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Abstract #3931

Childhood Brain Tumour Classification Through Proton Magnetic Resonance Spectroscopy and Diffusion Weighted Imaging

Dadi Zhao1,2, James T. Grist1,2, Heather E.L. Rose1,2, Huijun Li2, Lesley MacPherson2, Yu Sun1,2, and Andrew C. Peet1,2
1Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom, 2Department of Oncology, Birmingham Children's Hospital, Birmingham, United Kingdom

Multi-modal functional imaging is expected to improve the classification of childhood brain tumours. Forty-three patients with a confirmed childhood brain tumour were enrolled in this 1.5T multi-modal functional imaging study. Short-echo proton magnetic resonance spectroscopy (1H-MRS) and diffusion weighted imaging (DWI) were acquired and analysed through multi-class receiver operating characteristics for feature selection and a wavelet-based data-driven framework for 1H-MRS noise suppression. The balanced classification accuracy across the three tumour types was improved to 95% through linear discriminant analysis by combining DWI and noise-suppressed 1H-MRS, showing improved from 84% through only DWI and 88% through only noise-suppressed 1H-MRS.

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