Motion-robust diffusion tensor acquisition at routine 3T magnetic resonance imaging.

Area of Science:

• Medical Imaging
• Neuroimaging
• Diffusion Tensor Imaging

Background:

• Motion artifacts are a significant challenge in diffusion tensor imaging (DTI).
• These artifacts can compromise the accuracy of diffusion tensor estimation.
• Optimizing acquisition and reconstruction is crucial for improving image quality.

Purpose of the Study:

• To evaluate if optimizing k-space acquisition and reconstruction methods can decrease motion artifacts in DTI.
• To compare different acquisition and reconstruction techniques in phantom and human studies.

Main Methods:

• Diffusion tensor images were acquired from a water phantom with varying table displacements (1-3 mm).
• Images were reconstructed using homodyne and zero-fill methods with 8- and 16-k(y) overscanning.
• Artifacts were assessed visually and statistically (Wilcoxon signed-ranks test); fractional anisotropy (FA) changes were compared.

Main Results:

• Zero filling with 16-k(y) overscan significantly reduced artifacts for smaller displacements (1-2 mm).
• Significant differences were observed in reconstruction (P < 0.031) and overscanning methods (P < 0.016).
• Human studies showed significant artifact reduction (P < 0.005).

Conclusions:

• Optimizing acquisition and reconstruction methods effectively reduces motion-induced artifacts in DTI.
• These optimized techniques provide a robust method for estimating diffusion tensors.
• The findings support improved DTI data quality in clinical settings.