Evidence map›Paper›PMID 29193260›Full record

ArticleMagnetic resonance in medicine2018

RACER-GRASP: Respiratory-weighted, aortic contrast enhancement-guided and coil-unstreaking golden-angle radial sparse MRI.

Li Feng, Chenchan Huang, Krishna Shanbhogue, Daniel K Sodickson, Hersh Chandarana, Ricardo Otazo

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed.

  1. Review
  2. Article
  3. Free-breathing phase-sensitive inversion recovery TMagnetic resonance in medicine · 2026
    Article
  4. Accelerated Abdominal MRI: A Review of Current Methods and Applications.Journal of magnetic resonance imaging : JMRI · 2025
    Review
  5. MRI of GlycoNOE in the human liver using GraspNOE-Dixon.Magnetic resonance in medicine · 2025
    Article
  6. Article
  7. Article
  8. A signal model for fat-suppressed TNMR in biomedicine · 2025
    Article
  9. Article
  10. Free-breathing, fat-corrected TMagnetic resonance in medicine · 2024
    Article
  11. Article
  12. Kz-accelerated variable-density stack-of-stars MRI.Magnetic resonance imaging · 2023
    Article
  13. Article
  14. Article
  15. Golden-Angle Radial MRI: Basics, Advances, and Applications.Journal of magnetic resonance imaging : JMRI · 2022
    Review
  16. Repeatability and robustness of MP-GRASP TMagnetic resonance in medicine · 2022
    Article
  17. Aliasing artifact reduction in spiral real-time MRI.Magnetic resonance in medicine · 2021
    Article
  18. Article
  19. Rapid 4D-MRI reconstruction using a deep radial convolutional neural network: Dracula.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2021
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Li FengCenter for Advanced Imaging Innovation and Research (CAI2R), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
Chenchan HuangCenter for Advanced Imaging Innovation and Research (CAI2R), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
Krishna ShanbhogueCenter for Advanced Imaging Innovation and Research (CAI2R), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
Daniel K SodicksonCenter for Advanced Imaging Innovation and Research (CAI2R), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
Hersh ChandaranaCenter for Advanced Imaging Innovation and Research (CAI2R), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
Ricardo OtazoCenter for Advanced Imaging Innovation and Research (CAI2R), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.

Funding

TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Hersh Chandarana · 2014 to 2026
$19.3M
Parallel MR Imaging: New Techniques and TechnologiesR01EB000447 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI SODICKSON, DANIEL K · 2002 to 2012
$5.1M
Comprehensive Motion-Robust Pediatric MR Imaging Using Radial AcquisitionsR01EB018308 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI CHANDARANA, HERSH · 2015 to 2018
$1.6M
NIBIB NIH HHS P41 EB017183NIBIB NIH HHS R01 EB000447NIBIB NIH HHS R01 EB018308
6 · The paper itself

Abstract

purposeTo develop and evaluate a novel dynamic contrast-enhanced imaging technique called RACER-GRASP (Respiratory-weighted, Aortic Contrast Enhancement-guided and coil-unstReaking Golden-angle RAdial Sparse Parallel) MRI that extends GRASP to include automatic contrast bolus timing, respiratory motion compensation, and coil-weighted unstreaking for improved imaging performance in liver MRI.

methodsIn RACER-GRASP, aortic contrast enhancement (ACE) guided k-space sorting and respiratory-weighted sparse reconstruction are performed using aortic contrast enhancement and respiratory motion signals extracted directly from the acquired data. Coil unstreaking aims to weight multicoil k-space according to streaking artifact level calculated for each individual coil during image reconstruction, so that coil elements containing a high level of streaking artifacts contribute less to the final results. Self-calibrating GRAPPA operator gridding was applied as a pre-reconstruction step to reduce computational burden in the subsequent iterative reconstruction. The RACER-GRASP technique was compared with standard GRASP reconstruction in a group of healthy volunteers and patients referred for clinical liver MR examination.

resultsCompared with standard GRASP, RACER-GRASP significantly improved overall image quality (average score: 3.25 versus 3.85) and hepatic vessel sharpness/clarity (average score: 3.58 versus 4.0), and reduced residual streaking artifact level (average score: 3.23 versus 3.94) in different contrast phases. RACER-GRASP also enabled automatic timing of the arterial phases.

conclusionsThe aortic contrast enhancement-guided sorting, respiratory motion suppression and coil unstreaking introduced by RACER-GRASP improve upon the imaging performance of standard GRASP for free-breathing dynamic contrast-enhanced MRI of the liver. Magn Reson Med 80:77-89, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Indexed as

RespirationAdultAlgorithmsAortaArtifactsBreath HoldingCluster AnalysisComputer SimulationContrast MediaData CompressionFemaleHumansImage Interpretation, Computer-AssistedImage Processing, Computer-AssistedImaging, Three-DimensionalLiverContrast Mediacoil unstreakingcompressed sensingDCE-MRIfree breathingliverRACER-GRASPradial imagingstreaking artifact

Identifiers

PMID29193260
PMCPMC5876099

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.