Evidence map›Paper›PMID 41335252›Full record

ReviewSkeletal radiology2026

Acute and chronic injury of the knee articular cartilage: prevalence, injury mechanisms, MRI assessment and association with osteoarthritis.

Adrian A Marth, Thomas M Link

Abstract readReview
In one paragraph

Review in Skeletal radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Adrian A MarthDepartment of Radiology and Biomedical Imaging, University of California, 185 Berry Street, San Francisco, CA, 94107, USA. adrian.marth@ucsf.edu.ORCID http://orcid.org/0000-0002-7334-0757
Thomas M LinkDepartment of Radiology and Biomedical Imaging, University of California, 185 Berry Street, San Francisco, CA, 94107, USA.

Funding

Understanding the mechanisms by which weight change affects progression of knee osteoarthritis in obese and overweight individuals: An analysis of the Osteoarthritis Initiative DatasetR01AR078917 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GABRIELLE JOSEPH, THOMAS M LINK · 2021 to 2026
$3.4M
NIAMS NIH HHS R01 AR078917NIH HHS R01-AR078917
6 · The paper itself

Abstract

Knee articular cartilage lesions resulting from acute or chronic injury are frequently encountered in routine clinical magnetic resonance imaging (MRI). Acute lesions typically occur following recreational or athletic activity and are often associated with concomitant internal knee derangements, whereaschronic lesions are thought to result from repetitive loading that exceeds physiological thresholds in both magnitude and frequency. Accurate characterization of cartilage lesion size, depth, and subchondral bone involvement is clinically relevant, as it directly influences therapeutic decision-making. In clinical practice, MRI evaluation of the knee cartilage is primarily performed using intermediate-weighted, two-dimensional fast spin-echo sequences, preferably with high spatial resolution and at 3 Tesla. Looking ahead, machine learning approaches hold promise for improving the prediction of osteoarthritis by integrating pathologic imaging findings with complementary sources of information such as clinical parameters, quantitative biomarkers, and patient-reported outcomes.

Indexed as

Cartilage, ArticularKnee InjuriesMagnetic Resonance ImagingOsteoarthritis, KneeAcute DiseaseChronic DiseaseHumansPrevalenceCartilageDefectsKneeMagnetic resonance imagingOsteoarthritis

Identifiers

PMID41335252
PMCPMC12952286

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

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 Socratic graph.