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ORIGINAL ARTICLE
Comparative Evaluation of 3-Dimensional
Pseudocontinuous Arterial Spin Labeling With Dynamic
Contrast-Enhanced Perfusion Magnetic Resonance
Imaging in Grading of Human Glioma
Bhaswati Roy, PhD,* Rishi Awasthi, PhD,Þ Amit Bindal, MCh,þ Prativa Sahoo, MSc,§ Rajan Kumar, MS,||
Sanjay Behari, MCh,|| Bal K. Ojha, MCh,þ Nuzhat Husain, MD,¶ Chandra M. Pandey, PhD,#
Ram K.S. Rathore, PhD,§ and Rakesh Kumar Gupta, MD*
Introduction: The study was performed to compare dynamic contrastenhanced (DCE) magnetic resonance imaging (MRI) with 3-dimensional
(3D) pseudocontinuous arterial spin labeling (PCASL) MRI in gliomas
with an aim to see whether arterial spin labeling (ASL)Yderived cerebral
blood flow (CBF) values can be used as an alternative to DCE-MRI for
its grading.
Materials and Methods: Sixty-four patients with glioma (37 male;
mean age, 43 years; 38 high grade and 26 low grade) underwent
3D-PCASL and DCE-MRI. The DCE indices (relative cerebral blood
volume, rCBV; relative CBF, rCBF; permeability, ktrans and kep; and
leakage, ve) and ASL (absolute and rCBF) values were quantified from
the tumors. Student independent t test was used to compare ASL
and DCE-MRI indices. Pearson correlation was used to see correlation
between DCE- and ASL-derived CBF values in tumor and normal
parenchyma.
Results: On Student t test, neither ASL-derived absolute CBF
(P = 0.78) nor rCBF (P = 0.12) values were found to be significantly
different in 2 groups, whereas DCE indices except ve were significantly higher in high-grade gliomas. Arterial spin labelingYderived
rCBF values weakly correlated with DCE-derived rCBF values, whereas
these did not show correlation in normal grey (P = 0.12, r = 0.2) and
white (P = 0.26, r = 0.14) matter regions.
Conclusions: Three-dimensional pseudocontinuous arterial spin labeling does not appear to be a reliable technique in the current form and
may not be a suitable replacement for DCE in grading of glioma.
Key Words: dynamic contrast enhanced MRI, arterial spin labeling, glioma
(J Comput Assist Tomogr 2013;37: 321Y326)
G
liomas are the most common primary tumors of the central
nervous system in adults.1 The histopathologic grading plays
a significant role in treatment planning and prognostication of
From the *Departments of Radiology & Imaging, Fortis Memorial Research
Institute, Gurgaon; †Department of Radiodiagnosis, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow; ‡Department of Neurosurgery,
Chhatrapati Sahuji Maharaj Medical University, Lucknow; §Department of
Mathematics and Statistics, Indian Institute of Technology, Kanpur; ||Department of Neurosurgery, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow; ¶Department of Pathology, Ram Manohar Lohia, Institute of
Medical Sciences, Lucknow; and #Department of Biostatistics, Sanjay Gandhi
Postgraduate Institute of Medical Sciences, Lucknow, India.
Received for publication November 1, 2012; accepted December 12, 2012.
Reprints: Rakesh Kumar Gupta, MD, Department of Radiology & Imaging,
Fortis Memorial Research Institute, Gurgaon, Haryana, India 122002
(e-mail: [email protected]).
Bhaswati Roy acknowledges the financial support from University Grant
Commission, New Delhi, India; Rishi Awasthi acknowledges the
financial support from Indian Council of Medical Research,
New Delhi, India.
The authors have no funding or conflicts of interest to disclose.
Copyright * 2013 by Lippincott Williams & Wilkins
J Comput Assist Tomogr
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the disease process. The current gold standard for glioma
grading is the histopathologic assessment of the excised tumor
tissue. However, histopathologic assessment of tumor tissue
often suffers from inherent sampling error.
