SENSE and simultaneous multislice imaging.

Area of Science:

• Magnetic Resonance Imaging (MRI)
• Medical Imaging Technology
• Image Reconstruction Algorithms

Background:

• Simultaneous multislice (SMS) acquisitions are crucial for accelerating single-shot MRI.
• Increasing imaging speed is a key challenge in MRI acquisition.
• Sensitivity encoding (SENSE) is a vital technique in parallel MRI.

Purpose of the Study:

• To demonstrate the application of two-dimensional sensitivity encoding (2D-SENSE) for reconstructing simultaneous multislice (SMS) acquisitions.
• To show that 2D-SENSE can handle periodic but otherwise arbitrary undersampling patterns in SMS imaging.
• To validate 2D-SENSE for accelerated MRI scans.

Main Methods:

• A 3D k-space representation of the SMS sampling process was adopted.
• The reconstruction problem was framed as a 2D problem, equivalent to volumetric CAIPIRINHA.
• The SENSE algorithm was applied to reconstruct undersampled data.

Main Results:

• 2D-SENSE successfully reconstructed in vivo brain data from SMS-EPI and SMS-RARE acquisitions.
• The method demonstrated effectiveness with various acceleration factors and CAIPIRINHA shifts.
• The reconstruction accommodates non-integer undersampling in the slice direction using 'dummy slices'.

Conclusions:

• 2D-SENSE offers a conceptually simple, one-step reconstruction for both undersampled dimensions.
• This approach provides contrast-independent parallel imaging reconstruction for SMS acquisitions.
• The method enhances imaging speed and efficiency in MRI.