Gliomas grading is important for treatment plan; we aimed to investigate the application of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) in gliomas grading, by comparing with the three-dimensional pseudocontinuous arterial spin labeling (3D pCASL). 24 patients (13 high grade gliomas and 11 low grade gliomas) underwent IVIM DWI and 3D pCASL imaging before operation; maps of fast diffusion coefficient (
Gliomas are the most common primary tumor in brain. More accurate preoperative grading of gliomas could increase the rationality of treatment plans and judge prognosis. Generally, blood supply of high grade gliomas is significantly higher than that of low grade gliomas. Perfusion imaging can assess tumor blood supply, which could provide a reference for glioma grading. The main nonenhanced method of perfusion in MRI is arterial spin labeling (ASL). In addition, there is another solution, intravoxel incoherent motion (IVIM); it also does not need contrast agent; thus it is safe, repeatable, and without radiation burden.
IVIM is the microscopic translational movement occurring in each image voxel during an MRI acquisition, which was proposed by Le Bihan et al. [
The 3D pCASL is one submethod of ASL. It had been widely studied in gliomas and had reliable results with dynamic susceptibility contrast (DSC) [
The present study was approved by the Local Institutional Review and a written informed consent was obtained from all patients. From September 2013 to June 2014, 24 patients (nineteen men and five women, age range from 16 to 65 years, mean age 42 ± 14.24 years) confirmed as having gliomas by pathology were recruited and took MRI examinations before operation. The pathology results of all subjects were shown in Table
Summary of pathology of all subjects.
WHO grade | Age | Pathology | Location | |
---|---|---|---|---|
HGG | WHO III-IV |
Average, 51 years |
5 glioblastomas | 3 in parietal lobe |
8 anaplastic astrocytomas | 4 in the frontal lobe | |||
1 in parietal lobe | ||||
1 in temporal lobe | ||||
1 in lateral ventricle | ||||
1 in vermis cerebella | ||||
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7 diffuse astrocytomas | 3 in temporal lobe | |||
LGG | WHO I-II |
Average, 32 years |
3 oligodendrogliomas | 2 in the parietal lobe |
1 capillary astrocytoma | 1 in cerebellar |
HGG: high grade gliomas, LGG: low grade gliomas.
All MR data was acquired on a 3 T magnetic resonance (MR) scanner (Discovery MR750 System; GE Medical Systems, Milwaukee, WI, USA) with an 8-channel receiver head coil. DW-MR imaging was based on a standard Stejskal-Tanner diffusion-weighted spin-echo EPI pulse sequence with the following parameters: TR/TE = 3000/87.5 ms, field of view (FOV) = 24.0 cm, base resolution = 128 × 128, slice thickness = 5.0 mm, intersection gap = 1.5 mm, and a bandwidth = 250 Hz. Axial DW-imaging was acquired with multiple
After acquiring DWI and ASL imaging, axial T2-weighted imaging (Propeller, TR/TE = 4,300/103 ms, slices with thickness = 5.0 mm, and intersection gap = 1.5 mm), 3D T1-weighted imaging (3D-T1WI, BRAVO, TR/TE = 8,200/3,200 ms, slice thickness = 4.0 mm, and number of slices = 36), and coronal T2-fluid attenuated inversion recovery weighted imaging (TR/TE = 4,300/93 ms, slices with thickness = 5.0 mm, and intersection gap = 1.5 mm) were acquired. Axial T1-weighted imaging (FLAIR, TR/TE = 1,750/24 ms, slices with thickness = 5.0 mm, and intersection gap = 1.5 mm) was acquired before and after intravenous body weight adapted administration of gadobutrol (Dextran 40 Glucose Injection, Consun Pharmaceutical Group, Guangzhou, Guangdong, China).
The DWI imaging was calculated by at two-segment monoexponential algorithm as shown in IVIM equation (
Diffusion maps and structural 3D-T1WI images and were, respectively, coregistered to CBF images using SPM8 (
Coregistered images with ROIs. CBF map (a) and corresponding slice of 3D-T1WI (b) as well as DWI map (c).
