In Vivo Measurement of Oxygenation Changes after Stroke Using Susceptibility Weighted Imaging Filtered Phase Data
et al. (2013) In Vivo Measurement of Oxygenation Changes after Stroke Using Susceptibility Weighted Imaging Filtered
Phase Data. PLoS ONE 8(5): e63013. doi:10.1371/journal.pone.0063013
In Vivo Measurement of Oxygenation Changes after Stroke Using Susceptibility Weighted Imaging Filtered Phase Data
Meng Li 0
Jiani Hu 0
Yanwei Miao 0
Huicong Shen 0
Dingbo Tao 0
Zhihong Yang 0
Qinghang Li 0
Stephanie Y. Xuan 0
Waqar Raza 0
Sadeer Alzubaidi 0
E. Mark Haacke 0
Essa Yacoub, University of Minnesota, United States of America
0 1 Department of Radiology, Wayne State University , Detroit, Michigan , United States of America, 2 Department of Radiology, The First Affiliated Hospital, Dalian Medical University , Dalian, Liaoning , China , 3 Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing Neurosurgical Institute , Beijing , China , 4 Department of Neurology, The First Affiliated Hospital, Dalian Medical University , Dalian, Liaoning , China , 5 Department of Radiology, Third Hospital of Xingtai , Xingtai, Hebei , China , 6 Department of Neurological Surgery, Wayne State University , Detroit, Michigan , United States of America, 7 University of Toronto, Faculty of Arts & Science , Toronto, Ontario , Canada
Background and Purpose: Cerebral blood oxygenation level is critical for following the evolution of stroke patients. The purpose of this study was to investigate the feasibility of measuring changes in blood oxygen levels for patients with acute stroke using SWI and to compare these changes with the patient's recovery over time. Materials and Methods: A total 30 MRI scans was performed on 10 acute ischemic stroke patients. Every patient was followed at three time points: less than 24 hours; 2-3 weeks after stroke and 2 months after stroke. Both MRI scan and NIH stroke scale (NIHSS) were acquired for each patient at all three time points. Oxygen saturation changes were derived from phase values differences (DQ) measured over 10 veins from each hemisphere for all 10 patients over 3 time points. The correlation of oxygen saturation and NIHSS was further evaluated. Results: The stroke affected side of the brain showed moderate (r = 20.62) to strong (r = 20.70) correlation between the oxygenation change and NIHSS change. The oxygen saturation change from the normal side of the brain had essentially no association with recovery (r = 20.02 and20.31). The results suggest that increases in oxygen saturation correspond to improved outcome and reductions in oxygen saturation correspond to worse outcome. Conclusion: High resolution SWI provided a novel method to measure changes in oxygenation change of the human brain in vivo. By using the phase values from the veins, both spatial and temporal information can be found that relates to patient outcome post stroke.
Hemoglobin exists in the human body in two distinct states,
oxyhemoglobin and deoxyhemoglobin, which have different
magnetic susceptibilities. Oxyhemoglobin is the state where
oxygen is bound to the hemoglobin molecule and exhibits only a
very small diamagnetic susceptibility relative to surrounding brain
tissue. Deoxyhemoglobin is the state where oxygen is not bound to
the hemoglobin and exhibits paramagnetic properties relative to
surrounding brain tissue. Consequently, changes in oxygen
saturation levels will lead to a phase difference between veins
and the surrounding tissue . By comparing changes in venous
phase over multiple time points, it is possible to estimate the
changes in oxygen saturation. Ischemic stroke is caused by the
blocking of blood vessels, reduced oxygen delivery and increased
levels of deoxyhemoglobin. If the delivery of blood is interrupted
for too long, then the affected brain tissue will cease to function
and ultimately die. Therefore, monitoring levels of oxygen
saturation is key to determining tissue viability post stroke.
