Prospective motion correction with data reacquisition based on fat navigators for T1-weighted brain MRI at 3T

Area of Science:

• Medical Imaging
• Neuroimaging
• Magnetic Resonance Imaging

Background:

• T1-weighted (T1w) MRI is crucial for clinical and research applications at 3 Tesla.
• Image quality in T1w MRI is highly susceptible to motion artifacts, limiting diagnostic accuracy.
• Existing motion correction methods may not fully eliminate residual artifacts.

Purpose of the Study:

• To develop and evaluate a robust prospective motion correction (PMC) method for 3T T1w MRI using fat navigators (FatNav).
• To assess the effectiveness of data reacquisition in further reducing motion-induced artifacts after PMC.
• To quantify the impact of PMC and reacquisition on image quality metrics and brain volumes.

Main Methods:

• A PMC technique utilizing fat navigators (FatNav) was implemented for real-time motion correction in T1w MRI.
• Data segments with motion scores exceeding a predefined threshold were reacquired to minimize residual artifacts.
• Image quality was evaluated using visual assessment, blurriness, Signal-to-Noise Ratio (SNR), Peak Signal-to-Noise Ratio (PSNR), and cortical/white matter volumes in 26 participants (20 adults, 6 children).

Main Results:

• PMC with reacquisition significantly improved visual artifact scores (1.42 to 3.67) and reduced blurriness by 18.6% (p=0.001) in controlled motion scans.
• Cortical volume, SSIM, and PSNR showed significant increases with PMC (p<0.05).
• A linear relationship was observed between image quality metrics and the number of reacquired volumes, particularly when motion scores exceeded a specific threshold.

Conclusions:

• FatNav-based PMC is an effective strategy for mitigating motion artifacts in 3T T1w MRI.
• Selective data reacquisition based on motion thresholds offers a valuable method for further enhancing image quality.
• The combined approach improves the reliability and accuracy of T1w MRI in both research and clinical settings.