Normal probability plot and Shapiro-Wilk’s test were used to analyze data distribution. Pairwise comparisons of ASL and IVIM parameters between HGG and LGG were calculated. Bivariate correlations of parameters of ASL and IVIM DWI as well as IVIM DWI and conventional DWI were assessed. Student’s
The ASL and IVIM-DWI data of 24 patients yielded high quality images with good SNR with CBF and IVIM postprocessing (Figures
Female, aged 43 years with a glioblastoma of the right parietal lobe (WHO IV). The axial T2-weighted image (a) shows the medium signal thick walled mass with a hyperintense central cystic necrosis and peritumoral edema. Enhanced T1-weighted images (b) show the significantly enhanced tumor wall. CBF map (c) shows that the wall of the mass with unevenly high perfusion; the TBF and CBF of contralateral semioval center were 89.90 and 16.89 mL/100 g/min, respectively. The
Male, aged 33 years with astrocytoma glioma in the right parietal (WHO II). The mass was hyperintensive with a fuzzy edge in axial T2-weighted image (a) and without any gadolinium enhancement (b). It shows slight perfusion in the CBF map (c) but fails to distinguish the boundaries of the tumor from normal brain substance. The TBF and CBF of contralateral semioval center were 80.72 and 27.53 mL/100 g/min, respectively. The
Mean CBF and
Mean ASL and IVIM parameters in HGG and LGG as well as ROC analysis.
HGG | LGG | Test type |
|
AUC | Cutoff value | ||
---|---|---|---|---|---|---|---|
Tumor | TBF | 102.04 ± 45.55 | 62.26 ± 18.13 | tt |
|
0.783 | 63.17 |
|
5.1 ± 3.39 | 2.77 ± 0.69 | mw |
|
0.857 | 3.5 | |
|
0.69 ± 0.09 | 0.81 ± 0.12 | tt |
|
0.818 | 0.58 | |
|
0.4 ± 0.11 | 0.49 ± 0.1 | tt |
|
0.769 | 0.43 | |
ADC | 0.85 ± 0.09 | 1.04 ± 0.13 | tt |
|
0.85 | 0.96 | |
|
|||||||
WM | CBF | 25.25 ± 3.46 | 27.64 ± 8.21 | mw | 0.733 | ||
|
2.5 ± 0.18 | 2.52 ± 0.29 | mw | 0.691 | |||
|
0.41 ± 0.02 | 0.41 ± 0.02 | tt | 0.801 | |||
|
0.32 ± 0.03 | 0.29 ± 0.01 | mw | 0.207 | |||
ADC | 0.53 ± 0.03 | 0.53 ± 0.01 | tt | 0.857 |
Significant
In tumors, CBF was negatively correlated with the
Histogram parameters in tumor from the ASL and IVIM DWI scans were compared between HGG and LGG. For ASL, the maximum of CBF had the lowest
Histogram parameters of solid component in tumor from the ASL and MB-DWI from histogram analysis as well as ROC analysis in HGG and LGG (mean ± SD).
