Share：
Share this content in WeChat
X
[Chinese][PDF]134970
• Clinical Article •
The value of SWI and 3D-ASL in grading of gliomas
DU Changyue  MIAO Na  QI Xuhong  DONG Weimin  YU Yang  WEN Zhiyong 

Cite this article as: Du CY, Miao N, Qi XH, et al. The value of SWI and 3D-ASL in grading of gliomas. Chin J Magn Reson Imaging, 2019, 10(9): 645-649. DOI:10.12015/issn.1674-8034.2019.09.002.


[Abstract] Objective: To evaluate the value of susceptibility weighted imaging and three-dimensional arterial spin labeling in identification of gliomas.Materials and Methods: Ninety-two patients with glioma (35 Ⅱ, 13 Ⅲ and 44 Ⅳ) were enrolled. All cases underwent SWI and 3D-ASL scans before operations and were confirmed by postoperative pathology. Intratumoral susceptibility signal intensity (ITSS), the maximal cerebral blood flow value (CBFmax), r1 (CBFmax/unaffected contralateral white matter area CBF1), r2 (CBFmax/unaffected contralateral gray matter area CBF2), r3 (CBFmax/contralateral mirror area normal brain tissue CBF3) were obtained by post-processing. Then did statistical analysis. The value of the ITSS was analyzed by non-parametric Mann-Whitney U test. The values of the 3D-ASL parameters were analyzed by one-way ANOVA. P<0.05 was indicated as the statistically significant difference. Receiver operating characteristic (ROC) curve analysis was used to evaluate the performance of ITSS and 3D-ASL in discriminating between various grades of tumors.Results: The differences of ITSS in (Ⅱ vs. Ⅲ), (Ⅱ vs. Ⅳ) and (Ⅲ vs. Ⅳ) were statistically significant, and higher grades of gliomas showed higher ITSS scores (P<0.05). But the CBFmax, r1, r2 and r3 were statistically significant just in the group of (Ⅱ vs. Ⅳ)(P<0.05). The area under the curve (AUC), sensitivity and specificity of the combination of SWI and 3D-ASL were biggest.Conclusions: By combing SWI and 3D-ASL, the diagnostic efficacy of grading gliomas was greatest than that of a single technique, and SWI was more effective than 3D-ASL.
[Keywords] glioma；neoplasm grading；brain neoplasms；magnetic resonance imaging

DU Changyue Department of Radiology, Capital Medical University Electric Power Teaching Hospital, Beijing 100073, China

MIAO Na Department of Radiology, Capital Medical University Electric Power Teaching Hospital, Beijing 100073, China

QI Xuhong Department of Radiology, Capital Medical University Electric Power Teaching Hospital, Beijing 100073, China

DONG Weimin Department of Radiology, Capital Medical University Electric Power Teaching Hospital, Beijing 100073, China

YU Yang Department of Radiology, Capital Medical University Electric Power Teaching Hospital, Beijing 100073, China

WEN Zhiyong* Department of Radiology, Capital Medical University Electric Power Teaching Hospital, Beijing 100073, China

*Correspondence to: Wen ZY, E-mail: wenzhiyong3329@163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  This article was funded by the Science and Technology Project of State Grid Corporation No. O2017017
Received  2019-01-08
Accepted  2019-06-26
DOI: 10.12015/issn.1674-8034.2019.09.002
Cite this article as: Du CY, Miao N, Qi XH, et al. The value of SWI and 3D-ASL in grading of gliomas. Chin J Magn Reson Imaging, 2019, 10(9): 645-649. DOI:10.12015/issn.1674-8034.2019.09.002.

