Motion-insensitive diffusion imaging of the brain using optical tracking and dynamic sequence updates.

Area of Science:

• Medical Imaging
• Neuroimaging
• Magnetic Resonance Imaging

Background:

• Diffusion-weighted imaging (DWI) is susceptible to head motion, leading to signal loss from gradient imbalances.
• Existing prospective motion correction methods often use bipolar diffusion gradients.
• Monopolar diffusion sequences are more common in clinical practice.

Purpose of the Study:

• To develop and evaluate a motion-insensitive implementation for monopolar diffusion sequences.
• To reduce motion artifacts in brain DWI using intrasequence motion updates.

Main Methods:

• Developed a monopolar diffusion sequence with motion updates before RF pulses and diffusion gradients.
• Tested the sequence in phantoms and human brains at b=1000 s/mm² with rotational velocities up to 20°/s.
• Compared motion sensitivity, signal loss, and in vivo image profiles with and without intrasequence motion updates.

Main Results:

• Intrasequence motion updates reduced DWI motion sensitivity sevenfold.
• Optimal results were achieved by matching the echo time to the tracking system's frame-to-frame period.
• Signal losses, dropouts, and DTI analysis quality measures were improved with intrasequence updates.

Conclusions:

• A correction scheme for monopolar DWI sequences effectively reduces motion sensitivity.
• This method offers up to a sevenfold reduction in motion sensitivity compared to standard implementations.