Magnetic resonance imaging (MRI) plays a central role in
the evaluation of patients with gliomas.2 However, despite optimization of sequences and protocols, the classification and
grading of gliomas with conventional MRI is still not reliable.
Traditionally, mass effect, cyst formation, necrosis, and the extent of contrast enhancement on conventional MRI studies
correlate significantly with grade of glioma.2Y5 Most high-grade
gliomas on postcontrast T1-weighted images generally show
moderate to strong enhancement, whereas low-grade gliomas
have minimal or no contrast enhancement.5,6 However, lack of
contrast enhancement on MRI studies does not always equate
with the tumor grade. A broad spectrum of histologic types may
present as poor/nonenhancing lesions,6Y8 whereas some lowgrade tumors may show pronounced enhancement.9,10 Based
on these attributes, previous studies have reported the sensitivity of conventional MRI in glioma grading ranging from 55.1%
to 83.3%.11Y15
Perfusion-weighted MRI techniques have been used for the
assessment of tumor neoangiogenesis in vivo. Dynamic contrastenhanced (DCE) perfusion MRI is widely used in quantitative
assessment of tumor microenvironment through its hemodynamic and pharmacokinetic indices. Dynamic contrast-enhancedY
derived hemodynamic perfusion indices [relative cerebral blood
volume (rCBV) and relative cerebral blood flow (rCBF)] have
been shown to correlate with tumoral microvascular density as
well as expression of vascular endothelial growth factor.16Y18
Its pharmacokinetic indices [volume transfer coefficient (ktrans),
rate transfer constant between the extracellular extravascular
space and the plasma (kep), leakage (ve), and plasma volume (vp)]
have been shown to be the measure of blood brain barrier
(BBB) integrity.17Y20 These quantitative measures are shown to
be more informative than the conventional Gd-based T1Ycontrast
enhanced MRI.16Y20
With availability of high-field imaging, there has been a
resurgence of arterial spin labeling (ASL) imaging that may be
used as a noncontrast brain perfusion method for the absolute quantification of cerebral blood flow (CBF). Various studies
using continuous (CASL), pulsed (PASL), or 3-dimensional
(3D) pseudocontinuous ASL (PCASL) methods for the absolute
quantification of CBF values have been performed to look for
the discriminatory power of these techniques in differentiation
of high-from low-grade brain tumors.21Y23
There are few studies available in the literature comparing ASL and DCE-MRI mainly in tumors involving the body,
and no study is available in brain tumors.24,25 However, it
needs to be compared with established methods of noninvasive
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Roy et al
assessment of cerebral perfusion. The purpose of this study was
to prospectively compare DCE-MRI with 3D-PCASL MRI in
glioma grading with an aim to see whether ASL-derived CBF
values are as good as DCE-MRI in glioma grading.
MATERIALS AND METHODS
Subjects
Sixty-four (37 male and 27 female; mean age, 43 years)
untreated consecutive patients (38 high grade and 26 low grade)
with definitive diagnosis of glioma were included in this study.
All these patients had come for the preoperative evaluation of
the lesion and were not on corticosteroid therapy at the time
of study. The institutional ethics committee approved the study
protocol, and informed consent was obtained from all the patients
who participated in the study.
Data Acquisition
All patients underwent conventional, DCE, and PCASL MRI
on a 3.0-T scanner (Signa HDxt; General Electric, Milwaukee,
Wis) using an 8-channel head coil. Conventional MRI included
T2-weighted fast spin echo (FSE) images with repetition time
(TR)/echo time (TE)/number of excitations (NEX) equal to
4900 ms/85 ms/2; T1-weighted spin echo with TR/TE/NEX
equal to 625 ms/14 ms/2; T2-weighted fluid-attenuated inversion recovery with TR/TE/inversion time/NEX equal to
9000 ms/120 ms/ 2200 ms/1.
