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REVIEW: MR Elastography of Brain Tumors

1Department of Neurosurgery, Brigham and Women's Hospital, Boston, Harvard Medical School, Boston, MA, USA. Electronic address:
2Institute of Neuroradiology, University Medical Center Goettingen, Goettingen, Germany.
3Inserm U1148, LVTS, University Paris Diderot, University Paris 13, Paris, France.
4Department of Radiology, Brigham and Women's Hospital, Boston, Harvard Medical School, Boston, MA, USA.
Elsevier Science
Publication Date:
Neuroimage Clin
Volume Number:
Neuroimage Clin. 2019 Nov 23;25:102109.
PubMed ID:
Brain tumor, Glioma, MR elatography, Meningioma, Pituitary adenoma, Surgical planning
Appears in Collections:
P41 EB015898/EB/NIBIB NIH HHS/United States
Generated Citation:
Bunevicius A., Schregel K., Sinkus R., Golby A., Patz S. REVIEW: MR Elastography of Brain Tumors. Neuroimage Clin. 2019 Nov 23;25:102109. PMID: 31809993. PMCID: PMC6909210.
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MR elastography allows non-invasive quantification of the shear modulus of tissue, i.e. tissue stiffness and viscosity, information that offers the potential to guide presurgical planning for brain tumor resection. Here, we review brain tumor MRE studies with particular attention to clinical applications. Studies that investigated MRE in patients with intracranial tumors, both malignant and benign as well as primary and metastatic, were queried from the Pubmed/Medline database in August 2018. Reported tumor and normal appearing white matter stiffness values were extracted and compared as a function of tumor histopathological diagnosis and MRE vibration frequencies. Because different studies used different elastography hardware, pulse sequences, reconstruction inversion algorithms, and different symmetry assumptions about the mechanical properties of tissue, effort was directed to ensure that similar quantities were used when making inter-study comparisons. In addition, because different methodologies and processing pipelines will necessarily bias the results, when pooling data from different studies, whenever possible, tumor values were compared with the same subject's contralateral normal appearing white matter to minimize any study-dependent bias. The literature search yielded 10 studies with a total of 184 primary and metastatic brain tumor patients. The group mean tumor stiffness, as measured with MRE, correlated with intra-operatively assessed stiffness of meningiomas and pituitary adenomas. Pooled data analysis showed significant overlap between shear modulus values across brain tumor types. When adjusting for the same patient normal appearing white matter shear modulus values, meningiomas were the stiffest tumor-type. MRE is increasingly being examined for potential in brain tumor imaging and might have value for surgical planning. However, significant overlap of shear modulus values between a number of different tumor types limits applicability of MRE for diagnostic purposes. Thus, further rigorous studies are needed to determine specific clinical applications of MRE for surgical planning, disease monitoring and molecular stratification of brain tumors.