Improving the estimation of prognosis for glioblastoma patients by MR based hemodynamic tissue signatures

Advanced MRI and molecular markers have been raised as crucial to improve prognostic models for patients having glioblastoma (GBM) lesions. In particular, different MR perfusion based markers describing vascular intrapatient heterogeneity have been correlated with tumor aggressiveness, and represent...

Full description

Saved in:
Bibliographic Details
Published in:NMR in biomedicine 2018-12, Vol.31 (12), p.e4006-n/a
Main Authors: Fuster‐Garcia, Elies, Juan‐Albarracín, Javier, García‐Ferrando, Germán A., Martí‐Bonmatí, Luis, Aparici‐Robles, Fernando, García‐Gómez, Juan M.
Format: Article
Language:English
Subjects:
Biological products
Demographics
Glioblastoma
habitats
hemodynamic tissue signatures
Heterogeneity
intrapatient heterogeneity
Lesions
Magnetic resonance imaging
Markers
Medical prognosis
Neoplasia
Neoplasms
Patients
Perfusion
perfusion weighted imaging
Regression analysis
Tumors
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Advanced MRI and molecular markers have been raised as crucial to improve prognostic models for patients having glioblastoma (GBM) lesions. In particular, different MR perfusion based markers describing vascular intrapatient heterogeneity have been correlated with tumor aggressiveness, and represent key information to understand tumor resistance against effective therapies of these neoplasms. Recently, hemodynamic tissue signature (HTS) markers based on MR perfusion images have been demonstrated to be useful for describing the heterogeneity of GBM at the voxel level, as well as demonstrating significant correlations with the patient's overall survival. In this work, we analyze the abilities of these markers to improve the conventional prognostic models based on clinical, morphological, and demographic features. Our results, in both the regression and classification tests, show that inclusion of the HTS markers improves the reliability of prognostic models. The HTS method is fully automatic and it is available for research use at http://www.oncohabitats.upv.es. Hemodynamic tissue signatures (HTS) based on MR‐DSC images have been demonstrated to be useful for describing the heterogeneity of glioblastoma at voxel level, as well as demonstrating significant correlations with patients' overall survival. In this work analyse the capabilities of these markers to improve the conventional prognostic models based on clinical, morphological, and demographic features. Our results, both in the regression and classification tests, show that the inclusion of the HTS markers improves the reliability of prognostic models.
ISSN:0952-3480
1099-1492
DOI:10.1002/nbm.4006