Keywords: Oxygenation, Neuro, quantitative BOLD
Motivation: Standard low-resolution 2D-GRE acquisition for T2* mapping in mqBOLD MRI may suffer from long scan durations and insufficient quantification accuracy.
Goal(s): Improving quantification accuracy by switching from 2D to high-resolution 3D multi-echo GRE while simultaneously reducing scan duration by applying compressed sensing (CS) acceleration with deep-learning-based reconstruction.
Approach: T2* maps from low-resolution 2D-GRE and high-resolution 3D-GRE with different acceleration factors were compared in 11 healthy volunteers based on visual inspection and VOI-analyses.
Results: 3D-GRE yields high-resolution parameter maps with improved T2* values for GM/WM in less than half the scan duration compared to standard 2D-GRE when using CS acceleration with DL-based reconstruction.
Impact: High-resolution 3D-GRE with compressed sensing acceleration and deep-learning-based reconstruction was compared to standard 2D-GRE visually and quantitatively. 3D-GRE enables clinically feasible scan durations with improved and reliable T2* mapping, which may add to the clinical applicability of oxygenation-sensitive mqBOLD MRI.
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