Dynamic contrast-enhanced MRI was performed using a
3D spoiled gradient recalled echo (3D-SPGR) sequence [TR/
TE/flip angle/NEX/slice thickness/field of view (FOV)/matrix
size = 5.0 ms/2.1 ms/10 degrees/0.7/6 mm/240 240 mm/128 128 mm]. At the fourth acquisition, Gd-DTPA-BMA (Omniscan,
GE Healthcare Oslo, Norway) was administered intravenously
through a power injector at 5 mL/s, followed by 30 mL saline
flush. A series of 384 images in 32 time points for 12 slices were
acquired with temporal resolution of 5.65 seconds. Before 3DSPGR, T1-weighted FSE (TR/TE/NEX/slice-thickness/FOV/
matrix size = 375 ms/9.4 ms/1/6 mm/360 270 mm/256 256 mm), fast double spin echo proton density (PD)Yweighted
and T2-weighted (TR/TE1/TE2/NEX/slice-thickness/FOV/matrix
size = 3500 ms/25 ms/85 ms/1/6/360 270 mm/256 256 mm)
imaging were performed for the same slice position to quantify
voxelwise precontrast tissue longitudinal relaxation time (T10).26
The 3D-PCASL was performed before DCE-MRI with
frequency/phase/NEX/number of slice/FOV/slice thickness/bandwidth/postlabel delay/duration of tagging time/TR/TE/matrix =
512/8/3/46/240 mm/3 mm/62.50/1525 ms/1450 ms/4649 ms/
10.44 ms/128128 with spiral acquisition along with 3D
PD-weighted FSE. The parameter taken were the best considering scan time as a constraint. The equation of the model
used for quantification of perfusion is as follows:
ST ðsÞ
PLDðsÞ
1 exp exp
PW
T 1t ðsÞ
T ðsÞ
1b
;
CBF¼6000*L
LT ðsÞ
2T 1b ðsÞ 1 exp j
?*NEX PW SF PW PD
T 1b ðsÞ
where T1b represents T1 of blood, and for 3T, T1b is assumed as 1.6 seconds, ST is saturation time and set as 2 seconds,
postlabel delay represents postlabeling delay, LT is the labeling
duration, NEXPW is the number of excitation for perfusionweighted images, and SFPW represents the scaling factor of
perfusion-weighted sequence. The partition coefficient L for
whole brain is considered as 0.9, and the efficiency D is a combination of both inversion (0.8) and background suppression
efficiency (0.75), which results in overall efficiency of 0.6.
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The partial saturation of the reference image (PD) is corrected
by using a T1t of 1.2 seconds (typical of gray matter). The CBF
maps were generated in the scanner itself with suppression of
background.
Magnetic Resonance Imaging Data Processing
and Quantitative Analysis
Voxelwise tissue T10 was calculated from T1-, T2-, and
PD-weighted images obtained using FSE sequences, as described previously.26 The absolute tissue T10 value was used to
generate concentration time curve from signal intensityYtime
curve obtained from 3D-SPGR sequence.26 Quantitative analysis of concentration time curve was performed for calculation
of cerebral blood volume (CBV) and CBF. Pharmacokinetic
model was implemented for ktrans, kep, and ve calculations.
Corrected CBV map was generated by removing the leakage
effect of the disrupted BBB.16 Arterial spin labelingYderived
CBF maps were registered on DCE-derived CBF maps using
the mutual-informationYbased registration technique,27 and
then regions of interest (ROIs) were drawn on areas of maximum values for quantification of each perfusion indices. The
size of ROIs varied from 25 to 35 voxels depending on the size
of the lesion. The rCBV and rCBF values were quantified by
placing ROI on normal contralateral portion of the brain for
both ASL and DCE-MRI. In addition, 3D-PCASL was also performed on 20 healthy age-/sex-matched control subjects to look
for the normal CBF values in grey and white matter regions.
Statistical Analysis
The objective of this study was to compare the diagnostic
accuracy of ASL and DCE-MRI in detecting high- and lowgrade glioma. It has been reported that neoplastic transformation accompanies with increased vascularity, which is evident as
increase in perfusion indices. It is proposed that ASL- and
DCE-derived indices can differentiate between low- and highgrade glioma. Student independent t test was used for comparing these differences. Based on previous ASL-based study,21
the mean (SD) level of rCBF values in low-grade glioma was
assumed to be 4 (1.5) against 5 (1.5) for high-grade glioma with
95% power and P = 0.05, the minimum sample size estimated
was 60 cases.
