Contribution of susceptibility‑ and diffusion‑weighted magnetic resonance imaging for grading gliomas

Xu,Jianxing; Xu,Hai; Zhang,Wei; Zheng,Jiangang

doi:10.3892/etm.2018.6017

Contribution of susceptibility‑ and diffusion‑weighted magnetic resonance imaging for grading gliomas

Authors:
- Jianxing Xu
- Hai Xu
- Wei Zhang
- Jiangang Zheng
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Affiliations: Department of Radiology, Affiliated Wujin Hospital of Jiangsu University, Changzhou, Jiangsu 213002, P.R. China, Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 213002, P.R. China
Published online on: April 2, 2018 https://doi.org/10.3892/etm.2018.6017
Pages: 5113-5118

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Abstract

The aim of the present study was to assess the value of susceptibility‑weighted imaging (SWI) and diffusion‑weighted imaging (DWI) in the grading of gliomas and to evaluate the correlation between these quantitative parameters derived from SWI and DWI. A total of 49 patients with glioma were assessed by DWI and SWI. The evaluation included the ratio of apparent diffuse coefficient values between the solid portion of tumors and contralateral normal white matter (rADC) and the degree of intratumoral susceptibility signal intensity (ITSS) within tumors. Receiver operating characteristic curve (ROC) analyses were performed and the area under the ROC curve was calculated to compare the diagnostic performance, determine optimum thresholds for tumor grading, and calculate the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for identifying high‑grade gliomas. The correlation between DWI‑ and SWI‑derived parameters was also evaluated. The rADC and the degrees of ITSS within tumors were significantly higher in high‑grade gliomas than those in low‑grade gliomas. ROC curve analysis indicated that the rADC was a better index for grading gliomas than the ITSS degree. Statistical analysis demonstrated a threshold value of 1.497 for rADC to provide a sensitivity, specificity, PPV and NPV of 86.2, 85.0, 89.3 and 81.0%, respectively, for determining high‑grade gliomas. A degree of ITSS of 1.5 was defined as the threshold to identify high‑grade gliomas and sensitivity, specificity, PPV and NPV of 82.8, 75.0, 82.8 and 75.0% were obtained, respectively. Furthermore, a moderate inverse correlation between rADC and the ITSS degree was revealed. Combination of SWI with DWI may provide valuable information for glioma grading.

