Classification of paediatric brain tumours by diffusion weighted imaging and machine learning

Research output: Contribution to journalArticlepeer-review

Authors

  • Lesley MacPherson
  • Benjamin Pinkey
  • Adam Oates
  • Patrick Hales
  • Richard Grundy
  • Dorothee Auer
  • Daniel Rodriguez Gutierrez
  • Tim Jaspan
  • Shivaram Avula
  • Laurence Abernethy
  • Ramneek Kaur
  • Darren Hargrave
  • Dipayan Mitra
  • Simon Bailey
  • Nigel Davies
  • Christopher Clark

Colleges, School and Institutes

External organisations

  • Radiology Department
  • UCL Great Ormond Street Institute of Child Health
  • NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University Of Nottingham, Nottingham, UK
  • NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust
  • University of Liverpool
  • Great Ormond Street Children's Hospital
  • Newcastle Fertility Centre at Life, The Newcastle Upon Tyne Hospitals NHS Foundation Trust, Times Square, Newcastle Upon Tyne, United Kingdom.
  • Sir James Spence Institute of Child Health

Abstract

To determine if apparent diffusion coefficients (ADC) can discriminate between posterior fossa brain tumours on a multicentre basis. A total of 124 paediatric patients with posterior fossa tumours (including 55 Medulloblastomas, 36 Pilocytic Astrocytomas and 26 Ependymomas) were scanned using diffusion weighted imaging across 12 different hospitals using a total of 18 different scanners. Apparent diffusion coefficient maps were produced and histogram data was extracted from tumour regions of interest. Total histograms and histogram metrics (mean, variance, skew, kurtosis and 10th, 20th and 50th quantiles) were used as data input for classifiers with accuracy determined by tenfold cross validation. Mean ADC values from the tumour regions of interest differed between tumour types, (ANOVA P < 0.001). A cut off value for mean ADC between Ependymomas and Medulloblastomas was found to be of 0.984 × 10-3 mm2 s-1 with sensitivity 80.8% and specificity 80.0%. Overall classification for the ADC histogram metrics were 85% using Naïve Bayes and 84% for Random Forest classifiers. The most commonly occurring posterior fossa paediatric brain tumours can be classified using Apparent Diffusion Coefficient histogram values to a high accuracy on a multicentre basis.

Details

Original languageEnglish
Article number2987
JournalScientific Reports
Volume11
Issue number1
Publication statusPublished - 4 Feb 2021