Main Article Content
Abstract
aggressiveness, but grading using conventional MR imaging alone is often unreliable. Proton MR
Spectroscopy (MRS) is a well-established technique for quantifying the brain regional biochemistry
by providing valuable information on the metabolic composition within an area of tissue and
comparing the relative concentration of these metabolites. The aim of this study is to evaluate the
contribution of short and intermediate TE MRS in differentiation of high and low grade gliomas.
Patients and Methods: a prospective cross sectional study conducted on selected patients with
untreated gliomas whom were referred to the radiology department presenting with different
neurological symptoms from April 2018 to February 2019. 1.5 Tesla MRI and MRS were performed
before any interventional procedure. Histopathological diagnosis was obtained and all tumors
enrolled were graded according to the current World Health Organization criteria. The main
metabolites identified by MRS were N-acetyl-aspartate (NAA) at 2.02 ppm, creatine (Cr) at 3.0 ppm,
choline containing compounds (Cho) at 3.2 ppm. The following metabolic ratios were calculated
using standard commercial software: NAA/Cr, Cho/Cr, and Cho/NAA at both short and intermediate
TE.
Results: a total of 22 patients; (12 male and 8 females, age ranged 18–70 years). At intermediate TE,
the difference between high and low grade tumors was statistically significant in Cho metabolite
related ratios (Cho/NAA and Cho/Cr), p-value 0.001 and 0.003 respectively. At short TE, the
difference between high and low grade tumors was statistically significant in Cho metabolite related
ratios (Cho/NAA and Cho/Cr), P <0.001 and 0.01 respectively. On other hand, NAA/Cr ratio was
statistically insignificant in differentiating low and high grade tumors.
Conclusion: MRS is a non-invasive technique that provides an insight into the underlying biological
structure of brain gliomas and in turn improves the diagnostic accuracy. Cho/Cr and Cho/NAA ratios
were the most valuable indicators in assessing the tumor grade.
Keywords
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References
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References
Nelson SJ. Multivoxel magnetic resonance spectroscopy of brain Tumors1. Molecular
cancer therapeutics. 2003 May 1;2(5):497-507.
Law M, Yang S, Wang H, Babb JS, Johnson G, Cha S, Knopp EA, Zagzag D. Glioma
grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR
spectroscopic imaging compared with conventional MR imaging. American Journal of
Neuroradiology. 2003 Nov 1;24(10):1989-98.
Inoue T, Ogasra K, Beppu T, Ogawa A, Kabasawa H. Diffusion tensor imaging for
preoperative evaluation of tumor grade in gliomas. Clinical neurology and neurosurgery. 2005
Apr 1;107(3):174-80.
Barker P, Gillard J, Waldman A. Fundamentals of MR spectroscopy. Clinical MR
Neuroimaging, Diffusion, Perfusion and Spectroscopy. Journal of Neuroradiology.
;34:4553.
Fan G. Magnetic resonance spectroscopy and gliomas. Cancer Imaging. 2006;6(1):113.
Kim JH, Chang KH, Na DG, Song IC, Kwon BJ, Han MH, Kim K. 3T 1H-MR
spectroscopy in grading of cerebral gliomas: comparison of short and intermediate echo time
sequences. American journal of neuroradiology. 2006 Aug 1;27(7):1412-8.
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 Oct 1;49(10):795-803.
Toyooka M, Kimura H, Uematsu H, Kawamura Y, Takeuchi H, Itoh H. Tissue
characterization of glioma by proton magnetic resonance spectroscopy and perfusion-weighted
magnetic resonance imaging: glioma grading and histological correlation. Clinical imaging. 2008
Jul 1;32(4):251-8.
Di Costanzo A, Scarabino T, Trojsi F, Popolizio T, Catapano D, Giannatempo GM, et al.
Proton MR spectroscopy of cerebral gliomas at 3 T: spatial heterogeneity, and tumour grade and
extent. European radiology. 2008 Aug 1;18(8):1727-35.
Arvinda HR, Kesavadas C, Sarma PS, et al. Glioma grading: sensitivity, specificity,
positive and negative predictive values of diffusion and perfusion imaging. J of Neurooncol.
;94(1):87–96.
Soares DP, Law M. Magnetic resonance spectroscopy of the brain: review of metabolites
and clinical applications. Clinical Radiology. 2009;64(1):12–21.
Zou QG, Xu HB, Liu F, Guo W, Kong XC, Wu Y. The assessment of supratentorial
glioma grade: the combined role of multivoxel proton MR spectroscopy and diffusion tensor
imaging. Clinical radiology. 2011 Oct 1;66(10):953-60.
Cianfoni A, Law M, Re TJ, Dubowitz DJ, Rumboldt Z, Imbesi SG. Clinical pitfalls
related to short and long echo times in cerebral MR spectroscopy. Journal of Neuroradiology.
May 1;38(2):69-75.
Liu ZL, Zhou Q, Zeng QS, Li CF, Zhang K. Noninvasive evaluation of cerebral glioma
grade by using diffusion-weighted imaging-guided single-voxel proton magnetic resonance
spectroscopy. Journal of International Medical Research. 2012 Feb;40(1):76-84.
Kousi E, Tsougos I, Tsolaki E, Fountas KN, Theodorou K, Fezoulidis I, Kapsalaki E,
Kappas C. Spectroscopic evaluation of glioma grading at 3T: the combined role of short and long
TE. The Scientific World Journal. 2012;20:12-9.
Verma N, Cowperthwaite MC, Burnett MG, Markey MK. Differentiating tumor
recurrence from treatment necrosis: a review of neuro-oncologic imaging strategies. Neuro
oncology. 2013 Jan 16;15(5):515-34.
Caulo M, Panara V, Tortora D, Mattei PA, Briganti C, Pravatà E, Salice S, Cotroneo AR,
Tartaro A. Data-driven grading of brain gliomas: a multiparametric MR imaging study.
Radiology. 2014 Mar 22;272(2):494-503.
Naser RK, Hassan AA, Shabana AM, Omar NN. Role of magnetic resonance
spectroscopy in grading of primary brain tumors. The Egyptian Journal of Radiology and
Nuclear Medicine. 2016 Jun 1;47(2):577-84.
