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.
This abstract and the presentation materials are available to members only; a login is required.