Susceptibility Weighted Imaging (SWI) is a high resolution 3D
phase enhanced gradient echo method with full flow compensation
in all three directions . In SWI, susceptibility differences of
neighboring tissues are exploited to increase the contrast of MR
images, and can therefore aid in identifying tissue properties and
states in both magnitude and phase images. SWI is sensitive to the
presence of venous blood, hemorrhage and iron storage. By
measuring the phase difference between local small veins and
surrounding tissue, the venous oxygenation information can be
obtained. In particular, SWI filtered phase can be used to measure
changes in blood oxygen content. In acute stroke, SWI makes it
possible to detect the microbleeding  in the infarction and
intravascular clot in the thrombosed vessel . Moreover, SWI
can be used to evaluate the oxygen extraction fraction (OEF) and
the cerebral metabolic rate of oxygen in the acute stroke due to an
increased ratio of deoxyhemoglobin to oxyhemoglobin in the
affected region. OEF is considered a critical marker of tissue
viability and can be used to directly assess oxygen metabolism in
ischemic tissue . The purpose of this study is to investigate the
feasibility of measuring blood oxygen levels for patients with stroke
using phase information to observe the correlation of changes in
oxygen saturation over time with patient recovery.
Materials and Methods
Changes in the local magnetic field, DB, determine spatial
variation in the phase both inside and outside the structure. These
field changes give rise to a twofold effect: (i) dephasing of the signal
outside the structure and in the pixel containing the structure
leading to a reduction of T2* and (ii) the presence of measurable
phase . The SWI magnitude images are used to enhance the
sensitivity to both T2* and phase changes to reveal abnormal
looking veins. However, assigning an oxygen saturation to these
images is difficult. On the other hand, the SWI filtered phase
images can be used as a direct measure of the susceptibility from
the vessels and are a representation of local oxygen saturation [9
11]. To appreciate this, consider first the phase behavior as a
function of position r as given by:
where c is the gyro-magnetic ratio of the proton (2.6786108 rad/
s/T), DB is the change in magnetic field between tissues, B0 is the
static magnetic field, TE is the echo time and Dx is the local
magnetic susceptibility change between tissues.
Assuming the blood vessel is an infinite cylinder model , the
phase difference DQ between the blood in the vessel and the
surrounding tissue can be expressed as:
where h represents the angle between the blood vessel and the
static magnetic field B0. The susceptibility difference Dx is
where Dxdo  is the change in blood susceptibility per unit
hematocrit between fully deoxygenated and fully oxygenated
blood, and has been measured to be 1.861027. The average
oxygen saturation level Y is 0.55 . Hct is the percent of red
blood cells in a given volume of whole blood. The relationship
between the oxygenation change DY over the time and oxygen
saturation is expressed as:
blood vessel orientation due to cancellation of the geometry
dependent term (3cos2h21).
A total of 10 acute ischemic stroke patients aged from 20 to 74
years were recruited in this study. There were 6 males and 4
females, the mean and standard deviation of the age were 56.4
years and 18.0 years, respectively. All patients were not treated
with thrombolysis during this study. The NIH stroke scale
(NIHSS) was assessed by an experienced neurologist. Both MRI
scans and NIHSS measures were acquired for each patient at
three time points: 1) within the first 24 hours; 2) 23 weeks after
stroke; and 3) 2 months after stroke. Informed consent was
obtained from all subjects, and all protocols were approved by the
local institutional review board.
All MR imaging was acquired on a 1.5T magnet (GE Signa
HD1.5T) with an eight-channel head coil. The SWI sequence used
was a fully velocity-compensated, three-dimensional,
gradientecho sequence, with the following parameters: TE/TR = 40/
50 ms, FA = 20u, pixel bandwidth is 122 Hz/pixel, slice
thickness = 2 mm, field-of-view (FOV) = 2566256, and an acquisition
matrix = 5126512. After all sequences were acquired, the SWI
source data were post-processed using SPIN (signal processing in
NMR) software (Detroit, Michigan). High pass filtering was
applied using a central matrix size of 64664 .
Other MRI sequences used included: FLAIR, T2-weighted
imaging (T2WI), T1-weighted imaging (T1WI) and diffusion
weighted imaging (DWI). The combination of DWI, FLAIR and
SWI was used to define the location and extent of the stroke lesion.
Data were collected with the parameters for FLAIR: TR/
TE = 8602/123 ms, FA = 90u, FOV = 288 mm6192 mm, BW =
122 Hz/pixel and TH = 6 mm with a 1 mm gap; for T2WI: TR/
TE = 3000/104 ms, FA = 90u, FOV = 288 mm6192 mm, BW =
122 Hz/pixel and TH = 6 mm with a 7.5 mm gap; for T1WI:
TR/TE = 400/15 ms, FA = 90u, FOV = 288 mm6192 mm, BW
= 61.05 Hz/pixel and TH = 6 mm with a 1 mm gap; and for
DWI: TR/TE = 6000/82 ms, FA = 90o, FOV = 128 mm6128 mm,
BW = 1953 Hz/pixel, TH = 6 mm with a 1 mm gap and b = 0,
where 1 and 2 refer to the two MRI scans at different time points.
