Keywords
Arterial spin labelled perfusion imaging (ASL-PI) - brain tumors - preoperative prognostication
- tumor blood flow (TBF) estimation - tumor microvessel density
Introduction
Brain tumor is an important cause of morbidity and mortality all across the world.[1] Digital angiography is considered as the ultimate gold standard for preoperative
estimation of tumor vascularity, which is of great significance for a neurosurgeon;
however, it is invasive and time consuming, hence not routinely done as part of tumor
investigation protocol.[2]
[3] Magnetic resonance imaging (MRI) perfusion parameters give insight about the tumor
vascularity and vessel proliferation in a reasonably noninvasive manner.[4]
[5]
[6] Conventional dynamic susceptibility contrast perfusion MRI (DSC) is a widely used
technique in which initial transit of contrast medium is obtained using T2*-weighted
images It involves bolus injection of contrast material through large bore intravenous
cannulas for the evaluation of blood flow to the brain tumors. However, exogeneous
contrast injection is not feasible in patients with poor renal status and generalized
debilitated state.
Arterial spin labeling perfusion imaging (ASL-PI) is an evolving MRI modality that
measures cerebral blood flow (CBF) and calculates CBF by magnetically labeling the
arterial blood protons that flows into the region of interest (ROI), without the need
of exogenous contrast. The difference in signal between the images is directly proportional
to the extent of magnetization inversion received by the ROI. Consequently, ASL-PI
is favorable for patients with renal dysfunction, pediatric population, and those
necessitating repeated follow-up scans.[7]
There are hardly any studies evaluating relationship between ASL-PI estimated tumor
vascularity, histopathological findings, and prognosis of brain tumor in Indian population.
Therefore, there is a need to establish a correlation between ASL-PI derived tumor
blood flow (TBF) and histopathological assessment of vascularity in brain tumors in
our clinical scenario. Aim of our study was to correlate TBF using ASL-PI with microvessel
density (MVD), tumor grade, and preoperative prognostication of brain tumors.
Materials and Methods
This was a prospective observational study in a tertiary care hospital over a period
of eighteen months from September 2020 to February 2022. Total 63 patients of primary
brain neoplasm already undergoing MRI were included in the study. Patients with a
known primary tumor with cerebral metastases, previous brain tumor surgery, metallic
clips, pacemakers, or other generalized contraindications for MRI were excluded.
Methodology
MRI was acquired in a single session on 3T MR Imaging Scanner GE Discovery, 750, Milwaukee,
Wisconsin with a 32-channel phased array head-neck-spine coil. Prior approval was
taken from our institutional ethics review board. Written informed consent was taken
from every patient fulfilling the inclusion criteria. Relevant clinical history was
obtained from all patient and findings were recorded in a pre-determined Proforma.
After performing conventional MRI sequences (pre- and post-contrast 3D T1-weighted
(T1W), axial and coronal T2W and necessary fluid-attenuated inversion recovery images),
3D ASL was performed by the use of pseudo-continuous labeling technique. Ponto-medullary
junction was used as the labeling plane to avoid the curved petrous segment of internal
carotid artery (ICA) and select the terminal segment of ICA. The tumor in its greatest
dimension was made to coincide with the imaging plane, by referring to the conventional
MRI sequences.
Post-Processing
ASL-colored maps were produced using READY view software. ROIs were placed, in the
axial plane, in the region with maximum perfusion based on the color maps corresponding
to solid tumor as was seen on the T1W post-contrast image. Area with cysts, calcification,
necrosis, and blood vessels were avoided (based on T1W and T2W images).
Three to five nonoverlapping equal sized ROIs individually measuring at least more
than or equal to 5 mm were visually placed on the tumors in the axial color coded
ASL images.
The absolute mean TBF (mean TBF) was calculated by averaging the value of 3 to 5 ROIs
showing high TBF values. The absolute maximum TBF (max TBF) was represented by the
ROI showing maximum value among all.
The mean CBF value (mean CBF) was calculated from 3 to 5 ASL ROIs placed in normal
appearing cortical gray matter (using T1W images) and the maximum CBF value (maxCBF)
was represented by the cortical ROI showing maximum value among all.
Values were normalized to CBF by calculating the ratio of absolute TBF values with
CBF values to get relative TBF values (rTBFmean and rTBFmax).
Histopathological Evaluation
The patients were followed up and tumor tissue biopsy sample of operated patients
was sent for histopathological analysis to look for MVD and tumor grade. To calculate
the MVD, tissue sections were immunostained using a monoclonal mouse antibody directed
against CD34 antigen, which identifies vascular endothelial cells. Areas with highest
neovascularization (hot spots) were identified on low power magnification (40X) after
CD34 immunohistochemistry was performed. Microvessels within the tumor were counted
in three hotspots at 10X and 40X magnification and the mean of the three values was
considered to be the MVD.