Tumor | HGG | LGG |
|
Test type | AUC | Cutoff | |
---|---|---|---|---|---|---|---|
CBF | Mean (mL/100 g/min) | 102.04 ± 45.55 | 62.26 ± 18.13 | 0.011 | tt | 0.783 | |
Median (mL/100 g/min) | 99.65 ± 42.08 | 62.59 ± 18.07 | 0.011 | tt | 0.801 | ||
Maximum (mL/100 g/min) | 160.77 ± 80.72 | 91.27 ± 30.89 | 0.002 | mw |
|
|
|
Minimum (mL/100 g/min) | 54.08 ± 30.13 | 31.64 ± 8.96 | 0.022 | tt | 0.738 | ||
90th percentile (mL/100 g/min) | 132.15 ± 68.18 | 78.91 ± 25.35 | 0.015 | mw | 0.787 | ||
Standard deviation (mL/100 g/min) | 22.51 ± 16.07 | 13.15 ± 5.77 | 0.035 | mw | 0.755 | ||
Skewness | 0.22 ± 0.32 | −0.06 ± 0.25 | 0.024 | tt | 0.79 | ||
Kurtosis | 2.92 ± 0.76 | 2.64 ± 0.44 | 0.649 | mw | 0.559 | ||
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|
Mean ( |
5.1 ± 3.39 | 2.77 ± 0.69 | 0.002 | mw |
|
|
Median (10−3 mm2/s) | 3.54 ± 1.52 | 2.58 ± 0.33 | 0.002 | mw | 0.85 | ||
Maximum (10−3 mm2/s) | 30.28 ± 21.91 | 9.38 ± 8.72 | 0.015 | mw | 0.79 | ||
Minimum (10−3 mm2/s) | 0.84 ± 0.76 | 1.46 ± 0.77 | 0.03 | mw | 0.238 | ||
90th percentile (10−3 mm2/s) | 9.86 ± 10.22 | 4.02 ± 1.46 | 0.006 | mw | 0.825 | ||
Standard deviation (10−3 mm2/s) | 3.39 ± 3.35 | 13.8 ± 1.58 | 0.055 | mw | 0.734 | ||
Skewness | 2.81 ± 1.93 | 1.66 ± 1.3 | 0.186 | mw | 0.664 | ||
Kurtosis | 19.93 ± 20.46 | 10.04 ± 4.96 | 0.569 | mw | 0.573 | ||
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|
Mean (10−3 mm2/s) | 0.69 ± 0.09 | 0.81 ± 0.12 | 0.013 | tt | 0.818 | |
Median ( |
0.69 ± 0.09 | 0.82 ± 0.11 | 0.006 | mw |
|
|
|
Maximum (10−3 mm2/s) | 0.98 ± 0.19 | 1.07 ± 0.15 | 0.15 | mw | 0.678 | ||
Minimum (10−3 mm2/s) | 0.29 ± 0.25 | 0.55 ± 0.25 | 0.039 | tt | 0.755 | ||
90th percentile (10−3 mm2/s) | 0.83 ± 0.14 | 0.95 ± 0.11 | 0.029 | tt | 0.766 | ||
Standard deviation (10−3 mm2/s) | 0.12 ± 0.05 | 0.12 ± 0.08 | 0.776 | mw | 0.465 | ||
Skewness | −0.45 ± 1.23 | −0.42 ± 1.39 | 0.955 | mw | 0.49 | ||
Kurtosis | 6.63 ± 5.09 | 5.12 ± 6.53 | 0.063 | mw | 0.273 | ||
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|
Mean (10−3 mm2/s) | 0.4 ± 0.11 | 0.49 ± 0.1 | 0.039 | tt | 0.769 | |
Median (10−3 mm2/s) | 0.39 ± 0.12 | 0.49 ± 0.11 | 0.025 | tt |
|
|
|
Maximum (10−3 mm2/s) | 0.81 ± 0.18 | 0.84 ± 0.14 | 0.82 | mw | 0.528 | ||
Minimum (10−3 mm2/s) | 0.14 ± 0.07 | 0.22 ± 0.12 | 0.042 | tt | 0.766 | ||
90th percentile (10−3 mm2/s) | 0.57 ± 0.16 | 0.67 ± 0.15 | 0.14 | tt | 0.678 | ||
Standard deviation (10−3 mm2/s) | 0.13 ± 0.05 | 0.14 ± 0.05 | 0.728 | tt | 0.528 | ||
Skewness | 0.73 ± 0.69 | 0.29 ± 0.49 | 0.09 | tt | 0.297 | ||
Kurtosis | 4.22 ± 2.83 | 2.89 ± 1.04 | 0.11 | tt | 0.301 | ||
