Proton magnetic resonance spectroscopy ((1)H MRS) of human brain tumours: assessment of differences between tumour types and its applicability in brain tumour categorization

Eur Radiol. 2003 Mar;13(3):582-91. doi: 10.1007/s00330-002-1547-3. Epub 2002 Aug 2.


Our objective was to evaluate the usefulness of proton magnetic resonance spectroscopy ((1)H MRS) in categorizing brain tumours. In vivo single-voxel (1)H MRS at an echo time of 136 ms was performed in 108 patients with brain neoplasms that included 29 meningiomas (MEN), 15 low-grade astrocytomas (LGA), 12 anaplastic astrocytomas (AA), 25 glioblastomas (GBM) and 27 metastases (MET). Time-domain fitted areas of nine resonances were evaluated in all spectra. Twenty-five additional tumours were prospectively included as independent test set. Differences in at least two resonances were found in all pairwise comparisons of tumour groups except in GBM vs MET. Large lipid resonance at 1.30 ppm was found to be characteristic of GBM and MET, and alanine was characteristic of MEN. Significant differences were found between LGA and AA in choline-containing compounds and total creatine resonances. When implemented in a stepwise algorithm, these findings correctly classified 84% (21 of 25) tumours in the independent test set. Some additional utility was found in glycine/myo-inositol at 3.55 ppm for bilateral differentiation between GBM and MET (9 of 11, 82% correct classification in the test set). (1)H MRS provides useful information to categorize the most common brain tumours that can be implemented in clinical practice with satisfactory results.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Algorithms
  • Astrocytoma / diagnosis
  • Brain Neoplasms / diagnosis*
  • Brain Neoplasms / pathology
  • Cohort Studies
  • Diagnosis, Differential
  • Female
  • Glioblastoma / diagnosis
  • Humans
  • Magnetic Resonance Spectroscopy / methods*
  • Male
  • Meningioma / diagnosis
  • Middle Aged
  • Probability
  • Retrospective Studies
  • Sensitivity and Specificity
  • Severity of Illness Index