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Abstract: Objective: The main objective of this retrospective work was the study of three-dimensional (3D) heterogeneity measures of post-contrast pre-operative MR images acquired with T1 weighted sequences of patients with glioblastoma (GBM) as predictors of clinical outcome. Methods: 79 patients from 3 hospitals were included in the study. 16 3D textural heterogeneity measures were computed including run-length matrix (RLM) features (regional heterogeneity) and co-occurrence matrix (CM) features (local heterogeneity). The significance of the results was studied using Kaplan?Meier curves and Cox proportional hazards analysis. Correlation between the variables of the study was assessed using the Spearman?s correlation coefficient. Results: Kaplan?Meyer survival analysis showed that 4 of the 11 RLM features and 4 of the 5 CM features considered were robust predictors of survival. The median survival differences in the most significant cases were of over 6 months. Conclusion: Heterogeneity measures computed on the post-contrast pre-operative T1 weighted MR images of patients with GBM are predictors of survival. Advances in knowledge: Texture analysis to assess tumour heterogeneity has been widely studied. However, most works develop a two-dimensional analysis, focusing only on one MRI slice to state tumour heterogeneity. The study of fully 3D heterogeneity textural features as predictors of clinical outcome is more robust and is not dependent on the selected slice of the tumour.
Fuente: British Journal of Radiology, 2016, 89, 20160242
Editorial: British Institute of Radiology
Fecha de publicación: 16/06/2016
Nº de páginas: 9
Tipo de publicación: Artículo de Revista
DOI: 10.1259/bjr.20160242
ISSN: 1748-880X,0007-1285
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MOLINA, DAVID
PÉREZ BETETA, JULIÁN
LUQUE, BELÉN
ARREGUI, ELENA
CALVO, MANUEL
BORRÁS, JOSÉ M.
LÓPEZ, CARLOS
JUAN MARTINO GONZALEZ
CARLOS JOSE VELASQUEZ RODRIGUEZ
ASENJO, BEATRIZ
BENAVIDES, MANUEL
HERRUZO, ISMAEL
MARTÍNEZ GONZÁLEZ, ALICIA
PÉREZ ROMASANTA, LUIS
ARANA, ESTANISLAO
PÉREZ GARCÍA, VÍCTOR M.
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