Identifying Out-of-Voxel Echoes in Edited MRS With Phase Cycle Inversion.

Area of Science:

• Magnetic Resonance Imaging (MRI)
• Spectroscopy
• Signal Processing

Background:

• Out-of-voxel (OOV) signals are artifacts in MRI that can contaminate spectral data.
• Understanding the origin of OOV signals is crucial for improving spectral quality.
• Coherence Transfer Pathways (CTP) formalism provides a framework for analyzing signal behavior in MRI.

Purpose of the Study:

• To identify the origin of OOV signals using the CTP formalism.
• To leverage signal phase information from acquisition phase cycling schemes.
• To enable optimization of crusher gradients for OOV signal suppression.

Main Methods:

• A novel approach, phase cycle inversion (PCI), was developed to identify OOV signals.
• PCI modifies receiver phases to match phase evolutions of unwanted CTPs.
• The method was validated using MEGA-edited PRESS and STEAM sequences in simulations, phantom, and in vivo experiments.

Main Results:

• PCI successfully separated signals from different CTPs in simulations.
• The CTP responsible for OOV signals was identified in phantom and in vivo experiments.
• Optimized crusher gradients based on identified OOV-associated CTPs led to cleaner spectra.

Conclusions:

• PCI is a flexible and generalizable method for diagnosing the CTP origin of OOV signals.
• The approach is applicable across various pulse sequences and voxel locations.
• This technique aids in improving spectral quality by enabling targeted OOV signal suppression.