title: [The contribution of magnetic resonance spectroscopy to the classification of high grade gliomas. The predictive value of macromolecules].
abstract: BACKGROUND
  1H MRS allows the study of metabolite concentration changes in intracranial tumours, relating them, more or less successfully, to the histological type and grade of the tumour.
  
  
  OBJECTIVE
  To analyse the patterns which are useful for classifying the grades of cerebral gliomas by means of various ratios obtained using 1H MRS with two echo times (ET), with and without water suppression, paying special attention to the macromolecules.
  
  
  METHODS
  We studied 8 gliomas (1 grade II, 2 grade III and 5 grade IV) with single volume 1H MRS at ET 31 ms (8/8) and 136 ms (7/8). The intensities of the metabolites, including macromolecules (MMA, 0.9 ppm; MMB, 1.3 ppm), were normalised to water signal intensity for ET 31, to Cr at ET 31 and 136 ms and NAA/Cho for both ET and the ratio MMA/MMB at ET 31.
  
  
  RESULTS
  There were significant differences between the three grades on the ratios MMA/MMB (p= 0.000) with descent of the MMA/MMB coefficient as the grade increases, and NNA/Cho at ET 136 (p= 0.018). We found an inverse relationship between the quantity in mI and the increase in grade. No macromolecules were found at ET 136 in any of the tumours of grade II or III.
  
  
  CONCLUSIONS
  The spectra of gliomas with ET 31 showed macromolecules around 0.9 and 1.3 ppm with different relative ratios for each tumour grade. The ET 136 spectra informs about the content of NNA and Cho. Apart from the increase in MMB (0.9 ppm), with short ET the higher grades showed lower content of mI. The study of gliomas using 1H MRS with ET 31 and 136 ms contributes to the diagnosis of the grade of tumour.
authors.affiliation: Departamento de Quimica-Fisica; Universidad de Valencia. Facultad de Psicologia, Valencia, 46010, Espańa. Carmen.Martinez-Bisbal@uv.es
authors.forename: M C
authors.initials: MC
authors.lastname: Martínez-Bisbal
authors.forename: B
authors.initials: B
authors.lastname: Celda-Muñoz
authors.forename: L
authors.initials: L
authors.lastname: Martí-Bonmatí
authors.forename: P
authors.initials: P
authors.lastname: Ferrer-Ripollés
authors.forename: A J
authors.initials: AJ
authors.lastname: Revert-Ventura
authors.forename: J
authors.initials: J
authors.lastname: Piquer-Belloch
authors.forename: E
authors.initials: E
authors.lastname: Mollá-Olmos
authors.forename: E
authors.initials: E
authors.lastname: Arana-Fernández de Moya
authors.forename: R
authors.initials: R
authors.lastname: Dosdá-Muñoz
mesh_terms: D000328:Adult; D000368:Aged; D001932:Brain Neoplasms / Q000145:classification* / Q000175:diagnosis*; D005260:Female; D005910:Glioma / Q000145:classification* / Q000175:diagnosis*; D006801:Humans; D046911:Macromolecular Substances; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests
chemical_list: D046911:Macromolecular Substances