Wave-CAIPI for highly accelerated 3D imaging.

Area of Science:

• Magnetic Resonance Imaging (MRI)
• Parallel Imaging Techniques
• Image Reconstruction Algorithms

Background:

• Accelerated 3D MRI is crucial for reducing scan times and improving patient comfort.
• Existing parallel imaging methods often face trade-offs between acceleration, g-factor, and artifact levels.
• Controlled aliasing in parallel imaging (CAIPI) has shown promise in mitigating these trade-offs.

Purpose of the Study:

• To introduce and evaluate the wave-CAIPI acquisition and reconstruction technique.
• To achieve highly accelerated 3D MRI with negligible g-factor and artifact penalties.
• To demonstrate the utility of wave-CAIPI for high-resolution imaging and quantitative susceptibility mapping.

Main Methods:

• Wave-CAIPI employs sinusoidal gradients during readout and a modified 3D phase encoding strategy.
• This approach distributes aliasing evenly across spatial dimensions, leveraging 3D coil sensitivity.
• An efficient, convolution-based reconstruction method is proposed, avoiding data gridding.

Main Results:

• Wave-CAIPI enables 1 mm isotropic resolution, R = 3x3 accelerated full-brain imaging at 3T and 7T.
• Maximum g-factors were as low as 1.08 at 3T and 1.05 at 7T.
• Compared to 2D-CAIPI and bunched phase encoding, wave-CAIPI reduced maximum g-factors by up to two-fold for nine-fold acceleration.

Conclusions:

• Wave-CAIPI facilitates highly accelerated 3D MRI acquisitions.
• The technique offers low artifact levels and negligible g-factor penalties.
• Wave-CAIPI holds potential for advancing clinical high-resolution volumetric imaging.