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1	Inoue T, Ogasawara K, Beppu T, Ogawa A and Kabasawa H: Diffusion tensor imaging for preoperative evaluation of tumor grade in gliomas. Clin Neurol Neurosurg. 107:174–180. 2005. View Article : Google Scholar : PubMed/NCBI
2	Yoon JH, Kim JH, Kang WJ, Sohn CH, Choi SH, Yun TJ, Eun Y, Song YS and Chang KH: Grading of cerebral glioma with multiparametric MR imaging and 18F-FDG-PET. Concordance and Accuracy. Eur Radiol. 24:380–389. 2014. View Article : Google Scholar : PubMed/NCBI
3	Van Cauter S, De Keyzer F, Sima DM, Sava AC, D'Arco F, Veraart J, Peeters RR, Leemans A, Van Gool S, Wilms G, et al: Integrating diffusion kurtosis imaging, dynamic susceptibility-weighted contrast-enhanced MRI, and short echo time chemical shift imaging for grading gliomas. Neuro Oncol. 16:1010–1021. 2014. View Article : Google Scholar : PubMed/NCBI
4	Guo AC, Cummings TJ, Dash RC and Provenzale JM: Lymphomas and high-grade astrocytomas: Comparison of water diffusibility and histologic characteristics. Radiology. 224:177–183. 2002. View Article : Google Scholar : PubMed/NCBI
5	Sugahara T, Korogi Y, Kochi M, Ikushima I, Shigematu Y, Hirai T, Okuda T, Liang L, Ge Y, Komohara Y, et al: Usefulness of diffusion-weighted MRI with echo-planar technique in the evaluation of cellularity in gliomas. J Magn Reson Imaging. 9:53–60. 1999. View Article : Google Scholar : PubMed/NCBI
6	Higano S, Yun X, Kumabe T, Watanabe M, Mugikura S, Umetsu A, Sato A, Yamada T and Takahashi S: Malignant astrocytic tumors: Clinical importance of apparent diffusion coefficient in prediction of grade and prognosis. Radiology. 241:839–846. 2006. View Article : Google Scholar : PubMed/NCBI
7	Bulakbasi N, Guvenc I, Onguru O, Erdogan E, Tayfun C and Ucoz T: The added value of the apparent diffusion coefficient calculation to magnetic resonance imaging in the differentiation and grading of malignant brain tumors. J Comput Assist Tomogr. 28:735–746. 2004. View Article : Google Scholar : PubMed/NCBI
8	Kono K, Inoue Y, Nakayama K, Shakudo M, Morino M, Ohata K, Wakasa K and Yamada R: The role of diffusion-weighted imaging in patients with brain tumors. AJNR Am J Neuroradiol. 22:1081–1088. 2001.PubMed/NCBI
9	Lam WW, Poon WS and Metreweli C: Diffusion MR imaging in glioma: Does it have any role in the pre-operation determination of grading of glioma? Clin Radiol. 57:219–225. 2002. View Article : Google Scholar : PubMed/NCBI
10	Arvinda HR, Kesavadas C, Sarma PS, Thomas B, Radhakrishnan VV, Gupta AK, Kapilamoorthy TR and Nair S: Glioma grading: Sensitivity, specificity, positive and negative predictive values of diffusion and perfusion imaging. J NeuroOncol. 94:87–96. 2009. View Article : Google Scholar : PubMed/NCBI
11	Sehgal V, Delproposto Z, Haacke EM, Tong KA, Wycliffe N, Kido DK, Xu Y, Neelavalli J, Haddar D and Reichenbach JR: Clinical applications of neuroimaging with susceptibility-weighted imaging. J Magn Reson Imaging. 22:439–450. 2005. View Article : Google Scholar : PubMed/NCBI
12	Wang XC, Zhang H, Tan Y, Qin JB, Wu XF, Wang L and Zhang L: Combined value of susceptibility-weighted and perfusion-weighted imaging in assessing WHO grade for brain astrocytomas. J Magn Reson Imaging. 39:1569–1574. 2014. View Article : Google Scholar : PubMed/NCBI
13	Di Ieva A, Göd S, Grabner G, Grizzi F, Sherif C, Matula C, Tschabitscher M and Trattnig S: Three-dimensional susceptibility-weighted imaging at 7 T using fractal-based quantitative analysis to grade gliomas. Neuroradiology. 55:35–40. 2013. View Article : Google Scholar : PubMed/NCBI
14	Hori M, Mori H, Aoki S, Abe O, Masumoto T, Kunimatsu S, Ohtomo K, Kabasawa H, Shiraga N and Araki T: Three-dimensional susceptibility-weighted imaging at 3 T using various image analysis methods in the estimation of grading intracranial gliomas. Magn Reson Imaging. 28:594–598. 2010. View Article : Google Scholar : PubMed/NCBI
