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Related Experiment Videos

Automated Liver Elasticity Calculation for 3D MRE.

Bogdan Dzyubak1, Kevin J Glaser1, Armando Manduca1

  • 1Department of Radiology, Mayo Clinic, Rochester, MN.

Proceedings of Spie--The International Society for Optical Engineering
|October 17, 2017
PubMed
Summary

An automated algorithm accurately calculates liver stiffness from 3D Magnetic Resonance Elastography (MRE) data. This new method improves reproducibility and precision for diagnosing liver fibrosis.

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Area of Science:

  • Medical Imaging
  • Biomedical Engineering
  • Quantitative MRI

Background:

  • Magnetic Resonance Elastography (MRE) is a clinical tool for diagnosing liver fibrosis by quantifying tissue stiffness.
  • Automated analysis of MRE is challenging due to image artifacts and limitations in 3D acquisitions.
  • Existing 2D MRE methods have automated algorithms, but 3D MRE lacks confidence mapping for quality assessment.

Purpose of the Study:

  • To extend a validated 2D automated MRE analysis algorithm for use with 3D MRE data.
  • To develop and validate a simple wave-amplitude metric for 3D MRE processing.
  • To assess the accuracy, precision, and reproducibility of the automated algorithm for 3D MRE liver stiffness quantification.

Main Methods:

  • An extension of a 2D automated algorithm was developed for 3D MRE, incorporating a wave-amplitude metric.
Keywords:
AutomationCADElastographyLiverMREROISegmentationStiffness

Related Experiment Videos

  • The algorithm was validated against an expert reader using 57 patient MRE exams (both 2D and 3D).
  • Performance metrics included stiffness discrepancy and comparison with 2D MRE and inter-reader variability.

    • Main Results:

    • The automated liver elasticity calculation (ALEC) algorithm demonstrated minimal bias and good precision for 3D MRE stiffness quantification.
    • Stiffness discrepancy for 3D MRE was -0.8% ± 9.45%, outperforming 2D MRE (-3.2% ± 10.43%) and prior inter-reader results.
    • No automated processing failures occurred in the evaluated dataset, indicating robustness.

    Conclusions:

    • The ALEC algorithm successfully enables reproducible and precise stiffness measurements from 3D MRE datasets.
    • This automated approach facilitates the analysis of large 3D MRE datasets, improving clinical diagnostic capabilities.
    • The validated algorithm addresses limitations in 3D MRE processing, enhancing its utility for liver fibrosis assessment.