Evidence map›Paper›PMID 39330752›Full record

ReviewTomography (Ann Arbor, Mich.)2024

Magnetic Resonance Imaging Biomarkers of Muscle.

Usha Sinha, Shantanu Sinha

Abstract readReview
In one paragraph

Review in Tomography (Ann Arbor, Mich.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Review
  6. Optoacoustic muscle imaging.Journal of neuromuscular diseases · 2026
    Review
  7. Article
  8. Article
  9. Article
  10. Overuse-Induced Muscle Disorder: Establishing a Rat Model to Unravel the Role of Fibro-Adipogenic Progenitor Cells in Intramuscular Fibrosis.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2025
    Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Review
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

2 authors.

Usha SinhaDepartment of Physics, San Diego State University, San Diego, CA 92182, USA.
Shantanu SinhaMuscle Imaging and Modeling Lab., Department of Radiology, University of California at San Diego, San Diego, CA 92037, USA.

Funding

Role of the Extracellular Matrix in Age-Associated Strength Loss: Combining Imaging and Biochemistry to create a Multi-Scale Mesh-free ModelR01AG056999 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SINHA, SHANTANU · 2018 to 2022
$3.1M
NIA NIH HHS R01 AG056999NIH/ National Institute of Aging R01AG056999.
6 · The paper itself

Abstract

This review is focused on the current status of quantitative MRI (qMRI) of skeletal muscle. The first section covers the techniques of qMRI in muscle with the focus on each quantitative parameter, the corresponding imaging sequence, discussion of the relation of the measured parameter to underlying physiology/pathophysiology, the image processing and analysis approaches, and studies on normal subjects. We cover the more established parametric mapping from T1-weighted imaging for morphometrics including image segmentation, proton density fat fraction, T2 mapping, and diffusion tensor imaging to emerging qMRI features such as magnetization transfer including ultralow TE imaging for macromolecular fraction, and strain mapping. The second section is a summary of current clinical applications of qMRI of muscle; the intent is to demonstrate the utility of qMRI in different disease states of the muscle rather than a complete comprehensive survey.

Indexed as

BiomarkersMagnetic Resonance ImagingMuscle, SkeletalDiffusion Tensor ImagingHumansImage Processing, Computer-AssistedMuscular DiseasesBiomarkersdiffusion tensor imagingfat fractionneuromuscular disease biomarkerquantitative muscle MRIT2 mapping

Identifiers

PMID39330752
PMCPMC11436019

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.