Robust motion correction in CEST imaging exploiting low-rank approximation of the z-spectrum

Area of Science:

• Medical Imaging
• Biophysics
• Computational Biology

Background:

• Chemical Exchange Saturation Transfer (CEST) imaging is sensitive to motion artifacts.
• Accurate quantification in CEST is crucial for diagnostic applications.
• Existing motion correction methods may not adequately address complex motion in dynamic CEST acquisitions.

Purpose of the Study:

• To introduce and evaluate a novel image registration technique for robust quantification of CEST acquisitions corrupted by motion.
• To assess the efficacy of the proposed method in correcting both rigid and nonrigid motion.
• To improve the diagnostic value of CEST imaging through motion artifact reduction.

Main Methods:

• An iterative algorithm exploiting a low-rank approximation of the z-spectrum (LRAZ) was developed.
• The method gradually separates contrast variations due to off-resonance saturation and motion.
• Testing involved creatine CEST analysis in phantoms with simulated rigid motion and human thigh acquisitions during exercise.

Main Results:

• LRAZ registration of corrupted phantom data yielded a normalized RMS error of less than 4% compared to the gold standard.
• Creatine maps derived from registered data showed minimal differences from non-corrupted data.
• The technique effectively corrected nonrigid motion in dynamic skeletal muscle CEST acquisitions, outperforming conventional methods on complex human thigh motion.

Conclusions:

• The introduced LRAZ method enables robust registration of CEST image series affected by rigid and nonrigid motion.
• This technique significantly enhances the diagnostic value across various CEST applications.
• The LRAZ approach provides superior motion correction compared to conventional methods for complex biological tissues.