Evidence map›Paper›PMID 37010113›Full record

ReviewJournal of magnetic resonance imaging : JMRI2023

Updates on Compositional MRI Mapping of the Cartilage: Emerging Techniques and Applications.

Marcelo V W Zibetti, Rajiv G Menon, Hector L de Moura, Xiaoxia Zhang, Richard Kijowski, Ravinder R Regatte

Abstract readReview
In one paragraph

Review in Journal of magnetic resonance imaging : JMRI, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Article
  2. Correlation between functional impairment and quantitative MRI assessment of ankle cartilage in chronic ankle instability.Asia-Pacific journal of sports medicine, arthroscopy, rehabilitation and technology · 2026
    Article
  3. Article
  4. Article
  5. Detection of Early Knee Osteoarthritis Using Multi-Component TJournal of magnetic resonance imaging : JMRI · 2026
    Article
  6. Article
  7. Review
  8. Article
  9. [EJNMMI research · 2025
    Article
  10. Article
  11. Review
  12. Review
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Review
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Marcelo V W ZibettiCenter of Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.ORCID 0000-0003-2856-3625
Rajiv G MenonCenter of Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.ORCID 0000-0001-6160-886X
Hector L de MouraCenter of Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.ORCID 0000-0002-6620-9814
Xiaoxia ZhangCenter of Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.ORCID 0000-0003-3620-6994
Richard KijowskiCenter of Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.ORCID 0000-0002-2781-2899
Ravinder R RegatteCenter of Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.ORCID 0000-0002-4607-7682

Funding

TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Daniel K Sodickson · 2014 to 2026
$19.3M
Multiparametric Mapping of Knee Joint with Magnetic Resonance FingerprintingR01AR076985 · NIAMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI REGATTE, RAVINDER · 2021 to 2025
$3.1M
Imaging Biomarkers of Knee OsteoarthritisR01AR068966 · NIAMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI REGATTE, RAVINDER · 2016 to 2021
$3.1M
Rapid Quantitative Assessment of Knee Joint with Compressed SensingR01AR076328 · NIAMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI REGATTE, RAVINDER · 2020 to 2024
$3.0M
Data-Driven Learning Framework for Fast Quantitative Knee Joint MappingR01AR078308 · NIAMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Ravinder Regatte, Marcelo Victor Wust Zibetti · 2021 to 2026
$2.6M
Intervertebral Disc Mechanics with Functional GRASP-MRIR21AR078357 · NIAMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI REGATTE, RAVINDER · 2021 to 2022
$408k
Zero Echo Time Imaging of Knee JointR21AR075259 · NIAMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI REGATTE, RAVINDER · 2020 to 2021
$403k
NIAMS NIH HHS R01 AR068966NIAMS NIH HHS R01 AR076328NIAMS NIH HHS R01 AR076985NIAMS NIH HHS R01 AR078308NIAMS NIH HHS R01-AR078308-01A1NIAMS NIH HHS R21 AR075259NIAMS NIH HHS R21 AR078357NIBIB NIH HHS P41 EB017183
6 · The paper itself

Abstract

Osteoarthritis (OA) is a widely occurring degenerative joint disease that is severely debilitating and causes significant socioeconomic burdens to society. Magnetic resonance imaging (MRI) is the preferred imaging modality for the morphological evaluation of cartilage due to its excellent soft tissue contrast and high spatial resolution. However, its utilization typically involves subjective qualitative assessment of cartilage. Compositional MRI, which refers to the quantitative characterization of cartilage using a variety of MRI methods, can provide important information regarding underlying compositional and ultrastructural changes that occur during early OA. Cartilage compositional MRI could serve as early imaging biomarkers for the objective evaluation of cartilage and help drive diagnostics, disease characterization, and response to novel therapies. This review will summarize current and ongoing state-of-the-art cartilage compositional MRI techniques and highlight emerging methods for cartilage compositional MRI including MR fingerprinting, compressed sensing, multiexponential relaxometry, improved and robust radio-frequency pulse sequences, and deep learning-based acquisition, reconstruction, and segmentation. The review will also briefly discuss the current challenges and future directions for adopting these emerging cartilage compositional MRI techniques for use in clinical practice and translational OA research studies. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Indexed as

Cartilage, ArticularMusculoskeletal SystemOsteoarthritis, KneeHumansLongitudinal StudiesMagnetic Resonance Imagingaccelerated relaxometrycompressed sensingdeep learningmagnetic resonance fingerprintingquantitative mapping

Identifiers

PMID37010113
PMCPMC10323700

What OpenQuestion holds

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Registered trials

None linked

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.