Evidence map›Paper›PMID 34738252›Full record

ArticleMagnetic resonance in medicine2022

Optimization of spin-lock times in T

Marcelo V W Zibetti, Azadeh Sharafi, Ravinder R Regatte

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Detection of Early Knee Osteoarthritis Using Multi-Component TJournal of magnetic resonance imaging : JMRI · 2026
    Article
  2. Early Knee Osteoarthritis Detection by Multi-Component TBioengineering (Basel, Switzerland) · 2026
    Article
  3. Highly Accelerated TNMR in biomedicine · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Simultaneous Bilateral TJournal of magnetic resonance imaging : JMRI · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Optimization of spin-lock times for TScientific reports · 2022
    Article
  18. 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

3 authors.

Marcelo V W ZibettiCenter for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.ORCID 0000-0003-2856-3625
Azadeh SharafiCenter for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.ORCID 0000-0001-9572-4922
Ravinder R RegatteCenter for 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 Christopher M Collins · 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
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 R21 AR075259NIBIB NIH HHS P41 EB017183
6 · The paper itself

Abstract

purposeTo compare different optimization approaches for choosing the spin-lock times (TSLs), in spin-lattice relaxation time in the rotating frame (T

methodsOptimization criteria for TSLs based on Cramér-Rao lower bounds (CRLB) are compared with matched sampling-fitting (MSF) approaches for T

resultsAll optimized criteria were better than non-optimized ones. However, we observe that a modified CRLB and an MSF based on the mean of the normalized absolute error (MNAE) were more robust optimization approaches, performing well in all tested cases. The optimized TSLs obtained the best performance with synthetic data (3.5-8.0% error), model phantoms (1.5-2.8% error), and healthy volunteers (7.7-21.1% error), showing stable and improved quality results, comparing to non-optimized approaches (4.2-13.3% error on synthetic data, 2.1-6.2% error on model phantoms, 9.8-27.8% error on healthy volunteers).

conclusionA modified CRLB and the MSF based on MNAE are robust optimization approaches for choosing TSLs in T

Indexed as

Cartilage, ArticularMagnetic Resonance ImagingHumansKneeKnee JointPhantoms, ImagingCramér-Rao boundsquantitative MRIspin-lock timesT1ρ relaxation

Identifiers

PMID34738252
PMCPMC8822470

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.