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• Clinical Article •
Application of multimodal magnetic resonance imaging in the evaluation of gliomas
LIN Kun  CIDAN Wang-jiu  QI Ying  WANG Xiao-ming 

DOI:10.12015/issn.1674-8034.2018.01.004.


[Abstract] Objective: To investigate the application of multimodal magnetic resonance imaging in the diagnosis and grading of gliomas.Materials and Methods: Thirty patients of glioma with pathological and immune-histochemical confirmation, who underwent conventional and functional MRI were retrospectively enrolled in the study. Tumor enhancement, peritumoral edema, signal intensity of diffusion weighted imaging (DWI), intratumoral susceptibility signal intensity (ITSS) in susceptibility weighted imaging (SWI), perfusion in arterial spin labeling (ASL) and state of fiber bundles were compared in high grade gliomas and low grade gliomas. Fractional anisotropy (FA) value and apparent diffusion coefficient (ADC) value in diffusion tensor imaging (DTI) as well as choline (Cho) /creatine (Cr), N-acetyl aspartic acid (NAA)/Cr and Cho/NAA in 1H MR spectroscopy (MRS) were measured and calculated. The differences of all the above indexes in the two groups were statistically analyzed.Results: There were 15 HGG and 15 LGG. Peritumoral edema, ASL perfusion, fiber bundles state, ADC value and Cho/Cr, NAA/Cr, Cho/NAA between the two groups were significantly different (P <0.05). Tumor enhancement, DWI signal intensity, ITSS and FA value were not significantly different (P>0.05). The area under curve (AUC) of ASL perfusion, fiber bundle status, ITSS, ADC, Cho/Cr, NAA/Cr, Cho/NAA and FA were 0.889, 0.833, 0.778, 0.972, 0.972, 1.000, 1.000 and 0.486, respectively. The combined AUC of peritumoral edema, tumor enhancement and DWI signal intensity was 0.796.Conclusions: Multimodal MRI can provide comprehensive information of glioma, which plays a significant role in accurate diagnosis.
[Keywords] Glioma；Multimodal imaging；Magnetic resonance imaging；Diagnosis

LIN Kun Department of Radiology, Shengjing Hospital, China Medical University, Shenyang 110004, China

CIDAN Wang-jiu Department of Radiology, People's Hospital of Tibet Autonomous Region, Lhasa 850000, China

QI Ying Department of Radiology, Shengjing Hospital, China Medical University, Shenyang 110004, China

WANG Xiao-ming* Department of Radiology, Shengjing Hospital, China Medical University, Shenyang 110004, China

*Correspondence to: Wang XM, E-mail: wangxm024@163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  Clinical Capability Construction Project for Liaoning Provincial Hospitals No. LNCCC-B06-2014 Outstanding Scientific Fund of Shengjing Hospital No. 2014-02
Received  2017-09-11
Accepted  2017-11-20
DOI: 10.12015/issn.1674-8034.2018.01.004
DOI:10.12015/issn.1674-8034.2018.01.004.

[1]
Stylli SS, Luwor RB, Ware TM, et al. Mouse models of glioma. J Clin Neurosci, 2015, 22(4): 619-626.
[2]
Louis DN, Perry A, Reifenberger G, et al. The 2016 World Health Organization classification of tumors of the central nervous system: a summary. Acta Neuropathol, 2016, 131(6): 803-820.
[3]
Inamura T, Nishio S, Takeshita I, et al. Peritumoral brain edema in meningiomas-influence of vascular supply on its development. Neurosurgery, 1992, 31(2): 179-185.
[4]
Park MJ, Kim HS, Jahng GH, et al. Semiquantitative 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. Am J Neuroradiol, 2009, 30(7): 1402-1408.
[5]
Arevalo-Perez J, Peck KK, Young RJ, et al. Dynamic contrast-enhanced perfusion mri and diffusion-weighted imaging in grading of gliomas. J Neuroimaging, 2015, 25(5): 792-798.
[6]
Aghi MK, Nahed BV, Sloan AE, et al. The role ofsurgery in the management of patients with diffuse low grade glioma: a systematic review and evidence-based clinical practice guideline. J Neurooncol, 2015, 125(3): 503-530.
[7]
Cuccarini V, Erbetta A, Farinotti M, et al. Advanced MRI may complement histological diagnosis of lower grade gliomas and help in predicting survival. J Neurooncol, 2016, 126(2): 279-288.
[8]
Gatidis S, Schmidt H, Martirosian P, et al. Apparent diffusion coefficient-dependent voxel-wise computed diffusion-weighted imaging: an approach for improving SNR and reducing T2 shine-through effects. J Magn Reson Imaging, 2016, 43(4): 824-832.
[9]
Ferda J, Kastner J, Mukensnabl P, et al. Diffusion tensor magnetic resonance imaging of glial brain tumors. Eur J Radiol, 2010, 74(3): 428-436.
[10]
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.
[11]
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.
[12]
Li C, Ai B, Li Y, et al. Susceptibility-weighted imaging in grading brain astrocytomas. Eur J Radiol, 2010, 75(1): 81-85.
[13]
Grabner G, Kiesel B, Wöhrer A, et al. Local image variance of 7 Tesla SWI is a new technique for preoperative characterization of diffusely infiltrating gliomas: correlation with tumour grade and IDH1 mutational status. Eur Radiol, 2017, 27(4): 1556-1567.
[14]
Wang Q, Zhang H, Zhang J, et al. The diagnostic performance of magnetic resonance spectroscopy in differentiating high-from low-grade gliomas: a systematic review and meta-analysis. Eur Radiol, 2016, 26(8): 2670-2684.
[15]
Fudaba H, Shimomura T, Abe T, et al. Comparison of multiple parameters obtained on 3 T pulsed arterial spin-labeling, diffusion tensor imaging, and MRS and the Ki-67 labeling index in evaluating glioma grading. AJNR Am J Neuroradiol, 2014, 35(11): 2091-2098.
[16]
Shang HB, Zhao WG, Zhang WF. Preoperative assessment using multimodal functional magnetic resonance imaging techniques in patients with brain gliomas. Turk Neurosurg, 2012, 22(5): 558-565.
[17]
Fouke SJ, Benzinger T, Gibson D, et al. The role of imaging in the management of adults with diffuse low grade glioma: a systematic review and evidence-based clinical practice guideline. J Neurooncol, 2015, 125(3): 457-479.
[18]
Caulo M, Panara V, Tortora D, et al. Data-driven grading of brain gliomas: a multi-parametric MR imaging study. Radiology, 2014, 272(2): 494-503.
[19]
Park SM, Kim HS, Jahng GH, et al. Combination of high-resolution susceptibility-weighted imaging and the apparent diffusion coefficient: added value to brain tumour imaging and clinical feasibility of non-contrast MRI at 3T. Br J Radiol, 2010, 83(990): 466-475.

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