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Abstract #1321

Prediction of WHO histological grade of paediatric posterior fossa ependymoma using diagnostic MR imaging and machine learning

Richard J Dury1, Anbarasu Lourdusamy1, Dorothee P Auer2, Andrew Peet3, Richard G Grundy1, and Robert A Dineen2
1Children's Brain Tumour Research Centre, University of Nottingham, Nottingham, United Kingdom, 2Radiological Sciences, University of Nottingham, Nottingham, United Kingdom, 3Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom

Synopsis

Ependymoma is the second most common paediatric malignant brain tumour and has a dismal outcome. WHO histological grade provides insight to prognosis and in most series confers a poor survival. Here we present a method to non-invasively predict the grade of paediatric posterior fossa ependymoma using diagnostic MR imaging (T2w and ADC) and machine learning. We found that WHO Grade II and III tumours can both be predicted with a sensitivity/specificity of 0.7±0.23 and 0.67±0.15 respectively. We believe these results provide the basis for a clinically important aid to decision making in the early stages of treatment.

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