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Efficient estimation of gadolinium-based contrast agent concentration using transient-state keyhole MR-STAT
Fei Xu1, Edwin Versteeg1, Hongyan Liu1
1Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, UMC Utrecht, Utrecht, the Netherlands.
This study introduces an accelerated Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) method for fast, quantitative MRI. The technique accurately measures Gadolinium-based contrast agent (GBCA) concentrations, crucial for dynamic contrast-enhanced imaging.
Area of Science:
- Medical Imaging
- Biophysics
- Radiology
Background:
- Fast quantitative MRI (qMRI) enables multi-parameter quantification in brief scan times.
- Integrating qMRI into clinical protocols requires efficient post-contrast agent imaging.
- Current methods for tracking contrast agent concentration are time-prohibitive.
Purpose of the Study:
- To develop and validate an accelerated multi-parametric method for time-efficient estimation of Gadolinium-based contrast agent (GBCA) concentrations.
- To enable faster tracking of contrast agent dynamics in clinical MRI settings.
Main Methods:
- An accelerated 2D MR-STAT protocol was designed using transient-state acquisitions and Cartesian keyhole acceleration.
- GBCA concentrations were quantified in phantoms with varying gadobutrol concentrations (0.05–0.9 mM) based on reconstructed T1 values.
- Method validation involved linear regression analysis, synthetic patient data, and a hybrid human/phantom study.
Main Results:
- The accelerated MR-STAT protocol (undersampling factor of 4) accurately measured T1, T2, and GBCA concentrations.
- A strong linear relationship was observed between estimated and reference GBCA concentrations (slope=1.034, intercept=0.009).
Conclusions:
- A multi-parametric approach was developed for quantitative gadolinium concentration assessment in vitro and in a hybrid setup.
- The accelerated MR-STAT protocol measures gadobutrol concentrations (0.05–0.9 mM) within clinically applicable scan times.
- Further in vivo validation is required for this promising quantitative MRI technique.
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