The measured phase difference DQ1 and DQ2 are from the same
vessel from the images acquired at these two time points. How to
measure DQ is illustrated in Figure 1. The changes of oxygenation
DY2,1 can be obtained from Equation (4). DY2,1 is independent of
To keep the consistency of the patients head position in the
three time points, the patients head was adjusted to make the line
connected with anterior commissure and posterior commissure
(AC-PC line) perpendicular to the static magnetic field (B0) based
on the localizer image on the sagittal view. Further, we kept the
same slice thickness and interval at every scan for each patient,
and the same slice location based on the AC-PC line.
Vessel phase measurements
The criteria of the vessel selection were: 1) each vessel showed
clearly in all three MRI scans; 2) no vessel close to the skull or
sinuses was chosen (to avoid air/tissue interface artifacts); 3) 20
vessels were chosen for each patient, with 10 on the ipsilateral side
and 10 on the contralateral side. Figure 2 shows the vessel
selection for one patient. Therefore, a total of 600 veins was
valuated from all 10 patients to obtain oxygen saturation level
The procedures used to obtain DQ1, DQ2 and DQ3 are illustrated
in figure 3. For a particular vessel, each phase profile is obtained
along a line cutting across the vessel as indicated in Figures 3ac.
The phase difference is found by averaging the peak values for
both sides of the vessel wall and subtracting the minimum phase of
the vessel (Figure 1). The profile corresponding to the first time
SWI scan (,24 hours) is designated DQ1 and the remaining two
time point profiles are designated by DQ2 and DQ3. These values
are then used in equation (4) to derive the oxygenation change DY.
The comprehensive oxygenation changes of each side of the brain
are then obtained by averaging over the ten measured vessels. We
calculated oxygenation changes for two time intervals: 1) using
DQ1 as the baseline phase data, and with DQ2 to get oxygenation
change DY2,1 from the first and second MRI scans; and 2) using
DQ2 as the baseline phase data along with DQ3 to get the
oxygenation change DY3,2 from the second MRI scan to the third
Correlating oxygen saturation changes with NIHSS
To evaluate NIHSS change, the later NIHSSs were subtracted
from the previous ones to obtain DNIHSS2,1 and DNIHSS3,2. A
positive change indicates a worsening of their condition and a
negative change indicates an improvement in their condition.
The gender, age, and three NIHSS scores are given in Table 1.
We found that 8 patients had various degrees of recovery with the
NIHSS values changing from22 to28 at the second time point.
There were two patients who got worse with the scores increasing
by 2 and 3. However, the third score showed that after two months
all patients showed some improvement ranging from22 to210
compared to their first ones.
The results of Figure 4 show that the oxygenation change is
negatively correlated with the NIHSS change. The correlation
between the average oxygenation change and the NIHSS change
for the second and the first imaging time points is shown in
Figure 4a and 4c. The coefficients of determination R2 were
0.3866 for the affected side of the brain (4a), and 0.0004 for the
normal side of brain (4c). The correlation coefficients from the ten
patients were20.62 (4a) and20.02 (4c) for the stroke hemisphere
and the non-stroke hemisphere respectively. Figures 4b and 4d are
the scatterplots for the oxygenation change and NIHSS change for
the third and the second imaging time points. The coefficients of
determination R2 were 0.4858 and 0.0955 for the affected side of
the brain (4b) and the normal side of brain (4d) respectively. The
correlation coefficients from the ten patients were20.70 (4b) for
the stroke hemisphere and20.31 (4d) for the non-stroke
hemisphere. The results indicate that the affected side of the
brain showed moderate to strong correlation between the
oxygenation change and NIHSS change. However, the normal
side of the brain showed weak or no association between these two
Analysis of variance (ANOVA) based on linear regression was
applied to test the significance of the overall regression. The
confidence level was set as 95%. The results are shown in Table 2.
For the regression model of the data acquired from the second and
the first scan, the p-values were 0.05 and 0.95 for the affected side
of brain and normal side of brain respectively. ANOVA analysis
for the data acquired from the third and the second scan, the
pvalues were 0.02 and 0.38 for the stroke hemisphere and the
nonstroke hemisphere respectively. The correlation between
oxygenation changes and NIHSS changes has significance for the period
from the second to the third scan.