Dynamic contrast-enhanced MRI indices as well as ASLderived rCBF and absolute CBF values were compared using
Student t test for low- and high-grade tumors classified by
histopathology, and the data were presented as box plot using
Tukey hinges. To look for the correlation between DCE- and
ASL-derived CBF values in tumor (high and low grade) as well
as normal grey and white matter regions, Pearson correlation
analysis was used. P e0.05 was considered as significant. All
the statistical analysis was performed using statistical package
for social sciences (SPSS, version 16.0, Chicago, Ill).
RESULTS
Of a total 64 excised tumor tissues, 38 were found to be
high grade (29 glioblastoma and 9 grade III astrocytoma), and
26 were low-grade gliomas (23 grade II and 3 grade I).
All tumors were located in the supratentorial region. Highgrade gliomas appeared more heterogeneous on conventional
MRI than low-grade gliomas; however, the contrast enhancement was variable in all the lesions (Figs. 1 and 2). The time
duration between MRI and surgery varied from 2 to 7 days. In
42 of these patients (28 high grade and 14 low grade), a neartotal resection of all the visible intraoperative tumoral tissue
was performed. In 14 patients, the tumor extension to the contralateral lobe, ventricles, and deep grey matter nuclei resulted
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Evaluation of 3D-PCASL With DCE Perfusion MRI
FIGURE 1. A 35-year-old man with glioblastoma multiforme in left frontal region. Axial T2-weighted image (A) shows a mass with
heterogeneous signal intensity and surrounding edema. On T1-weighted image (B), lesion appears hypointense with areas of small
hyperintense foci suggesting hemorrhage. On postcontrast T1-weighted image (C), the lesion shows heterogeneous enhancement with
2 foci of dense enhancement. Arterial spin labelingYderived color-coded CBF map (D) shows increase in blood flow in a single focus
of the tumor (arrow). Dynamic contrast-enhancedYderived color-coded CBF (E) and CBVcorr map (F) show markedly increased values
in 2 foci (arrows). Note the marked disruption of BBB seen on kep (G) ktrans (H) maps (CBVcorr, corrected CBV; kep, rate transfer constant
between the extracellular extravascular space and the plasma, ktrans, volume transfer coefficient).
FIGURE 2. A 23-year-old woman with grade II astrocytoma in left frontotemporal region. Axial T2–weighted (A) and T1-weighted (B)
images show tumor with variable signal intensity. On postcontrast T1-weighted (C) image, a minimal contrast enhancement is seen.
The ASL-derived color-coded CBF map (D) shows hyperperfusion in tumoral region (arrow), whereas on DCE-MRIYderived CBF (E)
and CBVcorr (F), maps do not show any significant increase in its values. There was no break in BBB seen on kep and ktrans maps
(not shown).
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TABLE 1. Summary of DCE- and ASL-Derived Indices in
High- and Low-Grade Glioma Using Student t Test
High Grade,
Mean (SD)
Parameters
rCBV
rCBF
kep, minj1
ktrans, minj1
ve
ASL-CBF
(mL/100 g/min)
ASL-rCBF
5.27
5.69
1.36
0.24
0.17
143.92
(1.32)
(1.99)
(0.88)
(0.11)
(0.10)
(108.41)
3.34 (1.01)
Low Grade,
Mean (SD)
2.49
2.22
0.19
0.04
0.10
137.34
(0.84)
(0.57)
(0.24)
(0.06)
(0.18)
(76.77)
2.93 (0.96)
P
G0.001
G0.001
G0.001
G0.001
0.09
0.78
0.11
in leaving part of the visible tumor to minimize possible neurologic sequelae. In the remaining 8 patients, only a partial resection was performed because of the location of the tumor in
eloquent regions.
