PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 17, 2026Magnetic Resonance in Medicine1 citations

GRACE ‐ MORE : A Motion‐Resolved Golden‐Angle Radial CEST MRI Technique for Free‐Breathing Abdominal Imaging

View Full Paper
YFYitian FanCBChongxue BieXJXinding Jiang

Key Points

  • This research aims to develop a new imaging framework for reliable abdominal CEST MRI during free breathing.
  • Developed GRACE-MORE framework utilizing golden-angle radial sampling for CEST MRI.
  • Implemented respiratory-phase binning with self-gated strategy and advanced sorting techniques.
  • Reconstruction performed using a deep learning network with low-rank and sparsity constraints.
  • Achieved over threefold improvement in binning accuracy compared to conventional methods.
  • Demonstrated reduced reconstruction error and higher peak signal-to-noise ratio in simulations.
  • In vivo results showed a fourfold increase in Z-spectral signal-to-noise ratio.

Abstract

PURPOSE: To develop a motion-resolved acquisition and reconstruction framework for motion-robust and spectrally reliable abdominal CEST imaging under free-breathing conditions. THEORY AND METHODS: A framework termed Golden-angle RAdial CEST MRI with MOtion-REsolved reconstruction (GRACE-MORE) was developed to improve acquisition, respiratory-phase binning, and reconstruction. An interleaved steady-state saturation module with golden-angle radial sampling was adopted to enhance saturation efficiency and ensure uniform k-space coverage. Respiratory-phase binning was performed using a self-gated strategy, in which respiratory amplitude and phase were extracted from central k-space via principal component analysis, followed by hybrid empirical mode decomposition-continuous wavelet transform sorting to correct baseline drift and irregular breathing. Reconstruction was performed using a deep unrolled network constrained by low-rank and sparsity priors, which incorporated a modified U-Net with channel attention and a sliding-window grouping scheme to capture spatio-spectral correlations across saturation offsets. RESULTS: Validation on simulated, preclinical, and clinical datasets demonstrated more than a threefold improvement in binning accuracy compared with conventional methods. GRACE-MORE reduced reconstruction error, yielded a higher structural similarity index and peak signal-to-noise ratio in simulations, and achieved improved anatomical fidelity, effective motion suppression, and up to a fourfold increase in Z-spectral signal-to-noise ratio in vivo. CONCLUSION: GRACE-MORE enables motion-robust and spectrally reliable abdominal CEST imaging under free-breathing conditions.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Fan et al. (2026) studied this question.

synapsesocial.com/papers/6a095b3f7880e6d24efe10b0https://doi.org/10.1002/mrm.70434
Ask AI
Helpful
Bookmark
Share
View Full Paper

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Image metric-based correction (Autocorrection) of motion effects: Analysis of image metrics2000 · 134 citations
  2. 2MRI of GlycoNOE in the human liver using GraspNOE ‐Dixon2024 · 7 citations
  3. 3Comparative Analysis of Wavelet Transform for Time-Frequency Analysis and Transient Localization in Structural Health Monitoring2021 · 111 citations
  4. 4Liver stiffness assessment by tagged MRI of cardiac‐induced liver motion2011 · 47 citations
  5. 5Image quality assessment: from error visibility to structural similarity2004 · 57,912 citations