15	Pinker K, Noebauer-Huhmann IM, Stavrou I, Hoeftberger R, Szomolanyi P, Karanikas G, Weber M, Stadlbauer A, Knosp E, Friedrich K and Trattnig S: High-resolution contrast-enhanced, susceptibility-weighted MR imaging at 3T in patients with brain tumors. correlation with positron-emission tomography and histopathologic findings. AJNR Am J Neuroradiol. 28:1280–1286. 2007. View Article : Google Scholar : PubMed/NCBI
16	Heiss WD, Raab P and Lanfermann H: Multimodality assessment of brain tumors and tumor recurrence. J Nucl Med. 52:1585–1600. 2011. View Article : Google Scholar : PubMed/NCBI
17	Furtner J, Schöpf V, Preusser M, Asenbaum U, Woitek R, Wöhrer A, Hainfellner JA, Wolfsberger S and Prayer D: Non-invasive assessment of intratumoral vascularity using arterial spin labeling: A comparison to susceptibility-weighted imaging for the differentiation of primary cerebral lymphoma and glioblastoma. Eur J Radiol. 83:806–810. 2014. View Article : Google Scholar : PubMed/NCBI
18	Kleihues P, Louis DN, Scheithauer BW, Rorke LB, Reifenberger G, Burger PC and Cavenee WK: The WHO Classification of tumors of the nervous system. J Neuropathol Exp Neurol. 61:215–225. 2002. View Article : Google Scholar : PubMed/NCBI
19	Park MJ, Kim HS, Jahng GH, Ryu CW, Park SM and Kim SY: 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. AJNR Am J Neuroradiol. 30:1402–1408. 2009. View Article : Google Scholar : PubMed/NCBI
20	Castillo M, Smith JK, Kwock L and Wilber K: Apparent diffusion coefficients in the evaluation of high-grade cerebral gliomas. AJNR Am J Neuroradiol. 22:60–64. 2001.PubMed/NCBI
21	Murakami R, Hirai T, Sugahara T, Fukuoka H, Toya R, Nishimura S, Kitajima M, Okuda T, Nakamura H, Oya N, et al: Grading astrocytic tumors by using apparent diffusion coefficient parameters: Superiority of a one- versus two-parameter pilot method. Radiology. 251:838–845. 2009. View Article : Google Scholar : PubMed/NCBI
22	Sadeghi N, D'Haene N, Decaestecker C, Levivier M, Metens T, Maris C, Wikler D, Baleriaux D, Salmon I and Goldman S: Apparent diffusion coefficient and cerebral blood volume in brain gliomas: Relation to tumor cell density and tumor microvessel density based on stereotactic biopsies. AJNR Am J Neuroradiol. 29:476–482. 2008. View Article : Google Scholar : PubMed/NCBI
23	Wu CC, Guo WY, Chen MH, Ho DM, Hung AS and Chung HW: Direct measurement of the signal intensity of diffusion-weighted magnetic resonance imaging for preoperative grading and treatment guidance for brain gliomas. J Chin Med Assoc. 75:581–588. 2012. View Article : Google Scholar : PubMed/NCBI
24	Toyooka M, Kimura H, Uematsu H, Kawamura Y, Takeuchi H and Itoh H: Tissue characterization of glioma by proton magnetic resonance spectroscopy and perfusion-weighted magnetic resonance imaging: Glioma grading and histological correlation. Clin Imaging. 32:251–258. 2008. View Article : Google Scholar : PubMed/NCBI
25	Rauscher A, Sedlacik J, Deistung A, Mentzel HJ and Reichenbach JR: Susceptibility weighted imaging: Data acquisition, image reconstruction and clinical applications. Z Med Phys. 16:240–250. 2006. View Article : Google Scholar : PubMed/NCBI
26	Felix R, Schorner W, Laniado M, Niendorf HP, Claussen C, Fiegler W and Speck U: Brain tumors: MR imaging with gadolinium-DTPA. Radiology. 156:681–688. 1985. View Article : Google Scholar : PubMed/NCBI
27	Kurki T, Lundbom N, Kalimo H and Valtonen S: MR classification of brain gliomas: Value of magnetization transfer and conventional imaging. Magn Reson Imaging. 13:501–511. 1995. View Article : Google Scholar : PubMed/NCBI
28	Scott JN, Brasher PM, Sevick RJ, Rewcastle NB and Forsyth PA: How often are nonenhancing supratentorial gliomas malignant? A population study. Neurology. 59:947–949. 2002. View Article : Google Scholar : PubMed/NCBI