Multiparametric analysis of magnetic resonance images for glioma grading and patient survival time prediction.

Background: A systematic comparison of magnetic resonance imaging (MRI) options for glioma diagnosis is lacking.

Purpose: To investigate multiple MR-derived image features with respect to diagnostic accuracy in tumor grading and survival prediction in glioma patients.

Material And Methods: T1 pre- and post-contrast, T2 and dynamic susceptibility contrast scans of 74 glioma patients with histologically confirmed grade were acquired.

Automatic glioma characterization from dynamic susceptibility contrast imaging: brain tumor segmentation using knowledge-based fuzzy clustering.

Purpose: To assess whether glioma volumes from knowledge-based fuzzy c-means (FCM) clustering of multiple MR image classes can provide similar diagnostic efficacy values as manually defined tumor volumes when characterizing gliomas from dynamic susceptibility contrast (DSC) imaging.

Materials And Methods: Fifty patients with newly diagnosed gliomas were imaged using DSC MR imaging at 1.5 Tesla.

Predictive modeling in glioma grading from MR perfusion images using support vector machines.

The advantages of predictive modeling in glioma grading from MR perfusion images have not yet been explored. The aim of the current study was to implement a predictive model based on support vector machines (SVM) for glioma grading using tumor blood volume histogram signatures derived from MR perfusion images and to assess the diagnostic accuracy of the model and the sensitivity to sample size. A total of 86 patients with histologically-confirmed gliomas were imaged using dynamic susceptibility contrast (DSC) MRI at 1.

Glioma grading by using histogram analysis of blood volume heterogeneity from MR-derived cerebral blood volume maps.

Purpose: To retrospectively compare the diagnostic accuracy of an alternative method used to grade gliomas that is based on histogram analysis of normalized cerebral blood volume (CBV) values from the entire tumor volume (obtained with the histogram method) with that of the hot-spot method, with histologic analysis as the reference standard.

Materials And Methods: The medical ethics committee approved this study, and all patients provided informed consent. Fifty-three patients (24 female, 29 male; mean age, 48 years; age range, 14-76 years) with histologically confirmed gliomas were examined with dynamic contrast material-enhanced 1.