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Brain and central nervous system (CNS) tumours form the second most common group of cancers in children in the UK, accounting for 27% of all childhood cancers. Initial assessment of tumours from MRI scans is usually performed qualitatively, via radiologists' visual inspection. However, different brain tumours do not always demonstrate clear differences in physical appearance, so a diagnosis is usually made via histopathological examination of biopsy samples taken through surgery. This gives rise to the need for accurate, yet non-invasive diagnostic aids. In a previous study, we demonstrated the potential of MRI texture analysis in capturing quantitative information about paediatric brain tumours. In this work, we carry out a preliminary investigation on the use of 3D (volumetric) texture analysis of T1 and T2-weighted MR images in order to classify paediatric brain tumours. We then compare its performance with the traditional 2D texture analysis approach. Our preliminary findings are very encouraging and show that 3D textural features are capable of capturing more discriminative information about the tumours than the traditional 2D approach. However, it remains necessary to expand the work further to include larger cohorts and additional modalities.

Despite current advances in neuro-imaging, the characterisation of paediatric brain tumours and neurological disorders is very challenging. Whilst Magnetic Resonance Imaging (MRI) provides images of superb clarity, it gives little information on how aggressive a tumour is. It is also very difficult to visually inspect any underlying textural patterns between tumours on MR images. This gives rise to the need for a quantitative means of analysing MR images for characterising tumours. In this work, we present a preliminary investigation into the effectiveness of texture analysis as a quantitative approach for classifying paediatric brain tumours.