MRE Standardization

Unlocking Precision in Liver Stiffness Biomarkers

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Magnetic Resonance Elastography (MRE) is one of the most accurate, non-invasive imaging biomarkers for quantifying liver stiffness and assessing liver fibrosis. MRE’s clinical utility is recognized internationally — but consistency in acquisition and analysis is essential for reliable interpretation, especially in longitudinal monitoring.

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The Quantitative Imaging Biomarkers Alliance (QIBA) has published a Clinically Feasible Profile for MRE of the liver, establishing performance benchmarks and procedural guidance that reduce variability and support reproducible stiffness measurements.

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Standardizing MRE for Clinical Confidence and Comparability​

 

This QIBA profile defines:

• A clear performance claim: A measured change in clinical hepatic stiffness of ≥19% reflects a true biologic change with 95% confidence — a crucial metric for clinical decision making.

• Protocol consistency: Best practices across subject handling, image acquisition, reconstruction, quality assurance, and analysis help harmonize data from different sites and systems.

• Assessment procedures: Repeatability and stability checks ensure performance aligns with the defined claim, supporting credible results across clinical studies.

 

Whether you’re implementing MRE in research settings, deploying it in multi-center clinical trials, or optimizing liver imaging workflows, adherence to the QIBA profile brings rigor and reproducibility to quantitative liver stiffness imaging.

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MRE quantitatively measures liver stiffness — a surrogate for fibrosis and early disease progression — with strong evidence of accuracy and reproducibility. Standardizing how that measurement is performed and interpreted lowers variability and enhances its value as a biomarker in both clinical practice and drug development.

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Context-specific performance thresholds

 

​The QIBA Profile’s ≥19% change threshold reflects reproducible performance across heterogeneous, real-world clinical environments. In controlled clinical trial settings — where acquisition protocols, site training, QA, and central analysis are more rigorous — achievable repeatability is often substantially tighter. As a result, smaller thresholds (e.g., ~10%) may be appropriate and should be prospectively defined in the statistical analysis plan at the outset of a trial to support sensitive detection of treatment effects.

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