title: Discrimination of paediatric brain tumours using apparent diffusion coefficient histograms.
abstract: OBJECTIVE
  To determine if histograms of apparent diffusion coefficients (ADC) can be used to differentiate paediatric brain tumours.
  
  
  METHODS
  Imaging of histologically confirmed tumours with pre-operative ADC maps were reviewed (54 cases, 32 male, mean age 6.1 years; range 0.1-15.8 years) comprising 6 groups. Whole tumour ADC histograms were calculated; normalised for volume. Stepwise logistic regression analysis was used to differentiate tumour types using histogram metrics, initially for all groups and then for specific subsets.
  
  
  RESULTS
  All 6 groups (5 dysembryoplastic neuroectodermal tumours, 22 primitive neuroectodermal tumours (PNET), 5 ependymomas, 7 choroid plexus papillomas, 4 atypical teratoid rhabdoid tumours (ATRT) and 9 juvenile pilocytic astrocytomas (JPA)) were compared. 74% (40/54) were correctly classified using logistic regression of ADC histogram parameters. In the analysis of posterior fossa tumours, 80% of ependymomas, 100% of astrocytomas and 94% of PNET-medulloblastoma were classified correctly. All PNETs were discriminated from ATRTs (22 PNET and 4 supratentorial ATRTs) (100%).
  
  
  CONCLUSIONS
  ADC histograms are useful in differentiating paediatric brain tumours, in particular, the common posterior fossa tumours of childhood. PNETs were differentiated from supratentorial ATRTs, in all cases, which has important implications in terms of clinical management. Key Points • MR based apparent diffusion coefficient histograms can help differentiate paediatric brain tumours • ADC histogram parameters correctly classified the great majority of posterior fossa tumours.
authors.affiliation: Imaging and Biophysics Unit, UCL Institute of Child Health, 30 Guilford Street, London, WC1N 1EH, UK.
authors.forename: Jonathan G
authors.initials: JG
authors.lastname: Bull
authors.forename: Dawn E
authors.initials: DE
authors.lastname: Saunders
authors.forename: Christopher A
authors.initials: CA
authors.lastname: Clark
mesh_terms: D000293:Adolescent; D001254:Astrocytoma / Q000175:diagnosis* / Q000473:pathology; D001932:Brain Neoplasms / Q000175:diagnosis* / Q000473:pathology*; D002648:Child; D002675:Child, Preschool; D004058:Diffusion; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D004806:Ependymoma / Q000175:diagnosis* / Q000473:pathology; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008495:Medical Oncology / Q000379:methods*; D008527:Medulloblastoma / Q000175:diagnosis / Q000473:pathology; D018242:Neuroectodermal Tumors, Primitive / Q000175:diagnosis* / Q000473:pathology; D020288:Papilloma, Choroid Plexus / Q000175:diagnosis* / Q000473:pathology; D012044:Regression Analysis; D012189:Retrospective Studies; D018335:Rhabdoid Tumor / Q000175:diagnosis* / Q000473:pathology