Application of Multivoxel 1H-Magnetic Resonance Spectroscopy in the Grading of Cerebral Glioma

Document Type : Original Paper


1 medical physics, medical faculty mashhad university of medical science mashhad iran

2 Department of medical physics, Medicine Faculty, Mashhad University of Medical sciences, Mashhad, Iran

3 Department of medical imaging, Medicine Faculty, Shahid Beheshti University of Medical Sciences, Tehran, Iran


Introduction: Gliomas represent a considerable percentage of all diagnosed primary central nervous system tumors. A non-invasive access method, like magnetic resonance spectroscopy (MRS), is required for preoperative evaluation. So, the present study aimed to evaluate the application of Multivoxel 1H-MR Spectroscopy in the differentiation of high-grade from low-grade gliomas.
Material and Methods: 13 patients suspected of Cerebral Glioma, which already had been selected for brain surgery or biopsy, underwent a Multivoxel 1H-MR Spectroscopy. After the MRS exam, the pathology tests on specimens confirmed the grade of tumors. Then results were compared and represented as receiver operating characteristic (ROC) curves to show their sensitivity and specificity as well.
Results: Choline to creatine (Cho/Cr) and choline to N-acetyl-aspartate (Cho/NAA) were statistically lower in the low-grade group than in high-grade (p=0.007 and p=0.027, respectively) and N-acetyl-aspartate to creatine (NAA/Cr) was statistically higher in the high-grade group (p=0.037). But in border regions, only Cho/Cr and Cho/NAA were significant (P values= 0.19 and 0.22, respectively). With receiver operating characteristic (ROC) curves analysis, Cho/Cr had the best sensitivity and specificity in the differentiation of high-grade from low-grade gliomas in tumor area (92.86% sensitivity and 85.71% specificity) and this ratio had the best sensitivity and specificity in border regions of tumor (92.86% sensitivity and 78.43% specificity).
Conclusion: Metabolite ratios of low and high-grade gliomas (HGG) were significantly different from each other. Cho/Cr and Cho/NAA ratios can use as an internal reference for grading the glioma non-invasively in the tumor area and the border area of the tumor.


