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Constrained Ellipse Fitting for Efficient Parameter Mapping With Phase-Cycled bSSFP MRI.

Kubra Keskin, Ugur Yilmaz, Tolga Cukur

    IEEE Transactions on Medical Imaging
    |August 5, 2021
    PubMed
    Summary
    This summary is machine-generated.

    Constrained Ellipse Fitting (CELF) improves magnetic resonance imaging (MRI) by enabling accurate, efficient parameter estimation in balanced steady-state free precession (bSSFP) sequences using fewer scans.

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    Area of Science:

    • Magnetic Resonance Imaging (MRI)
    • Biomedical Engineering
    • Medical Physics

    Background:

    • Balanced steady-state free precession (bSSFP) MRI offers high scan efficiency but is sensitive to field inhomogeneity and provides non-standard T1-weighted contrast.
    • Conventional methods mitigate these issues using multiple phase-cycled acquisitions, but parameter estimation often requires numerous scans (N ≈ 10-16), reducing efficiency.

    Purpose of the Study:

    • To develop a novel, efficient, and accurate method for parameter estimation in phase-cycled bSSFP MRI.
    • To reduce the number of required acquisitions for reliable parameter mapping.

    Main Methods:

    • Proposed Constrained Ellipse Fitting (CELF) method based on the elliptical signal model for complex bSSFP signals.
    • Incorporated geometrical constraints and dictionary-based identification to enhance estimation efficiency and accuracy.
    • Utilized a separate T1 map to mitigate flip angle variation sensitivity.

    Main Results:

    • CELF accurately generates off-resonance and banding-free bSSFP maps with as few as N = 4 acquisitions.
    • Demonstrated improved efficiency and accuracy compared to existing model-based methods.
    • Identified limitations in relaxation parameter estimation accuracy due to bSSFP's microstructural sensitivity.

    Conclusions:

    • CELF offers a significant advancement in efficient and accurate parameter mapping for bSSFP MRI.
    • The method reduces scan time while maintaining high-quality image generation.
    • Further research may be needed to address biases in relaxation parameter estimation inherent to bSSFP imaging.