Oxygenation level is a vital parameter to monitor in intensive
care units for stoke patients and a number of other diseases such as
traumatic brain injury. Positron emission tomography (PET) is
available for clinical measurement of oxygenation; however, given
its invasive nature and low spatial resolution, it is still not routinely
utilized in critical care. SWI is a non-invasive, rapid MRI
technique that can provide high spatial resolution for imaging
oxygen saturation changes. Preliminary results from this study
demonstrate that SWI can provide an in vivo estimate of blood
oxygen saturation levels for patients with stroke and that decreases
in phase (increases in oxygen saturation) correlate with patient
outcome. Compared to traditional perfusion methods such as
dynamic-susceptibility contrast-enhanced MR imaging, SWI
provides higher resolution images and estimates of oxygenation
changes without the injection of a contrast agent and can be used
Figure 3. Phase profiles over the SWI filtered phase images corresponding to the three MRI scans (a),24 hours, (b) 23 weeks after
stroke, and (c) 2 months after the onset of stroke.
List of the ten patients age and their assessments of NIHSS at the three MRI scans: 1st is,24 hours, 2nd is 23 weeks after stroke, and 3rd is 2 months after the onset of
to assess indirectly perfusion deficits and the penumbra in acute
Ischemic stroke occurs as the result of obstruction within a
blood vessel that supplies blood to the brain, causing a deficiency
in blood flow (ischemia). During an ischemic stroke, the brain
initiates a series of events that may result in delayed damage to
brain cells . In this study, there were major changes seen in the
oxygenation changes on the ipsilateral (stroke) side but there were
few effects seen on the contralateral (normal) side. We postulate
that an increase in the brain oxygenation level in the stroke region
could result in an increase of the regional oxygen extraction
fraction (OEF)  and improved brain tissue viability. Our study
demonstrated that after acute ischemic stroke, the clinical
outcomes depended on the oxygen saturation level in the stroke
The oxygenation for each hemisphere is from the average over
the measurements from 10 vessels. The vessels were chosen as
close as possible to the stroke region in the affected hemisphere.
Different veins drain blood into different regions of the brain,
while only specific regions are affected by the stroke. So even
within the same hemisphere, vessel-wise comparisons
demonstrated that temporal changes of oxygenation were vessel and regional
SWI filtered phase imaging not only provides a non-invasive
and safe measurement of oxygen saturation changes but also
provides the most sensitive means to detect hemorrhage after
stroke . In Figure 2c and 2d, SWI shows that there is a
hemorrhage (within the yellow circle) in the left putamen (visible in
the second and third MRI scans). We also observed that the veins
around the stroke lesion in Figure 2c and 2d are darker than the
contralateral normal side and also darker than those in the first
time point (2b). This is because uncoupling between oxygen supply
and demand within or around the stroke region causes a relative
increase of deoxyhemoglobin levels.
A limitation of this approach is that we have to adjust the brain
in the same location for all scans so that the vessels are in the same
orientation for the different scans. Thus we can cancel the
geometry dependent term (3cos2h21). If the position of the head is
different by65u relative to the main field, this will induce only a
2% error in the result. Another limitation is in the partial volume
effect where the vessel may shift from being at the edge of a voxel
to the center of a voxel and that can modify the phase in the vessel.
In the former case the phase will be lower than that in the latter
case. This effect however should be random and should average
out over all the ten veins measured in the brain for any given time
point. Finally, new methods such as susceptibility mapping may
also provide a similar means to measure oxygen saturation in the
future , but these methods are still under development and
have their own artifacts and limitations.
We have found that SWI provides a non-invasive method of
measuring T2* changes in the brain and offers an alternative
means of measuring changes in oxygenation levels in the brain.
This capability complements the information available in the more
standard imaging techniques of diffusion and perfusion. The
results obtained by this study indicate that the oxygen saturation
change may predict clinical outcomes for the stroke patient.
ANOVA test results of four regression models which show in Figure 4 for both hemispheres. The stroke hemisphere show the significant correlation between the
oxygenation change vs. the NIHSS change for the time period of the third and the second MRI scan.
Conceived and designed the experiments: ML YM EMH JH. Performed
the experiments: DT ZY QL. Analyzed the data: ML JH SYX WR SA
EMH. Wrote the paper: ML YM HS JH EMH.
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