[1]
Ostrom QT, Bauchet L, Davis FG, et al. The epidemiology of glioma in adults: a "state of the science" review. Neuro Oncol, 2014, 16(7): 896-913.
[2]
Park MJ, Kim HS, Jahng GH, et al. Semi-quantitative assessment of intratumoral susceptibility signals using non-contrast-enhanced high-field high-resolution susceptibility-weighted imaging in patients with gliomas: comparison with MR perfusion imaging. AJNR Am J Neuroradiol, 2009, 30(7): 1402-1408.
[3]
Tietze A, Mouridsen K, Lassen-Ramshad Y, et al. Perfusion MRI derived indices of microvascular shunting and flow control correlate with tumor grade and outcome in patients with cerebral glioma. PloS One, 2015, 10(4): e0123044.
[4]
Hsu CC, Watkins TW, Kwan GN, et al. Susceptibility-weighed imaging of glioma: update on current imaging status and future directions. J Neuroimaging, 2016, 26(4): 383-390.
[5]
Dileva A, Göd S, Grabner G, et al. Three-dimensional susceptibility-weighted imaging at 7 T using fractal-based quantitative analysis to grade gliomas. Neuroradiology, 2013, 55(1): 35-40.
[6]
Xu JX, Xu H, Zhang W, et al. Contribution of susceptibility- and diffusion-weighted magnetic resonance imaging for grading gliomas. Exp Ther Med, 2018, 15(6): 5113-5118.
[7]
Cebeci H, Aydin O, Ozturk-Isik E, et al. Assesment of perfusion in glial tumors with arterial spin labeling;comparison with dynamic susceptibility contrast method. Eur J Radiol, 2014, 83(10): 1914-1919.
[8]
Wang XC, Zhang H, Tan Y, et al. Combined value of susceptibility-weighted and perfusion-weighted imaging in assessing WHO grade for brain astrocytomas. J Magn Reson Imaging, 2014, 39(6): 1569-1574.
[9]
Li XG, Zhu YS, Kang HY, et al. Glioma grading by microvascular permeability parameters derived from dynamic contrast-enhanced MRI and intratumoral susceptibility signal on susceptibility weighted imaging. Cancer Imaging, 2015, 15(1): 4.
[10]
詹茸婷，和鸿，王明磊，等．磁敏感加权成像血管结构半定量评分法对颅内胶质瘤分级的诊断价值．实用放射学杂志, 2014, 30(12): 1958-1961.
[11]
Di NN, Pang HP, Dang XF, et al. Perfusion imaging of brain gliomas using arterial spin labeling: correlation with histopathological vascular density in MRI-guided biopsies. Neuroradiology, 2017, 59(1): 51-59.
[12]
Dangouloff-Ros V, Deroulers C, Foissac F, et al. Arterial spin labeling to predict brain tumor grading in children: correlations between histopathologic vascular density and perfusion MR imaging. Radiology, 2016, 281(2): 553-566.
[13]
Ata ES, Turgut M, Eraslan C, et al. Comparison between dynamic susceptibility contrast magnetic resonance imaging and arterial spin labeling techniques in distinguishing malignant from benign brain tumors. Eur J Radiol, 2016, 85(9): 1545-1553.
[14]
Shen N, Zhao L, Jiang J, et al. Intravoxel incoherent motion diffusion-weighted imaging analysis of diffusion and microperfusion in grading gliomas and comparison with arterial spin labeling for evaluation of tumor perfusion. J Magn Reson Imaging, 2016, 44(3): 620-632.
[15]
Kong L, Chen H, Yang Y, et al. A meta-analysis of arterial spin labelling perfusion values for the prediction of glioma grade. Clin Radiol, 2017, 72(3): 255-261.
[16]
Bai Y, Lin Y, Zhang W, et al. Noninvasive amide proton transfer magnetic resonance imaging in evaluating the grading and cellularity of gliomas. Oncotarget, 2017, 8(4): 5834-5842.
[17]
Whitmore RG, Krejza J, Kapoor GS, et al. Prediction of oligodendroglial tumor subtype and grade using perfusion weighted magnetic resonance imaging. J Neurosurg, 2007, 107(3): 600-609.
[18]
Deibler AR, Pollock JM, Kraft RA, et al. Arerial spin-labeling in routine clinical practice, part 1: technique and artifacts. AJNR Am J Neuroradiol, 2008, 29(7): 1228-1234.

PREV Study of cerebral microstructure in patients with cerebral small vessel disease on intravoxel incoherent motion
NEXT Investigating the changes of ALFF of hearing related cortex of infants with sensorineural hearing loss by using fMRI
  


LINK


Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn