The use of multivariate MR imaging intensities versus metabolic data from MR spectroscopic imaging for brain tumour classification

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作者：

A Devos，AW Simonetti，MVD Graaf，L Lukas，JAK Suykens，L Vanhamme，LMC Buydens，A Heerschap，SV Huffel

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摘要：

This study investigated the value of information from both magnetic resonance imaging and magnetic resonance spectroscopic imaging (MRSI) to automated discrimination of brain tumours. The influence of imaging intensities and metabolic data was tested by comparing the use of MR spectra from MRSI, MR imaging intensities, peak integration values obtained from the MR spectra and a combination of the latter two. Three classification techniques were objectively compared: linear discriminant analysis, least squares support vector machines (LS-SVM) with a linear kernel as linear techniques and LS-SVM with radial basis function kernel as a nonlinear technique. Classifiers were evaluated over 100 stratified random splittings of the dataset into training and test sets. The area under the receiver operating characteristic (ROC) curve (AUC) was used as a global performance measure on test data. In general, all techniques obtained a high performance when using peak integration values with or without MR imaging intensities. For example for low- versus high-grade tumours, low- versus high-grade gliomas and gliomas versus meningiomas, the mean test AUC was higher than 0.91, 0.94, and 0.99, respectively, when both MR imaging intensities and peak integration values were used. The use of metabolic data from MRSI significantly improved automated classification of brain tumour types compared to the use of MR imaging intensities solely.

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关键词：

Experimental/ biomedical MRI brain cancer cellular biophysics tumours/ multivariate MR imaging intensities metabolic data brain tumour classification magnetic resonance spectroscopic imaging linear discriminant analysis least squares support vector machines radial basis function kernel nonlinear technique random splittings receiver operating characteristic curve peak integration values low-grade tumours high-grade tumours low-grade gliomas high-grade gliomas meningiomas/ A8760I Medical magnetic resonance imaging and spectroscopy A8770E Patient diagnostic methods and instrumentation B7510N Biomedical magnetic resonance imaging and spectroscopy