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Updated: Jan 15, 2026

Magnetic Resonance Elastography Methodology for the Evaluation of Tissue Engineered Construct Growth
Published on: February 9, 2012
Evaluating Measurement Stability in Glioblastomas Using Magnetic Resonance Elastography: Repeatability and
Ancuta I Friismose1,2, Jan S Aunan-Diop3,4, Michael Pedersen5
1Department of Radiology, Odense University Hospital, Odense, Denmark.
Magnetic resonance elastography (MRE) shows glioblastoma tumor stiffness (|G*|) and storage modulus (G') are repeatable and reliable metrics. Normalization to white matter may decrease measurement consistency.
Area of Science:
- Neuroimaging
- Biophysics
- Quantitative Biomarkers
Background:
- Magnetic resonance elastography (MRE) shows promise for intracranial tumor characterization, including glioblastoma.
- Evaluating measurement consistency and interobserver agreement is crucial for MRE's clinical adoption as a quantitative biomarker.
Purpose of the Study:
- To assess the repeatability and interobserver agreement of absolute and normalized shear modulus (|G*|), storage modulus (G'), and loss modulus (G″) in glioblastoma.
Main Methods:
- Prospective study involving 13 adults with histopathologically confirmed glioblastoma using 3T MRI.
- Two same-session MRE acquisitions were performed, with tumor segmentation by two independent observers.
- Repeatability assessed via repeatability coefficient and coefficient of variation; interobserver agreement via intraclass correlation coefficient.
Main Results:
- Absolute tumor |G*| and G' demonstrated high repeatability (coefficients of variation 1.42%-2.08%) and excellent interobserver agreement (ICC 0.97-0.95).
- Normalized measurements showed significantly lower repeatability (coefficients of variation 4.21%-5.45%) compared to absolute values.
- Tumor G″ exhibited higher variability, with no significant difference between absolute and normalized measurements.
Conclusions:
- Absolute tumor |G*| and G' are the most repeatable and reliable metrics for glioblastoma characterization using MRE.
- Normalization to normal-appearing white matter may decrease measurement repeatability due to white matter variability.
- The study's small sample size (n=13) warrants caution regarding generalizability.
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