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ADC | Mean (10−3 mm2/s) | 0.85 ± 0.09 | 1.04 ± 0.13 | 0.001 | tt | 0.85 | |
Median ( |
0.85 ± 0.11 | 1.07 ± 0.12 | 0.000 | mw |
|
|
|
Maximum (10−3 mm2/s) | 1.37 ± 0.29 | 1.42 ± 0.21 | 0.648 | tt | 0.58 | ||
Minimum (10−3 mm2/s) | 0.43 ± 0.27 | 0.65 ± 0.28 | 0.054 | tt | 0.75 | ||
90th percentile (10−3 mm2/s) | 1.07 ± 0.17 | 1.24 ± 0.16 | 0.019 | tt | 0.76 | ||
Standard deviation (10−3 mm2/s) | 0.16 ± 0.07 | 0.17 ± 0.05 | 0.528 | tt | 0.6 | ||
Skewness | 0.23 ± 1.5 | −0.16 ± 0.89 | 0.457 | tt | 0.35 | ||
Kurtosis | 6.67 ± 5.11 | 3.35 ± 1.95 | 0.04 | tt | 0.21 |
Statistically significant values are presented in bold font. mw: Mann-Whitney
LGG: low grade gliomas, AUC: area under the curve.
Histogram parameters of white matter from the ASL and MB-DWI from histogram analysis as well as ROC analysis in HGG and LGG (mean ± SD).
White matter | HGG | LGG | Test type |
| |
---|---|---|---|---|---|
CBF | Mean (mL/100 g/min) | 25.25 ± 3.46 | 27.64 ± 8.21 | mw | 0.733 |
Median (mL/100 g/min) | 25.69 ± 5.15 | 27.33 ± 7.48 | mw | 0.649 | |
Maximum (mL/100 g/min) | 38.62 ± 5.23 | 42.91 ± 12.49 | mw | 0.955 | |
Minimum (mL/100 g/min) | 13.82 ± 5.44 | 15.91 ± 7.79 | mw | 0.459 | |
90th percentile (mL/100 g/min) | 33.62 ± 4.75 | 35.18 ± 10.94 | mw | 0.459 | |
Standard deviation (mL/100 g/min) | 6.77 ± 3.62 | 6.14 ± 2.39 | mw | 0.331 | |
Skewness | 2.37 ± 7.86 | 2.32 ± 0.47 | mw | 0.776 | |
Kurtosis | 2.38 ± 0.45 | 2.86 ± 0.55 | mw |
|
|
|
|||||
|
Mean (10−3 mm2/s) | 2.5 ± 0.18 | 2.52 ± 0.29 | mw | 0.691 |
Median (10−3 mm2/s) | 2.44 ± 0.18 | 2.48 ± 0.27 | mw | 0.91 | |
Maximum (10−3 mm2/s) | 3.72 ± 0.62 | 3.79 ± 0.65 | mw | 0.733 | |
Minimum (10−3 mm2/s) | 1.76 ± 0.16 | 1.82 ± 0.19 | tt | 0.429 | |
90th percentile (10−3 mm2/s) | 2.99 ± 0.34 | 2.95 ± 0.26 | tt | 0.992 | |
Standard deviation (10−3 mm2/s) | 0.42 ± 0.11 | 0.39 ± 0.09 | tt | 0.453 | |
Skewness | 0.68 ± 0.36 | 0.75 ± 0.32 | tt | 0.627 | |
Kurtosis | 3.49 ± 1.24 | 3.88 ± 1.2 | mw | 0.459 | |
|
|||||
|
Mean (10−3 mm2/s) | 0.41 ± 0.02 | 0.41 ± 0.02 | tt | 0.801 |
Median (10−3 mm2/s) | 0.4 ± 0.02 | 0.41 ± 0.02 | tt | 0.473 | |
Maximum (10−3 mm2/s) | 0.47 ± 0.03 | 0.49 ± 0.04 | tt | 0.161 | |
Minimum (10−3 mm2/s) | 0.35 ± 0.03 | 0.33 ± 0.02 | tt | 0.083 | |
90th percentile (10−3 mm2/s) | 0.44 ± 0.03 | 0.45 ± 0.02 | tt | 0.385 | |
Standard deviation (10−3 mm2/s) | 0.03 ± 0.01 | 0.04 ± 0.01 | mw | 0.252 | |
Skewness | 0.11 ± 0.63 | −0.11 ± 0.34 | tt | 0.308 | |
Kurtosis | 2.56 ± 0.66 | 2.47 ± 0.41 | tt | 0.707 | |
|
|||||
