementary material is available at Brain online.
Conflict of interest
Professor Chappell, Professor Jezzard and Dr Okell have
received royalties from Siemens Healthcare through licen-
sing of US patents. Professor Chappell has received royal-
ties for commercial licenses from the FMRIB software
library.
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