The CBF values derived from 3D ASL imaging in grey
and white matter regions of healthy control subjects were found
to be [mean (SD)] 34.08 (10.78) and 16.56 (5.09) mL/100 g
per minute, respectively, whereas CBF derived from DCE-MRI
were found to be [mean (SD)] 54.51 (14.91) and 26.41 (12.48)
mL/100 g per minute, respectively. Arterial spin labelingYderived
absolute CBF and rCBF values and DCE-MRI indices from
low- and high-grade glioma are given in Table 1. On Student
t test, neither ASL-derived absolute CBF (P = 0.78) nor rCBF
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(P = 0.12) values were found to be significantly different in lowgrade compared with high-grade gliomas. On the other hand,
DCE-derived indices except ve were significantly higher in highgrade as compared with low-grade gliomas (Table 1).
Exploratory data analysis for DCE indices and ASL-derived
CBF values was conducted. The box plot of DCE indices for lowand high-grade glioma were distinct, and Tukey hinges were
nonoverlapping, which indicates a cutoff in DCE indices to differentiate low- and high-grade brain tumors. However, the box
plots of ASL values for low- and high-grade gliomas were
overlapping, suggesting no distinct cutoff for low- and highgrade gliomas (Fig. 3). Arterial spin labelingYderived rCBF
values poorly correlated with DCE-derived rCBF values (Fig. 4),
whereas there was no correlation between ASL and DCEMRIYderived CBF values of normal grey (P = 0.12, r = 0.2)
and white (P = 0.26, r = 0.14) matter regions.
DISCUSSION
In the present study, ASL-derived absolute CBF values
were not significantly different between histopathologically proven
high- and low-grade glioma. Even after normalizing these values
from the contralateral regions, the ASL-derived rCBF values
did not reach the level of statistical significance. On the other
hand, all the DCE-MRI indices (rCBV, rCBF, ktrans, and kep),
except ve, were found to be significantly higher in high-grade as
compared with low-grade glioma.
The increase in tumor burden leads to rapid increase in its
metabolic demand. To meet the increasing demand of the tumor
FIGURE 3. Box plot with Tukey Hinges show values of DCE and ASL-derived indices in high- and low-grade glioma. Note that neither
ASL-derived absolute (A) nor rCBF values (B) were distinct between low- and high-grade glioma; however, DCE-derived indices (CYF) show
clear differentiation between high- and low-grade glioma.
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FIGURE 4. Scatter plot shows weak correlation between
ASL-derived rCBF and DCE-derived rCBF values in high- and
low-grade gliomas.
tissue, the process of neoangiogenesis takes place, the degree of
which usually represents the aggressiveness of the neoplasm.
Dynamic contrast-enhanced perfusion imaging indices have
been widely used for the assessment of tumor and BBB permeability. Among these parameters, rCBV values have been
found to be most precise in glioma grading.16,28 However, we
need expertise in offline postprocessing to generate hemodynamic and permeability maps in DCE imaging because it is not
a commercially available product on the scanners and thus is a
great disadvantage. On the other hand, ASL does not require
administration of contrast agent, and hence, there is a lot of
emphasis on its development despite its ability to quantify only
CBF values. However, the CBF maps are made available immediately for quantification on all available scanners after acquisition and are an advantage to the users.
High perfusion values have been reported in imaging of
high-grade as compared with low-grade gliomas using continuous ASL. Authors concluded that ASL-derived CBF allows
reliable differentiation between low-grade and high-grade gliomas.29,30 However, in the current study, we did not find significant differences in ASL-derived CBF values between high- and
low-grade glioma.
Two broad techniques of ASL: continuous (CASL), which
uses a long train of square pulses to approximate a continuous
inversion of flowing spins, and PASL, which uses a short inversion pulse to label a fixed amount of blood, are available.
