MRI with TRELLIS: a novel approach to motion correction

Area of Science:

• Magnetic Resonance Imaging (MRI)
• Biomedical Engineering
• Medical Imaging Technology

Background:

• Motion artifacts significantly degrade the quality of MRI scans.
• Existing motion correction techniques can be complex and may not utilize all acquired data efficiently.

Purpose of the Study:

• To introduce and evaluate TRELLIS, a novel motion-correcting pulse sequence and reconstruction algorithm for MRI.
• To demonstrate the effectiveness of TRELLIS in quantifying and correcting object motion during MRI acquisition.

Main Methods:

• k-Space is filled using orthogonal overlapping strips with alternating phase- and frequency-encoding directions.
• The overlap between strips facilitates signal averaging and forms a system of equations to quantify motion.
• TRELLIS utilizes all acquired data for both motion detection and image reconstruction.

Main Results:

• Simulations with computer-generated phantoms demonstrated TRELLIS's effectiveness.
• Experiments with a purpose-built moving phantom validated the algorithm's performance.
• Successful application in human subjects confirmed the method's efficacy in real-world scenarios.

Conclusions:

• TRELLIS provides an effective solution for motion correction in MRI.
• The uniform k-space sampling and comprehensive data utilization offer advantages over existing methods.
• TRELLIS enhances image reconstruction accuracy by simultaneously addressing motion artifacts.