当前位置： SCI文献检索 > EUROPEAN RADIOLOGY期刊下所有文献 > Morphological MRI-based features provide pretreatment survival prediction in glioblastoma.

Morphological MRI-based features provide pretreatment survival prediction in glioblastoma.

Abstract：

OBJECTIVES:We wished to determine whether tumor morphology descriptors obtained from pretreatment magnetic resonance images and clinical variables could predict survival for glioblastoma patients. METHODS:A cohort of 404 glioblastoma patients (311 discoveries and 93 validations) was used in the study. Pretreatment volumetric postcontrast T1-weighted magnetic resonance images were segmented to obtain the relevant morphological measures. Kaplan-Meier, Cox proportional hazards, correlations, and Harrell's concordance indexes (c-indexes) were used for the statistical analysis. RESULTS:A linear prognostic model based on the outstanding variables (age, contrast-enhanced (CE) rim width, and surface regularity) identified a group of patients with significantly better survival (p < 0.001, HR = 2.57) with high accuracy (discovery c-index = 0.74; validation c-index = 0.77). A similar model applied to totally resected patients was also able to predict survival (p < 0.001, HR = 3.43) with high predictive value (discovery c-index = 0.81; validation c-index = 0.92). Biopsied patients with better survival were well identified (p < 0.001, HR = 7.25) by a model including age and CE volume (c-index = 0.87). CONCLUSIONS:Simple linear models based on small sets of meaningful MRI-based pretreatment morphological features and age predicted survival of glioblastoma patients to a high degree of accuracy. The partition of the population using the extent of resection improved the prognostic value of those measures. KEY POINTS:• A combination of two MRI-based morphological features (CE rim width and surface regularity) and patients' age outperformed previous prognosis scores for glioblastoma. • Prognosis models for homogeneous surgical procedure groups led to even more accurate survival prediction based on Kaplan-Meier analysis and concordance indexes.

journal_name

Eur Radiol

journal_title

European radiology

authors

Pérez-Beteta J,Molina-García D,Martínez-González A,Henares-Molina A,Amo-Salas M,Luque B,Arregui E,Calvo M,Borrás JM,Martino J,Velásquez C,Meléndez-Asensio B,de Lope ÁR,Moreno R,Barcia JA,Asenjo B,Benavides M,Herruzo I,

doi

10.1007/s00330-018-5758-7

subject

Has Abstract

pub_date

2019-04-01 00:00:00

pages

1968-1977

issue

eissn

0938-7994

issn

1432-1084

pii

10.1007/s00330-018-5758-7

journal_volume

pub_type

杂志文章,多中心研究

在线工具

Morphological MRI-based features provide pretreatment survival prediction in glioblastoma.