title: Discrimination between glioblastoma multiforme and solitary metastasis using morphological features derived from the p:q tensor decomposition of diffusion tensor imaging.
abstract: The management and treatment of high-grade glioblastoma multiforme (GBM) and solitary metastasis (MET) are very different and influence the prognosis and subsequent clinical outcomes. In the case of a solitary MET, diagnosis using conventional radiology can be equivocal. Currently, a definitive diagnosis is based on histopathological analysis on a biopsy sample. Here, we present a computerised decision support framework for discrimination between GBM and solitary MET using MRI, which includes: (i) a semi-automatic segmentation method based on diffusion tensor imaging; (ii) two-dimensional morphological feature extraction and selection; and (iii) a pattern recognition module for automated tumour classification. Ground truth was provided by histopathological analysis from pre-treatment stereotactic biopsy or at surgical resection. Our two-dimensional morphological analysis outperforms previous methods with high cross-validation accuracy of 97.9% and area under the receiver operating characteristic curve of 0.975 using a neural networks-based classifier.
authors: Neuroscience Research Centre, Cardiovascular and Cell Sciences Institute, St. George's, University of London, London, UK.
authors: Guang
authors: G
authors: Yang
authors: Timothy L
authors: TL
authors: Jones
authors: Thomas R
authors: TR
authors: Barrick
authors: Franklyn A
authors: FA
authors: Howe
mesh_terms: D000465:Algorithms; D001932:Brain Neoplasms / Q000473:pathology* / Q000556:secondary*; D003937:Diagnosis, Differential; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005260:Female; D005909:Glioblastoma / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: MRI; brain tumour classification; brain tumour segmentation; computer-aided diagnosis; diffusion tensor imaging; feature selection; morphological shape analysis; pattern recognition and classification