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Abstract #0415

Multimodal MRI to aid prediction of low-grade glioma growth characteristics

Franklyn Howe1, Timothy Jones2, Philip Rich2, Jordan Colman3, Guang Yang4, Felix Raschke5, Venus Liang1, Alex Denley1, and Thomas Barrick1
1Neurosciences Research Centre, St George's, University of London, London, United Kingdom, 2St George's University Hospitals NHS Foundation Trust, London, United Kingdom, 3Ashford and St Peter's Hospitals NHS Foundation Trust, Surrey, United Kingdom, 4National Lund and Heart Institute, Imperial College, London, United Kingdom, 5OncoRay—National Center for Radiation Research in Oncology, Dresden, Germany

1H MRS and DTI measures were assessed for their ability to predict the future growth and malignant transformation of low-grade gliomas. The tumour core NAA concentration and the mean diffusivity (MD) within the MRS voxel, combined with the FLAIR tumour volume, provided a good predictor of tumours with higher growth rates. A ROC analysis gave an AUC of 0.86 to predict tumours likely to undergo malignant progression, and AUC of 0.98 when including those undergoing early debulking. The combined NAA, MD and volumetric parameter provided a single time-point assessment of future growth characteristics.

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