Evidence map›Paper›PMID 38904746›Full record

ReviewMagma (New York, N.Y.)2024

Quantitative MRI methods for the assessment of structure, composition, and function of musculoskeletal tissues in basic research and preclinical applications.

Victor Casula, Abdul Wahed Kajabi

Abstract readReview
In one paragraph

Review in Magma (New York, N.Y.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. 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.

Victor CasulaResearch Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland. victor.casula@oulu.fi.ORCID http://orcid.org/0000-0003-0447-2796
Abdul Wahed KajabiCenter for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA.

Funding

TRD4 - Ultrahigh Field Engineering and SafetyP41EB027061 · NIBIB · UNIVERSITY OF MINNESOTA · PI Mehmet Akcakaya · 2019 to 2026
$11.7M
Advanced 7 Tesla imaging of the knee for root cause of OsteoarthritisR01EB034575 · NIBIB · UNIVERSITY OF MINNESOTA · PI Jutta M Ellermann, Gregory John Metzger · 2023 to 2026
$2.1M
NIBIB NIH HHS P41 EB027061NIBIB NIH HHS R01 EB034575NIBIB NIH HHS R01EB034575
6 · The paper itself

Abstract

Osteoarthritis (OA) is a disabling chronic disease involving the gradual degradation of joint structures causing pain and dysfunction. Magnetic resonance imaging (MRI) has been widely used as a non-invasive tool for assessing OA-related changes. While anatomical MRI is limited to the morphological assessment of the joint structures, quantitative MRI (qMRI) allows for the measurement of biophysical properties of the tissues at the molecular level. Quantitative MRI techniques have been employed to characterize tissues' structural integrity, biochemical content, and mechanical properties. Their applications extend to studying degenerative alterations, early OA detection, and evaluating therapeutic intervention. This article is a review of qMRI techniques for musculoskeletal tissue evaluation, with a particular emphasis on articular cartilage. The goal is to describe the underlying mechanism and primary limitations of the qMRI parameters, their association with the tissue physiological properties and their potential in detecting tissue degeneration leading to the development of OA with a primary focus on basic and preclinical research studies. Additionally, the review highlights some clinical applications of qMRI, discussing the role of texture-based radiomics and machine learning in advancing OA research.

Indexed as

Cartilage, ArticularMagnetic Resonance ImagingOsteoarthritisAnimalsHumansImage Processing, Computer-AssistedJointsMachine LearningMusculoskeletal SystemCartilageMagnetic resonance imagingMeniscusMusclesOsteoarthritis

Identifiers

PMID38904746
PMCPMC11582218

What OpenQuestion holds

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LicenceCC BY
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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.