Theoretically, CASL has higher signal-to-noise ratio than PASL,
but it is limited to transmit/receive coils because of the high
radiofrequency duty cycle. Subsequently, a modification of CASL
was introduced as PCASL. It combines the advantage of better
signal-to-noise ratio of CASL and the lower power deposition of
PASL, which makes it possible to use the more sensitive array
coils and hence was better than the rest.31 However, the accurate
quantification by ASL methods depends on arterial transit times
to the voxels, local relaxation time of the tissue, and equilibrium
magnetization of the blood.30 Among these, transit time has the
most pronounced effect on the accuracy of its quantification.
In older patients or patients with cardiovascular abnormalities, lower perfusion results in longer transit times. As a result,
the distal end of the labeled bolus does not reach the capillary
bed and still contained in the arterial vessels leading to wrong
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Evaluation of 3D-PCASL With DCE Perfusion MRI
estimations. The assumption of a constant T1 relaxation time of
arterial blood irrespective of vessel size and blood oxygenation
may also lead to erroneous quantification. In addition, in case of
high flow rates, the general assumption of complete exchange
of labeled blood and tissue spins again leads to wrong estimation of CBF values. In a previous study, it has been reported that
some low-grade glioma showed increased perfusion foci whereas
some high-grade tumors were found to be hypoperfused.21
In PCASL, the inversion efficiency can be significantly
modulated by factors, such as gradient imperfections and the
presence of off-resonance fields, that cause a phase mismatch.32
Even if the PCASL sequence is theoretically optimized by
modulating the average gradient and phase accumulation between radio frequency pulses, the tagging efficiency of PCASL
can be compromised by local shifts in the magnetic field, and
thus the resonance frequency, at the tagging plane. A loss in
tagging efficiency leads to lower signal-to-noise perfusion maps
and may also cause considerable quantification errors in
CBF.33,34 The model used for quantification of perfusion does
not include measurement of transit time, which may be responsible for the erroneous results. In addition, the magnitude
of the errors may exhibit large and unpredictable variations between different subject population and scan sessions because offresonance fields depend on the shimming profiles of each scan
and scanners at different sites are likely to exhibit differences in
shimming and gradient performance.33,34 The aforementioned
flaws due to vulnerability of ASL are probably responsible for the
results in the current study.
Dynamic contrast-enhanced MRI methods offer a better
signal-to-noise ratio as compared with the ASL techniques in
addition to its ability to assess the integrity and extent of BBB
disruption. Dynamic contrast-enhanceYderived rCBV and rCBF
correspond to the degree of vascularization of a particular tissue, whereas its pharmacokinetic indices (eg, ktrans, kep, and ve)
have been widely used to quantify the extent of BBB disruption in various pathologic conditions of the central nervous
system.17Y20 All these indices are known to be useful in differentiating high-grade from low-grade brain tumors.28 In a previous
study, DCE-derived rCBV, kep, and ve were found to be significant
discriminators of low- and high-grade glioma.28 Consistent with
these previous findings, we have also observed that DCE-MRI
indices are significantly higher in high-grade as compared with
low-grade gliomas. These results reconfirm the ability of DCEMRI in noninvasive characterization of gliomas. On the other
hand, ASL provides only CBF measure and is unable to provide
information regarding BBB integrity. In addition, ASL-derived
rCBF values weakly correlated with DCE derived rCBF values,
whereas no correlation was observed between ASL and DCEMRI derived CBF values in normal grey (P = 0.12, r = 0.2) and
white (P = 0.26, r = 0.14) matter regions. These inconsistencies
of ASL may be due to intersubject variability and previously
mentioned limitations. Consequently it appears to be inept in
quantitative assessment of brain tumors and require further improvement in technique to establish it as an effective imaging
biomarker of tumor grade.
We conclude that despite the advances in technical development of ASL, the results of this study suggest that the
currently available ASL method still suffer from interpatient
variability. The product sequence may need some optimization
to use it reliably in the clinical settings for glioma grading. On
the other hand, DCE-MRI technique still remains ideal for
quantitative assessment of perfusion in gliomas because it provides both pharmacokinetic (ktrans and kep) and hemodynamic
parameters (CBV and CBF), which helps to accurately characterize tumor physiology more comprehensively.
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