RT Journal Article
T1 Tumor Surface Regularity at MR Imaging Predicts Survival and Response to Surgery in Patients with Glioblastoma.
A1 Perez-Beteta, Julian
A1 Molina-Garcia, David
A1 Ortiz-Alhambra, Jose A
A1 Fernandez-Romero, Antonio
A1 Luque, Belen
A1 Arregui, Elena
A1 Calvo, Manuel
A1 Borras, Jose M
A1 Melendez, Barbara
A1 Rodriguez-de-Lope, Angel
A1 Moreno-de-la-Presa, Raquel
A1 Iglesias-Bayo, Lidia
A1 Barcia, Juan A
A1 Martino, Juan
A1 Velasquez, Carlos
A1 Asenjo, Beatriz
A1 Benavides, Manuel
A1 Herruzo, Ismael
A1 Revert, Antonio
A1 Arana, Estanislao
A1 Perez-Garcia, Victor M
K1 Brain Neoplasms
K1 Glioblastoma
K1 Kaplan-Meier Estimate
K1 Magnetic Resonance Imaging
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< .001, HR = 3.05). The model achieved concordance indexes of 0.76 and 0.74 for the discovery and validation cohorts, respectively. Tumor surface regularity was a predictor of survival for patients who underwent complete resection (P = .01, HR = 1.90). Tumors with irregular surfaces did not benefit from total over subtotal resections (P = .57, HR = 1.17), but those with regular surfaces did (P = .004, HR = 2.07). Conclusion The surface regularity obtained from high-resolution contrast-enhanced pretreatment volumetric T1-weighted MR images is a predictor of survival in patients with glioblastoma. It may help in classifying patients for surgery.
PB Radiological Society of North America
YR 2018
FD 2018-04-03
LK http://hdl.handle.net/10668/12622
UL http://hdl.handle.net/10668/12622
LA en
NO Pérez-Beteta J, Molina-García D, Ortiz-Alhambra JA, Fernández-Romero A, Luque B, Arregui E, et al. Tumor Surface Regularity at MR Imaging Predicts Survival and Response to Surgery in Patients with Glioblastoma. Radiology. 2018 Jul;288(1):218-225
DS RISalud
RD Sep 11, 2025