Statistical Analysis
Data was entered in MS EXCEL spreadsheet and analyzed using 21.0 version of Statistical
Package for Social Sciences. Number and percentages represented categorical variables,
while mean and median were represented by continuous variables. Normality of data
was tested by appropriate statistical tests like Kolmogorov–Smirnov test. Correlation
between perfusion parameters (meanTBF, maxTBF, rTBFmean, rTBFmax) and MVD (at 10X
and 40X magnification) were performed using Spearman Rank Order Correlation.
Results and Observations
Total 63 patients of primary brain tumor were studied. The range for patient age was
between 6 and 72 years and median age was 40 years. Forty-three (68.6%) males and
20 (31.4%) females were included. Most of the patients presented with complaints of
headache, hemiparesis, seizures, and blurring of vision. There were 36 gliomas, 16
meningiomas, eight schwannomas, two craniopharyngiomas, and one hemangioblastoma.
Data was normally distributed following a bell-shaped curve.
The mean of meanTBF values (mL/min/100 g) found in the gliomas group, meningiomas
group, schwannoma group, craniopharyngioma group, and hemangioblastoma group was 145.58,
192.26, 85.77, 36.50, and 402.90, respectively. The median of meanTBF values in the
glioma group, meningioma group, schwannoma group, craniopharyngioma group, and hemangioblastoma
group was 121.65, 137.82, 83.5, 36.5, and 402.9, respectively.
The mean of maxTBF values (mL/min/100 g) in the glioma group, meningioma group, schwannoma
group, craniopharyngioma group, and hemangioblastoma group was 147.15, 251.55, 96.43,
43.3, and 578.3, respectively. The median of maxTBF value in the glioma group, meningioma
group, schwannoma group, craniopharyngioma group, and hemangioblastoma group was 131.5,
158.63, 94.5, 43.4, and 578.3, respectively.
The mean of rTBFmean values (mL/min/100 g) turned out to be 3.46 in case of glioma,
4.73 in case of meningioma, 2.22 in case of schwannoma, 1.17 in case of craniopharyngioma,
and 14.92 in case of hemangioblastoma. The median of rTBFmean value was found to be
3.76 in glioma, 4.34 in meningioma, 2.49 in schwannoma, 1.17 in craniopharyngioma,
and 14.92 in hemangioblastoma.
The mean of rTBFmax values (mL/min/100 g) turned out to be 4.12 in case of gliomas,
3.67 in case of meningiomas, 3.52 in case of schwannomas, 2.62 in case of craniopharyngiomas,
and 3.87 in case of hemangioblastoma. The median of rTBFmax value was found to be
3.82 in gliomas, 3.53 in meningiomas, 5.1 in schwannomas, 3.6 in craniopharyngiomas,
and 38.75 in hemangioblastoma.
The mean TBF, max TBF, rTBFmean, and rTBFmax value was maximum in hemangioblastomas
followed by meningiomas and gliomas ([Table 1]).
Table 1
Tumor blood flow parameters in different tumor sybtypes
|
Tumor type
|
|
Gliomas
|
Meningiomas
|
Schwannoma
|
Craniopharyngioma
|
Hemangioblastoma
|
|
meanTBF (mL/min/100 g)
|
Mean
|
145.58
|
192.26
|
85.77
|
36.5
|
402.90
|
|
Median
|
121.65
|
137.82
|
83.5
|
36.5
|
402.9
|
|
Range
|
25.8–297
|
8.3368.4
|
52–115
|
6–67
|
402.9–402.9
|
|
maxTBF
(mL/min/100 g)
|
Mean
|
147.15
|
251.55
|
96.1
|
43.3
|
578.3
|
|
Median
|
131.5
|
158.63
|
94.5
|
43.4
|
578.3
|
|
Range
|
30.4–308.4
|
11–386.3
|
63–129.2
|
8.8–78
|
578.3–578.3
|
|
rTBF mean (mL/min/100 g)
|
Mean
|
3.46
|
4.73
|
2.22
|
1.17
|
14.92
|
|
Median
|
3.76
|
4.34
|
2.49
|
1.17
|
14.92
|
|
Range
|
0.81–8.25
|
0.4–6.52
|
1.16–3.01
|
0.25–2.09
|
14.92–14.92
|
|
rTBFmax (mL/min/100 g)
|
Mean
|
4.120
|
3.670
|
4.852
|
3.623
|
38.75
|
|
Median
|
3.822
|
3.534
|
5.19
|
3.623
|
38.75
|
|
Range
|
15.88–60.77
|
17.49–59.25
|
31.4–54.16
|
35.2–37.25
|
38.75–38.75
|
Abbreviation: rTBF, relative tumor blood flow.
