title: Accurate classification of childhood brain tumours by in vivo ¹H MRS - a multi-centre study.
abstract: OBJECTIVE
  To evaluate the accuracy of single-voxel Magnetic Resonance Spectroscopy ((1)H MRS) as a non-invasive diagnostic aid for paediatric brain tumours in a multi-national study. Our hypotheses are (1) that automated classification based on (1)H MRS provides an accurate non-invasive diagnosis in multi-centre datasets and (2) using a protocol which increases the metabolite information improves the diagnostic accuracy.
  
  
  METHODS
  Seventy-eight patients under 16 years old with histologically proven brain tumours from 10 international centres were investigated. Discrimination of 29 medulloblastomas, 11 ependymomas and 38 pilocytic astrocytomas (PILOAs) was evaluated. Single-voxel MRS was undertaken prior to diagnosis (1.5 T Point-Resolved Spectroscopy (PRESS), Proton Brain Exam (PROBE) or Stimulated Echo Acquisition Mode (STEAM), echo time (TE) 20-32 ms and 135-136 ms). MRS data were processed using two strategies, determination of metabolite concentrations using TARQUIN software and automatic feature extraction with Peak Integration (PI). Linear Discriminant Analysis (LDA) was applied to this data to produce diagnostic classifiers. An evaluation of the diagnostic accuracy was performed based on resampling to measure the Balanced Accuracy Rate (BAR).
  
  
  RESULTS
  The accuracy of the diagnostic classifiers for discriminating the three tumour types was found to be high (BAR 0.98) when a combination of TE was used. The combination of both TEs significantly improved the classification performance (p<0.01, Tukey's test) compared with the use of one TE alone. Other tumour types were classified accurately as glial or primitive neuroectodermal (BAR 1.00).
  
  
  CONCLUSIONS
  (1)H MRS has excellent accuracy for the non-invasive diagnosis of common childhood brain tumours particularly if the metabolite information is maximised and should become part of routine clinical assessment for these children.
authors.affiliation: IBIME, Universitat Politècnica de València, Spain. javirob@upv.es
authors.forename: Javier
authors.initials: J
authors.lastname: Vicente
authors.forename: Elies
authors.initials: E
authors.lastname: Fuster-Garcia
authors.forename: Salvador
authors.initials: S
authors.lastname: Tortajada
authors.forename: Juan M
authors.initials: JM
authors.lastname: García-Gómez
authors.forename: Nigel
authors.initials: N
authors.lastname: Davies
authors.forename: Kal
authors.initials: K
authors.lastname: Natarajan
authors.forename: Martin
authors.initials: M
authors.lastname: Wilson
authors.forename: Richard G
authors.initials: RG
authors.lastname: Grundy
authors.forename: Pieter
authors.initials: P
authors.lastname: Wesseling
authors.forename: Daniel
authors.initials: D
authors.lastname: Monleón
authors.forename: Bernardo
authors.initials: B
authors.lastname: Celda
authors.forename: Montserrat
authors.initials: M
authors.lastname: Robles
authors.forename: Andrew C
authors.initials: AC
authors.lastname: Peet
mesh_terms: D000293:Adolescent; D001932:Brain Neoplasms / Q000145:classification* / Q000175:diagnosis* / Q000378:metabolism; D002648:Child; D002675:Child, Preschool; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*