Evaluation of tumor shape features for overall survival prognosis in glioblastoma multiforme patients

Glioblastoma multiforme (GBM) is a rapidly growing tumor associated with poor prognosis. This study evaluates the effectiveness of thirteen tumor shape features for overall survival (OS) prognosis in GBM patients. Shape features were extracted from the abnormality regions of the GBM tumor visible on...

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Bibliographic Details
Published in:Surgical oncology 2019-06, Vol.29, p.178-183
Main Authors: Sanghani, Parita, Ti, Ang Beng, Kam King, Nicolas Kon, Ren, Hongliang
Format: Article
Language:English
Subjects:
Algorithms
Brain cancer
Brain Neoplasms - mortality
Brain Neoplasms - pathology
Brain Neoplasms - surgery
Datasets
Edema
Entropy
Feature extraction
Glioblastoma
Glioblastoma - mortality
Glioblastoma - pathology
Glioblastoma - surgery
Glioblastoma multiforme
Hazards
Humans
Image contrast
Image enhancement
Image Interpretation, Computer-Assisted - methods
Magnetic Resonance Imaging - methods
Medical prognosis
NMR
Nuclear magnetic resonance
Overall survival prognosis
Prognosis
Regression analysis
ROC Curve
Shape
Shape feature extraction
Standard deviation
Survival
Survival analysis
Survival Rate
Tumors
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Summary:Glioblastoma multiforme (GBM) is a rapidly growing tumor associated with poor prognosis. This study evaluates the effectiveness of thirteen tumor shape features for overall survival (OS) prognosis in GBM patients. Shape features were extracted from the abnormality regions of the GBM tumor visible on the fluid attenuated inversion recovery (FLAIR) and T1-weighted contrast enhanced (T1CE) MR images of GBM patients. Survival analysis was performed using univariate and multivariate (with clinical features) Cox proportional hazards regression analysis. Kaplan-Meier survival curves were plotted and observed for the shape features which were found to be significant from the Cox regression analysis. Three 3D shape features: Bounding ellipsoid volume ratio (BEVR), sphericity and spherical disproportion, computed from both the abnormality regions were found to be significant for OS prognosis in GBM patients. •3 shape features found significant for GBM survival prognosis from Cox regression .•Same features significant for GBM survival prognosis from KM survival curves.•3D tumor shape features more useful for GBM survival prognosis than 2D .•Irregular GBM tumor shape signifies poor survival .•Regular GBM tumor shape associated with prolonged survival.
ISSN:0960-7404
1879-3320
DOI:10.1016/j.suronc.2019.05.005