Positive correlation was observed between vessel count (at 10X/40X magnification)
and meanTBF (mL/min/100 g), maxTBF (mL/min/100 g), rTBFmean, and rTBFmax value was
statistically significant (p = < 0.001). The scatterplot ([Fig. 1]) illustrates the association between rTBFmean/rTBF max with vessel count at 10X
/ 40X magnification, respectively.
Fig. 1 Scatter plot diagram. Individual points represent individual cases. The blue trend
line represents the general trend of correlation between the two variables. The shaded
gray area represents the 95% confidence interval of this trend line. A and B depict correlation of relative tumor blood flow (rTBF) mean with 10X (A) and 40X (B) magnification. C and D depict correlation of rTBF max with 10X (C) and 40X (D) magnification. Spearman correlation coefficients were 0.8, 0.6, 0.4, and 0.3, respectively.
The meanTBF, maxTBF, rTBFmean, and rTBFmax (mL/min/100 g) of gliomas was not normally
distributed in different World Health Organization (WHO) grades. The median value
of meanTBF in grade I, II, III, and IV gliomas (as per 2016 WHO classification) was
38, 71.7, 138.6, and 165.7 mL/min/100 g, respectively. Median value of TBFmax in increasing
grades was 51, 78.2, 150, and 208 mL/min/100 g, respectively. However, no statically
significant difference was observed (Kruskal–Wallis test) in mean TBF (χ2 = 4.588,
p = 0.205) among different subgroups. Strength of association (Kendall's Tau) came
out to be 0.36 (medium effect size). Similarly no statically significant difference
was observed in maxTBF (χ2 = 4.770, p = 0.189) with strength of association (Kendall's Tau) being 0.37 (medium effect size),
or rTBFmean (χ2 = 6.582, p = 0.087) with strength of association (Kendall's Tau) as 0.48 (medium effect size).
The rTBFmax (χ2 = 3.143, p = 0.370) also showed no statically significant difference as strength of association
(Kendall's Tau) was 0.12 (Small Effect Size).
TBF values in typical meningiomas were higher (TBFmean: 368.4 mL/min/100 g, TBFmax:
386.3 mL/min/100 g, rTBFmean: 6.5, rTBFmax: 52.9), and in a case of atypical meningioma
TBF value was lower (TBFmean: 11.6 mL/min/100 g, TBFmax: 15 mL/min/100 g, rTBFmean:
0.4, and rTBFmax: 37.5).
Discussion
ASL-PI, in which a magnetically “labeled” image is subtracted from a nonlabeled “reference”
image can be used as a modality to estimate the MVD of tumor without any use of exogenous
contrast, thereby predicting the vascularity of the tumor.
Our study showed a positive correlation among meanTBF and MVD at 10X magnification
(p-value < 0.001, rho =0.88) and a moderate positive correlation among meanTBF and MVD
at 40X magnification (p-value <0.001). Additionally, positive correlation was observed between maxTBF and
MVD at 10X magnification (p-value <0.001, rho = 0.91) and between maxTBF and MVD at 40X magnification. These
findings were found to be in agreement with studies by Noguchi et al,[8] Koizumi et al,[9] Kikuchi K et al,[10] and Kimura et al[11] which also show a positive correlation between meanTBF and maxTBF with MVD (or percentage
vessel count).
We found that TBF in case of the hemangioblastoma ([Fig. 2]) was higher than other tumors (namely meningiomas, gliomas, and schwannomas), which
was in agreement with the study performed by T. Noguchi et al.[8] This corroborates with the fact that there is marked neovascularity with large vessels
within the lesion. This could potentially be helpful in eliminating the differential
diagnosis of posterior fossa lesions having a cyst with solid nodule type of enhancement;
the lesion with high TBF would point toward diagnosis of hemangioblastoma.
Fig. 2 Post-contrast axial T1-weighted imaging (A) and corresponding arterial spin labeling map (B) in case of a hemangioblastoma in posterior fossa show markedly raised tumor blood
flow (TBF; TBFmean: 402.9 mL/min/100 g, TBFmax: 578.3 mL/min/100 g, rTBFmean: 14.9,
rTBFmax: 38.7) in the enhancing areas. (C and D) Histopathological microvessel density seen on 10X and 40X magnification, respectively.
TBF by ASL-PI can assess tumor neovascularity, which plays a crucial role in histologic
grading of tumor. Present study demonstrated low TBF values in low grade than high
grade gliomas ([Fig. 3]). In most of the cases, there was an increasing trend seen between TBF values and
increasing grade of gliomas. Such association of TBF values with grading of gliomas
was also demonstrated by Noguchi et al,[8] Wang et al,[12] Yeom et al,[13] and Abdel-Razek et al.[14] Arisawa et al in 2018 concluded that ASL-PI can be considered as an alternate perfusion
MRI method in distinguishing low- to high-grade gliomas where DSC cannot be used.[15] Khashbat et al in 2017 established that TBF by ASL-PI can be used to distinguish
low- to high-grade nonenhancing astrocytic tumors as well.[16] This study revealed a worse perioperative prognosis and a higher mortality in high
as compared with low grade glioma.