|
Mean (10−3 mm2/s) | 0.32 ± 0.03 | 0.29 ± 0.01 | mw | 0.207 |
Median (10−3 mm2/s) | 0.3 ± 0.02 | 0.29 ± 0.01 | mw | 0.608 | |
Maximum (10−3 mm2/s) | 0.4 ± 0.08 | 0.37 ± 0.04 | mw | 0.331 | |
Minimum (10−3 mm2/s) | 0.25 ± 0.02 | 0.26 ± 0.01 | mw | 0.82 | |
90th percentile (10−3 mm2/s) | 0.37 ± 0.08 | 0.33 ± 0.03 | mw | 0.15 | |
Standard deviation (10−3 mm2/s) | 0.04 ± 0.03 | 0.02 ± 0.01 | mw | 0.207 | |
Skewness | 0.54 ± 0.47 | 0.47 ± 0.76 | tt | 0.785 | |
Kurtosis | 3.07 ± 1.41 | 3.41 ± 0.84 | mw | 0.106 | |
|
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ADC | Mean (10−3 mm2/s) | 0.53 ± 0.03 | 0.53 ± 0.01 | tt | 0.857 |
Median (10−3 mm2/s) | 0.53 ± 0.03 | 0.53 ± 0.02 | tt | 0.988 | |
Maximum (10−3 mm2/s) | 0.64 ± 0.08 | 0.62 ± 0.05 | tt | 0.64 | |
Minimum (10−3 mm2/s) | 0.46 ± 0.02 | 0.45 ± 0.02 | tt | 0.293 | |
90th percentile (10−3 mm2/s) | 0.59 ± 0.08 | 0.58 ± 0.05 | tt | 0.826 | |
Standard deviation (10−3 mm2/s) | 0.04 ± 0.02 | 0.04 ± 0.02 | mw | 0.82 | |
Skewness | 0.45 ± 0.8 | 0.13 ± 0.57 | tt | 0.278 | |
Kurtosis | 3.28 ± 1.47 | 2.78 ± 0.74 | mw | 0.392 |
Statistically significant values are presented in bold font. mw: Mann-Whitney
There were many kinds of water molecule movements in brain tissue, including intracellular, intercellular, and transmembrane molecular diffusion, as well as microcirculation of blood in the capillary network. It has been confirmed that when applying a diffusion gradient field of high
Compared to previously recent published works in gliomas [
For example, mean values of
Like CBF,
In this study, the
Compared to LGG, the
Through the measurement process of the cerebral cortex, it was found that the cerebrospinal fluid in sulcus had a larger impact on the
Currently, perfusion methods of MRI were mainly DSC and ASL. DSC was based on precise understanding of the arterial input function and a lot of assumptions. Thus, it was difficult to measure and quantify [
Like ASL, IVIM does not need a contrast agent. It is based on the characteristics of the tissue itself. It stimulates and reads the information in voxels successively, and it is mainly sensitive to the increase of incoherent motion in voxel. Therefore, it is not directly affected by the anterior cerebral vascular (e.g., stenosis of internal carotid artery or vertebral artery), or the cardiac output and subjects’ postures. As Henkelman [
The IVIM DWI shows efficacy in differentiating the low grade from high grade gliomas,
The authors declare that they have no conflict of interests.
Yuankai Lin and Jianrui Li contributed equally to this study.