Differentiation of Low-Grade and High-Grade Glioma Using the Combination of Conventional Magnetic Resonance Imaging and Apparent Diffusion Coefficient Value

Rahmad Mulyadi, Mochammad Hatta, Andi Asadul Islam, Bachtiar Murtala, Jumraini Tammase, Reninda Ananda Aman, Eka Susanto

Abstract


BACKGROUND: The conventional magnetic resonance imaging (cMRI) and apparent diffusion coefficient (ADC) may have a role in predicting tumor grade for gliomas and may in turn assist in identifying tumor biopsy sites. In this study, we aimed to determine the added value of a joint approach of diffusion-weighted imaging (DWI) and cMRI to determine of low grade and high-grade glioma, compare to cMRI alone.

METHODS: Data were collected from 56 glioma patients, who underwent examinations and received treatment at Cipto Mangunkusumo National Central General Hospital, Jakarta, Indonesia, from the period of 2015–2018. Inclusion criteria was patients who underwent cMRI with a DWIADC sequence and patient that were diagnosed with glioma according to the histopathological results. Pathology reports of the imaging results were reviewed independently. A receiver operator curve (ROC) analysis assessed the predictive potential of cMRI and ADC values for low-grade and high-grade gliomas.

RESULTS: Fifty-six subjects met the inclusion criteria. The combination of MRI and ADC values increased sensitivity (to 90%) and negative predictive value (to 92.9%), and also improved the negative likelihood ratio (to 0.14). However, the combination of MRI and ADC values had the highest area under the curve (78.6%) and sensitivity (78.6%), which was similar to the separated examination.

CONCLUSION: The combination of ADC value and conventional MRI increases sensitivity in differentiating low-grade and high-grade glioma compared to separated examination.

KEYWORDS: glioma, conventional MRI, ADC value


Full Text:

PDF

References


Forst DA, Nahed BV, Loeffler JS, Batchelor TT. Low-grade gliomas. Oncologist. 2014; 19: 403-13, CrossRef.

Ostrom QT, Gittleman H, Truitt G, Boscia A, Kruchko C, Barnholtz-Sloan JS. CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2011–2015. Neuro Oncol. 2018; 20 (Suppl 4): iv1--iv86, CrossRef.

Law M, Yang S, Babb JS, Knopp EA, Golfinos JG, Zagzag D, et al. Comparison of cerebral blood volume and vascular permeability from dynamic susceptibility contrast-enhanced perfusion MR imaging with glioma grade. Am J Neuroradiol. 2004; 25: 746-55, PMID.

Lee EJ, Lee SK, Agid R, Bae JM, Keller A, Terbrugge K. Preoperative grading of presumptive low-grade astrocytomas on MR imaging: diagnostic value of minimum apparent diffusion coefficient. AJNR Am J Neuroradiol. 2008; 29: 1872-7, CrossRef.

Ahmed R, Oborski MJ, Hwang M, Lieberman FS, Mountz JM. Malignant gliomas: current perspectives in diagnosis, treatment, and early response assessment using advanced quantitative imaging methods. Cancer Manag Res. 2014; 6: 149-70, CrossRef.

Rees JH. Diagnosis and treatment in neuro-oncology: an oncological perspective. Br J Radiol. 2011; 84 (Special Issue 2): S82-9, CrossRef.

Darbar A, Waqas M, Enam SF, Mahmood SD. Use of preoperative apparent diffusion coefficients to predict brain tumor grade. Cureus. 2018; 10: e2284, CrossRef.

Guzmán-De-Villoria JA, Mateos-Pérez JM, Fernández-García P, Castro E, Desco M. Added value of advanced over conventional magnetic resonance imaging in grading gliomas and other primary brain tumors. Cancer Imaging. 2014; 14(1): 35, CrossRef.

Bulakbasi N, Guvenc II, Onguru O, Erdogan E, Tayfun C, Ucoz T. The added value of the apparent diffusion coefficient calculation to magnetic resonance imaging in the differentiation and grading of malignant brain tumors. Neuro. 2004; 28: 735-46, CrossRef.

Nick Bryan R. Introduction: Imaging the brain and its diseases. In: Gillard JH, Waldman AD, Barker PB, editors. Clinical MR Neuroimaging: Physiological and Functional Techniques. 2nd ed. Cambridge: Cambridge University Press; 2010. p.1-4, CrossRef.

Baig MA, Klein JP, Mechtler LL. Imaging of brain tumors. Contin Lifelong Learn Neurol. 2016; 22: 1529-52, CrossRef.

Bulakbasi N, Kocaoglu M, Örs F, Tayfun C, Ügöz T. Combination of single-voxel proton MR spectroscopy and apparent diffusion coefficient calculation in the evaluation of common brain tumors. Am J Neuroradiol. 2003; 24: 225-33, PMID.

Kang Y, Choi SH, Kim YJ, Kim KG, Sohn CH, Kim JH, et al. Gliomas: Histogram analysis of apparent diffusion coefficient maps with standard- or high-b-value diffusion-weighted MR imaging--correlation with tumor grade. Radiology. 2011; 261: 882-90, CrossRef.

Komori T. The 2016 WHO classification of tumours of the central nervous system: The major points of revision. Neurol Med Chir. 2017; 57: 301-11, CrossRef.

Law M, Yang S, Wang H, Babb JS, Johnson G, Cha S, et al. Glioma grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging. AJNR Am J Neuroradiol. 2003; 24: 1989-98, PMID.

Zhang L, Min Z, Tang M, Chen S, Lei X, Zhang X. The utility of diffusion MRI with quantitative ADC measurements for differentiating high-grade from low-grade cerebral gliomas: Evidence from a meta-analysis. J Neurol Sci. 2017; 373: 9-15, CrossRef.

Mahdiyeh S, Fariborz F, Hossein G, Mojtaba M, Ayoob R, Soheilah K, et al. Grading of glioma tumors by analysis of minimum apparent diffusion coefficient and maximum relative cerebral blood volume. Casp J Neurol Sci. 2017; 2(4): 42-53, article.

Murakami R, Hirai T, Kitajima M, Fukuoka H, Toya R, Nakamura H, et al. Magnetic resonance imaging of pilocytic astrocytomas: usefulness of the minimum apparent diffusion coefficient (ADC) value for differentiation from high-grade gliomas. Acta radiol. 2008; 49: 462-7, CrossRef.

Hilario A, Ramos A, Perez-Nuñez A, Salvador E, Millan JM, Lagares A, et al. The added value of apparent diffusion coefficient to cerebral blood volume in the preoperative grading of diffuse gliomas. Am J Neuroradiol. 2012; 33: 701-7, CrossRef.

Zonari P, Baraldi P, Crisi G. Multimodal MRI in the characterization of glial neoplasms: the combined role of single-voxel MR spectroscopy, diffusion imaging and echo-planar perfusion imaging. Neuroradiology. 2007; 49: 795-803, CrossRef.




DOI: https://doi.org/10.18585/inabj.v12i1.996

Indexed by:

                 

                  

               

     

 

The Prodia Education and Research Institute