Fig. 3 Post-contrast axial T1-weighted imaging (A, C) and corresponding arterial spin labeling map (B, D) in case of a low grade (A, B with TBFmean: 67 mL/min/100 g, TBFmax: 75mL/min/100 g, rTBFmean: 4, rTBFmax: 58.3)
and high grade (C, D with TBFmean: 195 mL/min/100 g, TBFmax: 266.3 mL/min/100 g, rTBFmean: 5.9, rTBFmax:
44.7) gliomas, respectively. rTBF mean, relative mean tumor blood flow.
Our study uncovered that TBF was high in typical meningiomas whereas low in atypical
meningioma ([Fig. 4]). This was in concordance with study published by Qiao et al[17] who described three different visual patterns of ASL-derived CBF maps in cases of
meningiomas with higher-grade meningiomas depicting no substantial hyper perfusion.
This knowledge helped the surgeon as more difficulties were encountered in high grade/atypical
meningiomas due to parenchymal invasion. There was better understanding of tumor margin
and estimation of extent of resection preoperatively. Potentially complex surgeries
with higher chances of complication and longer operative time could be predicted.
As was seen in our case of angiomatous meningioma, where presence of pial-cortical
arterial supply helped in predicting higher chances of bleeding and difficult resection.
Similar findings were observed by ElBeheiry et al as well.[18]
In our study, ASL-PI proved valuable in estimating the absolute quantitative values
of CBF. This is not always possible in DSC perfusion, as it lacks a direct linear
relationship between signals changes and contrast concentration, more so in cases
with partial volume artifacts. As ASL-PI relies on the intrinsic diffusible tracer,
it was not affected by permeability characteristics in comparison to DSC perfusion
MRI, in which permeability acts as a main confounding factor in the measurement accuracy
of relative Cerebral blood Volume (CBV) values.[19] ASL helped in providing a roadmap for the evaluation of tumor infiltration. It was
useful in targeting the site of biopsy from the highest-grade portion of the tumor,
thus assisting accurate grading of a tumor.
Limitations
Our sample size was relatively small due to ongoing coronavirus disease 2019 pandemic
at the time. Studies with a larger sample size and in different brain tumor subgroups
can aid in establishing ASL-PI as a standard preoperative prognostic tool. Furthermore,
ASL-PI is affected by the flow related biophysics, as inversion time for labeling
varies with the changing hemodynamics. One needs to be careful while selecting these
parameters, as low values are required for pediatric and geriatric populations. ASL-PI
has low signal to noise ratio with longer acquisition time when compared with other
perfusion techniques. Another limitation of ASL is that it can produce an underestimation
of CBF by causing prolongation of arterial transit times causing relaxation of spin-label
in cases of severe ischemia.[20] Some low-grade tumors may also exhibit excessive vascularity, thereby showing markedly
raised TBF as in the cases of oligodendroglioma. In addition, presently ASL-PI can
provide only CBF values; however, future developments in ASL techniques may be able
to derive other perfusion parameters like CBV for brain tumors. Limited published
literature could be found on grading and prognostication of brain tumors based on
ASL-PI.
Conclusion
In our study, we observed a positive association between TBF calculated using ASL-PI
and the brain tumor MVD, thereby assessing tumor vascularity. This knowledge plays
an important role in surgical decision making, scheduling presurgical interventions
such as preoperative embolization, and provides valuable acumen in predicting patient
prognosis. TBF by ASL-PI can be considered a noninvasive in vivo marker in predicting
the grade of brain tumors and further assist in envisaging prognosis of the patients
with brain tumors. However, comprehensive investigation of correlation between ASL-PI,
tumor vascularity, and grading is further necessary in specific subtypes of brain
tumor. Further development is desired in ASL-PI technique to additionally assist in
CBV calculations in assessing brain tumor vascularity.
Fig. 4 Post-contrast axial T1-weighted imaging (A, C) and corresponding arterial spin labeling map (B, D) in case of typical (A, B with TBFmean: 127.6 mL/min/100 g, TBFmax: 143.6 mL/min/100 g, rTBFmean: 4, rTBFmax:
35.7) and atypical (C, D with TBFmean: 11.6 mL/min/100 g, TBFmax: 15 mL/min/100 g, rTBFmean: 0.4, rTBFmax:
37.5) meningiomas, respectively. rTBF mean, relative mean tumor blood flow.
