Texture Feature Ratios from Relative CBV Maps of Perfusion MRI Are Associated with Patient Survival in Glioblastoma.

Autor:	Lee J; From the Departments of Bioinformatics and Computational Biology (J.L., A.R.)., Jain R; Department of Radiology (R.J.), New York University School of Medicine, Langone Medical Center, New York, New York., Khalil K; Department of Radiology (K.K., B.G.), Henry Ford Hospital, Detroit, Michigan., Griffith B; Department of Radiology (K.K., B.G.), Henry Ford Hospital, Detroit, Michigan., Bosca R; Department of Medical Physics (R.B.), University of Wisconsin, Madison, Wisconsin., Rao G; Neurosurgery (G.R.), The University of Texas MD Anderson Cancer Center, Houston, Texas., Rao A; From the Departments of Bioinformatics and Computational Biology (J.L., A.R.) aruppore@mdanderson.org.
Jazyk:	angličtina
Zdroj:	AJNR. American journal of neuroradiology [AJNR Am J Neuroradiol] 2016 Jan; Vol. 37 (1), pp. 37-43. Date of Electronic Publication: 2015 Oct 15.
DOI:	10.3174/ajnr.A4534
Abstrakt:	Background and Purpose: Texture analysis has been applied to medical images to assist in tumor tissue classification and characterization. In this study, we obtained textural features from parametric (relative CBV) maps of dynamic susceptibility contrast-enhanced MR images in glioblastoma and assessed their relationship with patient survival. Materials and Methods: MR perfusion data of 24 patients with glioblastoma from The Cancer Genome Atlas 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 tumor 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 patients with glioblastoma. (© 2016 by American Journal of Neuroradiology.)
Databáze:	MEDLINE
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