Tumour heterogeneity in glioblastoma assessed by MRI texture analysis: a potential marker of survival.
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 T1weighted sequences of patients with glioblastoma (GBM) as predictors of clinical outcome.
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.
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.
Heterogeneity measures computed on the post-contrast pre-operative T1weighted MR images of patients with GBM are predictors of survival.
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.
1 Instituto de Matemática Aplicada a la Ciencia y la Ingeniería, Universidad de Castilla-La Mancha, Ciudad Real, Spain.
David
D
Molina
1 Instituto de Matemática Aplicada a la Ciencia y la Ingeniería, Universidad de Castilla-La Mancha, Ciudad Real, Spain.
Julián
J
Pérez-Beteta
1 Instituto de Matemática Aplicada a la Ciencia y la Ingeniería, Universidad de Castilla-La Mancha, Ciudad Real, Spain.
Belén
B
Luque
2 Hospital General de Ciudad Real, Ciudad Real, Spain.
Elena
E
Arregui
2 Hospital General de Ciudad Real, Ciudad Real, Spain.
Manuel
M
Calvo
2 Hospital General de Ciudad Real, Ciudad Real, Spain.
José M
JM
Borrás
2 Hospital General de Ciudad Real, Ciudad Real, Spain.
Carlos
C
López
3 Hospital Marqués de Valdecilla, Santander, Spain.
Juan
J
Martino
3 Hospital Marqués de Valdecilla, Santander, Spain.
Carlos
C
Velasquez
4 Hospital Carlos Haya, Málaga, Spain.
Beatriz
B
Asenjo
4 Hospital Carlos Haya, Málaga, Spain.
Manuel
M
Benavides
4 Hospital Carlos Haya, Málaga, Spain.
Ismael
I
Herruzo
1 Instituto de Matemática Aplicada a la Ciencia y la Ingeniería, Universidad de Castilla-La Mancha, Ciudad Real, Spain.
Alicia
A
Martínez-González
5 Hospital Universitario de Salamanca, Salamanca, Spain.
Luis
L
Pérez-Romasanta
6 Instituto Valenciano de Oncología, Valencia, Spain.
Estanislao
E
Arana
1 Instituto de Matemática Aplicada a la Ciencia y la Ingeniería, Universidad de Castilla-La Mancha, Ciudad Real, Spain.
Víctor M
VM
Pérez-García