Evidence map›Paper›PMID 35129777›Full record

ReviewGeroScience2022

New imaging tools for mouse models of osteoarthritis.

S Drevet, B Favier, B Lardy, G Gavazzi, E Brun

Open access · greenAbstract readReview
In one paragraph

Review in GeroScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.7field-weighted citation impact, top 10% of its field
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

12 citing papers in PubMed, 17 citations in OpenAlex.

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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

5 authors at 4 institutions in 1 country.

S DrevetUniv. Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000, Grenoble, France. sdrevet@chu-grenoble.fr.
B FavierUniv. Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000, Grenoble, France.
B LardyUniv. Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000, Grenoble, France.
G GavazziUniv. Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000, Grenoble, France.
E BrunUniv. Grenoble Alpes, Inserm, UA7, STROBE Laboratory, 38 000, Grenoble, France.
Centre Hospitalier Universitaire de Grenoble · FRInserm · FRUniversité Grenoble Alpes · FRVetAgro Sup · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osteoarthritis (OA) is a chronic degenerative disease characterized by a disruption of articular joint cartilage homeostasis. Mice are the most commonly used models to study OA. Despite recent reviews, there is still a lack of knowledge about the new development in imaging techniques. Two types of modalities are complementary: those that assess structural changes in joint tissues and those that assess metabolism and disease activity. Micro MRI is the most important imaging tool for OA research. Automated methodologies for assessing periarticular bone morphology with micro-CT have been developed allowing quantitative assessment of tibial surface that may be representative of the whole OA joint changes. Phase-contrast X-ray imaging provides in a single examination a high image precision with good differentiation between all anatomical elements of the knee joint (soft tissue and bone). Positron emission tomography, photoacoustic imaging, and fluorescence reflectance imaging provide molecular and functional data. To conclude, innovative imaging technologies could be an alternative to conventional histology with greater resolution and more efficiency in both morphological analysis and metabolism follow-up. There is a logic of permanent adjustment between innovations, 3R rule, and scientific perspectives. New imaging associated with artificial intelligence may add to human clinical practice allowing not only diagnosis but also prediction of disease progression to personalized medicine.

Indexed as

Cartilage, ArticularOsteoarthritis, KneeAnimalsArtificial IntelligenceDisease Models, AnimalKnee JointMiceX-Ray MicrotomographyImagingInnovationMouse modelsOsteoarthritisTechnologies

Identifiers

PMID35129777
PMCPMC9135906
OpenAlexW4210905172

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.