The glioblastoma biomechanical landscape: A systematic review of magnetic resonance elastography (MRE) of brain tumors and healthy brain

Diagnosis of a glioblastoma (GBM) brain tumor is associated with very poor prognosis. Currently, few preclinical models used to identify new therapies address the soft brain tissue environment and GBM mechanoresponses, which are implicated in disease progression. Understanding the GBM biomechanical landscape is critical to deriving improved preclinical models and magnetic resonance elastography (MRE) holds promise to address this gap. Due to technical and feasibility issues for MRE of patient tumors at scale, most studies only report on small cohorts of patients, thus limiting the conclusions that may be drawn from individual studies. To thus gain a better overview, we have undertaken a systematic review and meta-analysis of the reported tissue viscoelastic property values from studies of both healthy brain and brain tumors, with a particular focus on delineating measurements relative to MRE transducer vibration frequency. Based on these analyses, healthy white matter consistently appears stiffer than gray matter. Further, analyses of pooled healthy brain tissue measurements vs human GBM suggested that, overall, the GBM has the same stiffness as the surrounding healthy tissue. This contrasted with mouse models of GBM, where the tumors appear softer than brain tissue. The limited number of studies of human GBM <i>in situ</i> is a caveat to these conclusions and MRE analyses of larger GBM patient cohorts are urgently needed. Meanwhile, the information from this analysis can be used to guide engineering of improved preclinical models with features that recapitulate the <i>in vivo</i> brain tissue environment.

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Publication Details

Journal
APL Bioengineering
Published
2025-09-01
DOI
https://doi.org/10.1063/5.0277950
Citations
2
Primary Topic
Ultrasound Imaging and Elastography
Type
article
Field-Weighted Citation Impact
2.72

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article

The glioblastoma biomechanical landscape: A systematic review of magnetic resonance elastography (MRE) of brain tumors and healthy brain

Lauriane Jugé, Lynne E. Bilston, Geraldine M. O’Neill, Eric Hau et al.
2 citations
APL Bioengineering
Ultrasound Imaging and Elastography
2.72
article

The glioblastoma biomechanical landscape: A systematic review of magnetic resonance elastography (MRE) of brain tumors and healthy brain

Lauriane Jugé, Lynne E. Bilston, Geraldine M. O’Neill, Eric Hau, Thuvarahan Jegathees
article en
2 citations

Abstract

Diagnosis of a glioblastoma (GBM) brain tumor is associated with very poor prognosis. Currently, few preclinical models used to identify new therapies address the soft brain tissue environment and GBM mechanoresponses, which are implicated in disease progression. Understanding the GBM biomechanical landscape is critical to deriving improved preclinical models and magnetic resonance elastography (MRE) holds promise to address this gap. Due to technical and feasibility issues for MRE of patient tumors at scale, most studies only report on small cohorts of patients, thus limiting the conclusions that may be drawn from individual studies. To thus gain a better overview, we have undertaken a systematic review and meta-analysis of the reported tissue viscoelastic property values from studies of both healthy brain and brain tumors, with a particular focus on delineating measurements relative to MRE transducer vibration frequency. Based on these analyses, healthy white matter consistently appears stiffer than gray matter. Further, analyses of pooled healthy brain tissue measurements vs human GBM suggested that, overall, the GBM has the same stiffness as the surrounding healthy tissue. This contrasted with mouse models of GBM, where the tumors appear softer than brain tissue. The limited number of studies of human GBM <i>in situ</i> is a caveat to these conclusions and MRE analyses of larger GBM patient cohorts are urgently needed. Meanwhile, the information from this analysis can be used to guide engineering of improved preclinical models with features that recapitulate the <i>in vivo</i> brain tissue environment.

APL BioengineeringVol. 9(3)
The University of Sydney (AU), Children's Hospital at Westmead (AU), Sydney Hospital (AU), Westmead Hospital (AU), UNSW Sydney (AU), Westmead Institute for Medical Research (AU), Sydney Children’s Hospitals Network (AU), Neuroscience Research Australia (AU)
National Health and Medical Research Council
Openalex Percentile: Top 9%
Ultrasound Imaging and Elastography
2.72
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