Role of diffusion and perfusion magnetic resonance imaging in predicting the histopathological grade of gliomas - A prospective study

 

 Permissions and Reprints

Context: Gliomas are the most common brain tumors. In addition to conventional magnetic resonance imaging (MRI) techniques, a variety of new techniques offers more than the anatomic information. The new MRI techniques include perfusion-weighted imaging (PWI) and diffusion-weighted imaging (DWI). Aims: The aim of this study is to assess the sensitivity, specificity, predictive value, and accuracy of diffusion- and perfusion-weighted MRI in the preoperative grading of gliomas. Setting/Design: The study was conducted in the Department of Neurosurgery, Pathology, and Radiodiagnosis, Sher-e-Kashmir Institute of Medical Sciences, Kashmir, India, which is the only tertiary care neurosurgical center in the state. It was a prospective study. Patients and Methods: Thirty-one consecutive patients with gliomas were included in the study. All the patients were evaluated by a standard conventional contrast-enhanced study on Siemens 1.5 Tesla MRI. In addition to the standard MRI, diffusion- and perfusion-weighted MRI were also performed. The histopathological grading of the tumor was done as per the WHO classification of 2007. The sensitivity, specificity, predictive value, and accuracy of diffusion- and perfusion-weighted MRI in determining tumor grade were calculated. Comparison was done between PWI, DWI findings, and WHO histopathological grading. Analysis Method: The statistical analysis was done using the Statistical Package for the Social Sciences, and receiver operating characteristic curves were used to estimate sensitivity, specificity, and accuracy. Results: The overall sensitivity of PWI (with regional cerebral blood volume cutoff of 1.7) in the preoperative assessment of high-grade gliomas was 82.6% and specificity was 75%, the positive predictive value (PPV) was 90.48%, and the negative predictive value (NPV) was 60%. The overall accuracy was 80.65%. In case of DWI, the sensitivity was 69.57% and the specificity was 75%, and the PPV and NPVs were 88.8% and 46.15%, respectively. The overall accuracy was 71%. Conclusion: Our results clearly show higher accuracy of diffusion- and perfusion-weighted MRI in assessment of glioma grade as compared to conventional MRI. This information can prove very useful for the operating neurosurgeon in preoperative assessment and surgical planning. Postoperatively, the neuropathologist can also benefit from such information.

Financial support and sponsorship

Nil.

Publication History

Article published online:
09 September 2022

© 2019. Asian Congress of Neurological Surgeons. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Thieme Medical and Scientific Publishers Pvt. Ltd.
A-12, 2nd Floor, Sector 2, Noida-201301 UP, India

• References

• 1 Young GS. Advanced MRI of adult brain tumors. Neurol Clin 2007;25:947-73, viii.
• 2 Seo HS, Chang KH, Na DG, Kwon BJ, Lee DH. High b-value diffusion (b = 3000 s/mm2) MR imaging in cerebral gliomas at 3T: Visual and quantitative comparisons with b = 1000 s/mm2. AJNR Am J Neuroradiol 2008;29:458-63.
• 3 Louis DN, Ohgaki H, Wiestler OD, Cavenee WK, Burger PC, Jouvet A, et al. The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol 2007;114:97-109.
• 4 Weber MA, Zoubaa S, Schlieter M, Jüttler E, Huttner HB, Geletneky K, et al. Diagnostic performance of spectroscopic and perfusion MRI for distinction of brain tumors. Neurology 2006;66:1899-906.
• 5 Chishty IA, Rafique MZ, Hussain M, Akhtar W, Ahmad MN, Sajjad Z, et al. MRI characterization and histopathological correlation of primary intra-axial brain glioma. J Liaquat Univ Med Health Sci 2010;9:64-9.
• 6 Stadnik TW, Chaskis C, Michotte A, Shabana WM, van Rompaey K, Luypaert R, et al. Diffusion-weighted MR imaging of intracerebral masses: Comparison with conventional MR imaging and histologic findings. AJNR Am J Neuroradiol 2001;22:969-76.
• 7 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.
• 8 Lev MH, Ozsunar Y, Henson JW, Rasheed AA, Barest GD, Harsh GR 4th, et al. Glial tumor grading and outcome prediction using dynamic spin-echo MR susceptibility mapping compared with conventional contrast-enhanced MR: Confounding effect of elevated rCBV of oligodendrogliomas. AJNR Am J Neuroradiol 2004;25:214-21.
• 9 Bulakbasi N, Kocaoglu M, Farzaliyev A, Tayfun C, Ucoz T, Somuncu I. Assessment of diagnostic accuracy of perfusion MR imaging in primary and metastatic solitary malignant brain tumors. AJNR Am J Neuroradiol 2005;26:2187-99.
• 10 Shin JH, Lee HK, Kwun BD, Kim JS, Kang W, Choi CG, et al. Using relative cerebral blood flow and volume to evaluate the histopathologic grade of cerebral gliomas: Preliminary results. AJR Am J Roentgenol 2002;179:783-9.
• 11 Liu X, Tian W, Kolar B, Yeaney GA, Qiu X, Johnson MD, et al. MR diffusion tensor and perfusion-weighted imaging in preoperative grading of supratentorial nonenhancing gliomas. Neuro Oncol 2011;13:447-55.
• 12 Fan GG, Deng QL, Wu ZH, Guo QY. Usefulness of diffusion/perfusion-weighted MRI in patients with non-enhancing supratentorial brain gliomas: A valuable tool to predict tumour grading? Br J Radiol 2006;79:652-8.
• 13 Castillo M, Smith JK, Kwock L, Wilber K. Apparent diffusion coefficients in the evaluation of high-grade cerebral gliomas. AJNR Am J Neuroradiol 2001;22:60-4.
• 14 Tien RD, Felsberg GJ, Friedman H, Brown M, MacFall J. MR imaging of high-grade cerebral gliomas: Value of diffusion-weighted echoplanar pulse sequences. AJR Am J Roentgenol 1994;162:671-7.