RT Journal Article
T1 Tumor Surface Regularity at MR Imaging Predicts Survival and Response to Surgery in Patients with Glioblastoma.
A1 Pérez-Beteta, Julián
A1 Molina-García, David
A1 Ortiz-Alhambra, José A
A1 Fernández-Romero, Antonio
A1 Luque, Belén
A1 Arregui, Elena
A1 Calvo, Manuel
A1 Borrás, José M
A1 Meléndez, Bárbara
A1 Rodríguez de Lope, Ángel
A1 Moreno de la Presa, Raquel
A1 Iglesias Bayo, Lidia
A1 Barcia, Juan A
A1 Martino, Juan
A1 Velásquez, Carlos
A1 Asenjo, Beatriz
A1 Benavides, Manuel
A1 Herruzo, Ismael
A1 Revert, Antonio
A1 Arana, Estanislao
A1 Pérez-García, Víctor M
AB Purpose To evaluate the prognostic and predictive value of surface-derived imaging biomarkers obtained from contrast material-enhanced volumetric T1-weighted pretreatment magnetic resonance (MR) imaging sequences in patients with glioblastoma multiforme. Materials and Methods A discovery cohort from five local institutions (165 patients; mean age, 62 years ± 12 [standard deviation]; 43% women and 57% men) and an independent validation cohort (51 patients; mean age, 60 years ± 12; 39% women and 61% men) from The Cancer Imaging Archive with volumetric T1-weighted pretreatment contrast-enhanced MR imaging sequences were included in the study. Clinical variables such as age, treatment, and survival were collected. After tumor segmentation and image processing, tumor surface regularity, measuring how much the tumor surface deviates from a sphere of the same volume, was obtained. Kaplan-Meier, Cox proportional hazards, correlations, and concordance indexes were used to compare variables and patient subgroups. Results Surface regularity was a powerful predictor of survival in the discovery (P = .005, hazard ratio [HR] = 1.61) and validation groups (P = .05, HR = 1.84). Multivariate analysis selected age and surface regularity as significant variables in a combined prognostic model (P
YR 2018
FD 2018
LK http://hdl.handle.net/10668/12622
UL http://hdl.handle.net/10668/12622
LA en
DS RISalud
RD Apr 12, 2025