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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
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
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
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: Br J Radiol 2016; 89: 20160242
Editorial: British Institute of Radiology
Fecha de publicación: 16/06/2016
Nº de páginas: 9
Tipo de publicación: Artículo de Revista
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PÉREZ BETETA, JULIÁN
BORRÁS, JOSÉ M.
JUAN MARTINO GONZALEZ
CARLOS JOSE VELASQUEZ RODRIGUEZ
MARTÍNEZ GONZÁLEZ, ALICIA
PÉREZ ROMASANTA, LUIS
PÉREZ GARCÍA, VÍCTOR M.