Main Subjects

  1. Kocarnik JM, Compton K, Dean FE, Fu W, Gaw BL, Harvey JD, et al. Cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life years for 29 cancer groups from 2010 to 2019: a systematic analysis for the global burden of disease study 2019. JAMA oncology. 2022 Mar 1;8(3):420-44.
  2. Behin A, Hoang-Xuan K, Carpentier AF, Delattre JY. Primary brain tumours in adults. The Lancet. 2003 Jan 25;361(9354):323-31.
  3. Xia Y, Yang C, Hu N, Yang Z, He X, Li T, et al. Exploring the key genes and signaling transduction pathways related to the survival time of glioblastoma multiforme patients by a novel survival analysis model. BMC genomics. 2017 Jan;18(1):1-1.
  4. Auer TA. Advanced MR techniques in glioblastoma imaging—upcoming challenges and how to face them. European Radiology. 2021 Sep;31(9):6652-4.
  5. Eckel-Passow JE, Lachance DH, Molinaro AM, Walsh KM, Decker PA, Sicotte H, et al. Glioma groups based on 1p/19q, IDH, and TERT promoter mutations in tumors. New England Journal of Medicine. 2015 Jun 25;372(26):2499-508.
  6. Chao B, Jiang F, Bai H, Meng P, Wang L, Wang F. Predicting the prognosis of glioma by pyroptosis‐related signature. Journal of cellular and molecular medicine. 2022 Jan;26(1):133-43.
  7. Louis DN, Ohgaki H, Wiestler OD, Cavenee WK, Burger PC, Jouvet A, Scheithauer BW, Kleihues P. The 2007 WHO classification of tumours of the central nervous system. Acta neuropathologica. 2007 Aug;114:97-109.
  8. Rees JH, Smirniotopoulos JG, Jones RV, Wong K. Glioblastoma multiforme: radiologic-pathologic correlation. Radiographics. 1996 Nov;16(6):1413-38.
  9. Scott JN, Brasher PM, Sevick RJ, Rewcastle NB, Forsyth PA. How often are nonenhancing supratentorial gliomas malignant? A population study. Neurology. 2002 Sep 24;59(6):947-9.
  10. Faramarzi A, Allahverdy A, Amiri M, Siyah Mansoory M. Detection of Glioblastoma Multiforme Tumor in Magnetic Resonance Spectroscopy Based on Support Vector Machine. Iranian Journal of Medical Physics. 2018 Dec 1;15(Special Issue-12th. Iranian Congress of Medical Physics):278-.
  11. Knopp EA, Cha S, Johnson G, Mazumdar A, Golfinos JG, Zagzag D, et al. Glial neoplasms: dynamic contrast-enhanced T2*-weighted MR imaging. Radiology. 1999 Jun;211(3):791-8.
  12. Al-Okaili RN, Krejza J, Woo JH, Wolf RL, O'Rourke DM, Judy KD, et al. Intraaxial brain masses: MR imaging–based diagnostic strategy—initial experience. Radiology. 2007 May;243(2):539-50.
  13. Dean BL, Drayer BP, Bird CR, Flom RA, Hodak JA, Coons SW, et al. Gliomas: classification with MR imaging. Radiology. 1990 Feb;174(2):411-5.
  14. Watanabe M, Tanaka R, Takeda N. Magnetic resonance imaging and histopathology of cerebral gliomas. Neuroradiology. 1992 Nov;34:463-9.
  15. Rudnay M, Waczulikova I, Bullova A, Rjaskova G, Chorvath M, Jezberova M, et al. Magnetic resonance spectroscopy-its added value in brain glioma multiparametric assessment. Bratislavske Lekarske Listy. 2021 Jan 1;122(10):708-14.
  16. Al-Okaili RN, Krejza J, Woo JH, Wolf RL, O'Rourke DM, Judy KD, et al. Intraaxial brain masses: MR imaging–based diagnostic strategy—initial experience. Radiology. 2007 May;243(2):539-50.
  17. Kim JH, Chang KH, Na DG, Song IC, Kwon BJ, Han MH, et al. 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.
  18. 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. American journal of neuroradiology. 2003 Nov 1;24(10):1989-98.
  19. Li BS, Babb JS, Soher BJ, Maudsley AA, Gonen O. Reproducibility of 3D proton spectroscopy in the human brain. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine. 2002 Mar;47(3):439-46.
  20. Möller-Hartmann W, Herminghaus S, Krings T, Marquardt G, Lanfermann H, Pilatus U, et al. Clinical application of proton magnetic resonance spectroscopy in the diagnosis of intracranial mass lesions. Neuroradiology. 2002 May;44(5):371-81.
  21. Mader I, Rauer S, Gall P, Klose U. 1H MR spectroscopy of inflammation, infection and ischemia of the brain. European journal of radiology. 2008 Aug 1;67(2):250-7.
  22. Durmo F, Rydelius A, Baena SC, Askaner K, Lätt J, Bengzon J, et al. Multivoxel 1H-MR spectroscopy biometrics for preoprerative differentiation between brain tumors. Tomography. 2018 Dec;4(4):172-81.
  23. Ishimaru H, Morikawa M, Iwanaga S, Kaminogo M, Ochi M, Hayashi K. Differentiation between high-grade glioma and metastatic brain tumor using single-voxel proton MR spectroscopy. European radiology. 2001 Sep;11:1784-91.
  24. Hamsini BC, Reddy BN, Neelakantan S, Kumaran SP. Clinical application of MR spectroscopy in identifying biochemical composition of the intracranial pathologies. GABA And Glutamate–New Developments In Neurotransmission Research. 2018 Mar 21.
  25. Inglese M, Rusinek H, George IC, Babb JS, Grossman RI, Gonen O. Global average gray and white matter N-acetylaspartate concentration in the human brain. Neuroimage. 2008 Jun 1;41(2):270-6.
  26. Clark JB. N-acetyl aspartate: a marker for neuronal loss or mitochondrial dysfunction. Developmental neuroscience. 1998 Jul 1;20(4-5):271.
  27. Yerli H, Agildere AM, Özen Ö, Geyik E, Atalay B, Elhan AH. Evaluation of cerebral glioma grade by using normal side creatine as an internal reference in multi-voxel 1H-MR spectroscopy. Diagnostic and interventional radiology. 2007 Mar 1;13(1):3.
  28. Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. 1982 Apr;143(1):29-36.
  29. Zeng Q, Liu H, Zhang K, Li C, Zhou G. Noninvasive evaluation of cerebral glioma grade by using multivoxel 3D proton MR spectroscopy. Magnetic resonance imaging. 2011 Jan 1;29(1):25-31.
  30. Rock JP, Hearshen D, Scarpace L, Croteau D, Gutierrez J, Fisher JL, et al. Correlations between magnetic resonance spectroscopy and image-guided histopathology, with special attention to radiation necrosis. Neurosurgery. 2002 Oct 1;51(4):912-20.
  31. Negendank WG, Sauter R, Brown TR, Evelhoch JL, Falini A, Gotsis ED, et al. Proton magnetic resonance spectroscopy in patients with glial tumors: a multicenter study. Journal of neurosurgery. 1996 Mar 1;84(3):449-58.
  32. Vamvakas A, Williams SC, Theodorou K, Kapsalaki E, Fountas K, Kappas C, et al. Imaging biomarker analysis of advanced multiparametric MRI for glioma grading. Physica Medica. 2019 Apr 1;60:188-98.
  33. 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.