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SUPER: A blockwise curve-fitting method for accelerating MR parametric mapping with fast reconstruction.

Chenxi Hu1, Dana C Peters1

  • 1Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut.

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|January 19, 2019
PubMed
Summary
This summary is machine-generated.

Shift Undersampling improves Parametric mapping Efficiency and Resolution (SUPER) is a new method that accelerates parametric mapping. This technique significantly reduces reconstruction time and improves image quality in brain and cardiac imaging.

Keywords:
SUPERSUPER-SENSEblockwise curve-fittinghigh-resolution MOLLImodel-based reconstructionparametric mapping acceleration

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Medical Imaging Analysis
  • Computational Imaging

Background:

  • Parametric mapping in MRI is crucial for quantitative tissue characterization.
  • Current methods face limitations in reconstruction speed and efficiency.
  • Accelerating parametric mapping is essential for broader clinical adoption.

Purpose of the Study:

  • To introduce and evaluate Shift Undersampling improves Parametric mapping Efficiency and Resolution (SUPER), a novel blockwise curve-fitting method.
  • To demonstrate SUPER's capability for accelerating parametric mapping with very fast reconstruction.
  • To assess SUPER's performance against existing model-based reconstruction techniques.

Main Methods:

  • SUPER utilizes interleaved k-space undersampling for blockwise cost function decomposition, enhancing reconstruction efficiency.
  • The method was combined with SENSE for up to 4-fold acceleration.
  • Validation involved T1 mapping using simulations, phantom, and in vivo brain imaging (N=5), comparing SUPER/SUPER-SENSE with MARTINI and GRAPPATINI.
  • A novel SUPER-SENSE MOLLI cardiac T1-mapping sequence was developed and compared to standard MOLLI.

Main Results:

  • In brain imaging, 2-fold SUPER showed significantly lower NRMSE, d-factor, and TPV compared to 2-fold MARTINI.
  • 4-fold SUPER-SENSE demonstrated superior performance over 4-fold GRAPPATINI in NRMSE, d-factor, and TPV.
  • Cardiac SUPER-SENSE MOLLI achieved comparable myocardial T1, slightly lower blood T1, and improved spatial resolution within the same imaging time.

Conclusions:

  • SUPER and SUPER-SENSE offer efficient, model-based reconstruction for accelerated parametric mapping.
  • These methods enhance the clinical utility of parametric mapping techniques.
  • SUPER represents a significant advancement in fast and accurate parametric MRI reconstruction.