Evidence map›Paper›PMID 42437108›Full record

ArticleOsteoarthritis and cartilage open2026

Deep learning-based effusion-synovitis volume measured on MRI is associated with osteoarthritis progression: A longitudinal analysis of data from the osteoarthritis initiative.

Adrian A Marth, Felix Liu, Ethan Pan, Sevtap T Ulas, John A Lynch, Alexandra S Gersing, Nancy E Lane, Michael C Nevitt, Charles E McCulloch, Thomas M Link and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Osteoarthritis and cartilage open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Adrian A MarthDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, USA.
Felix LiuDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, USA.
Ethan PanDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, USA.
Sevtap T UlasDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, USA.
John A LynchDepartment of Epidemiology and Biostatistics, University of California, San Francisco, USA.
Alexandra S GersingDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, USA.
Nancy E LaneDepartment of Internal Medicine, U.C. Davis Health, Sacramento, CA, USA.
Michael C NevittDepartment of Epidemiology and Biostatistics, University of California, San Francisco, USA.
Charles E McCullochDepartment of Epidemiology and Biostatistics, University of California, San Francisco, USA.
Thomas M LinkDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, USA.
Gabby B JosephDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, 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
The Study of Muscle, Mobility and Aging with Knee OAR01AG070647 · NIA · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Nancy E Lane · 2021 to 2026
$2.5M
Impact of Weight loss on Knee Joint Biochemical and Structural DegenerationR01AR064771 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LINK, THOMAS M · 2014 to 2019
$1.6M
NIAMS NIH HHS R01 AR064771NIAMS NIH HHS R01 AR078917NIA NIH HHS R01 AG070647
6 · The paper itself

Abstract

Objective: To investigate whether the 48-month change in effusion-synovitis volume (ΔESV) is associated with concurrent knee osteoarthritis progression, and to compare these associations with those of semiquantitative change in effusion-synovitis using the MRI Osteoarthritis Knee Score (ΔMOAKS). Design: In this study using data from the Osteoarthritis Initiative conducted from 02/2004-10/2015, deep learning-based measurements of knee ESV were derived from baseline and 48-month follow-up knee MRI (n = 2469). OA outcomes included change of Kellgren-Lawrence (KL) grade, Whole-Organ Magnetic Resonance Imaging Score (WORMS) and its subscales (meniscus, bone marrow edema-like lesions [BMELL], cartilage), and symptom progression by the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Associations of ESV change (ΔESV) with OA outcome changes were evaluated using spline-based regression models. Effect sizes were reported as interdecile differences (IDDs; 90th vs 10th percentile of the exposure). To compare the associations between ΔESV and ΔMOAKS, differences in IDD (ΔIDD) were estimated. Results: ΔESV was significantly associated with ΔKL grade, ΔWORMS Conclusions: Longitudinal change in ESV was associated with concurrent imaging-based and symptomatic osteoarthritis progression over 48 months. Compared with changes in MOAKS scores, ΔESV showed stronger associations with imaging-based OA outcomes. These findings underscore the potential of MRI-based ΔESV as an osteoarthritis imaging biomarker, while further studies are needed to establish its predictive and clinical utility.

Indexed as

BiomarkersDeep learningKneeMagnetic resonance imagingOsteoarthritisSynovitis

Identifiers

PMID42437108
PMCPMC13355676

What Socratic holds

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LicenceCC BY
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Registered trials

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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.