BACKGROUND AND PURPOSE: Texture analysis has been applied to medical images to assist in @entity5 tissue classification and characterization. In this study, we obtained textural features from parametric (relative CBV) maps of dynamic susceptibility contrast-enhanced MR images in @entity463 and assessed their relationship with @entity1 survival. MATERIALS AND METHODS: MR perfusion data of 24 @entity1 with @entity463 from The @entity5 were analyzed in this study. One- and 2D texture feature ratios and kinetic textural features based on relative CBV values in the contrast-enhancing and nonenhancing lesions of the @entity5 were obtained. Receiver operating characteristic, Kaplan-Meier, and multivariate Cox proportional hazards regression analyses were used to assess the relationship between texture feature ratios and overall survival. RESULTS: Several feature ratios are capable of stratifying survival in a statistically significant manner. These feature ratios correspond to homogeneity (P = .008, based on the log-rank test), angular second moment (P = .003), inverse difference moment (P = .013), and entropy (P = .008). Multivariate Cox proportional hazards regression analysis showed that homogeneity, angular second moment, inverse difference moment, and entropy from the contrast-enhancing lesion were significantly associated with overall survival. For the nonenhancing lesion, skewness and variance ratios of relative CBV texture were associated with overall survival in a statistically significant manner. For the kinetic texture analysis, the Haralick correlation feature showed a P value close to .05. CONCLUSIONS: Our study revealed that texture feature ratios from contrast-enhancing and nonenhancing lesions and kinetic texture analysis obtained from perfusion parametric maps provide useful information for predicting survival in @entity1 with @entity463 .

Texture Feature Ratios from Relative CBV Maps of Perfusion MRI Are Associated with XXXX @entity463 .

@entity5 :: ('MESH:D009369', 'Disease') :: ['tumor', 'Cancer Genome Atlas'] @entity1 :: ('9606', 'Species') :: ['patients', 'patient'] @entity463 :: ('MESH:D005909', 'Disease') :: ['glioblastoma']
@entity1 :: (9606,Species) :: ['Patient']
