Evidence map›Paper›PMID 40113602›Full record

ArticleSkeletal radiology2025

Cartilage thickness distribution and its dependence on demographic, radiographic, and MRI structural pathology in knee osteoarthritis-data from the IMI-APPROACH cohort.

Mylène P Jansen, Tom D Turmezei, Kishan Dattani, Dimitri A Kessler, Simon C Mastbergen, Margreet Kloppenburg, Francisco J Blanco, Ida K Haugen, Francis Berenbaum, Wolfgang Wirth and 3 more

Abstract read
In one paragraph

Article in Skeletal radiology, 2025. 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

13 authors.

Mylène P JansenDepartment of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht, The Netherlands. m.p.jansen-36@umcutrecht.nl.ORCID http://orcid.org/0000-0003-1929-6350
Tom D TurmezeiDepartment of Radiology, Norfolk , Norwich University Hospital, Norwich, UK.
Kishan DattaniNorwich Medical School, University of East Anglia, Norwich, UK.
Dimitri A KesslerDepartment of Radiology, University of Cambridge, Cambridge, UK.
Simon C MastbergenDepartment of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht, The Netherlands.
Margreet KloppenburgDepartment of Rheumatology, Leiden University Medical Center, Leiden, The Netherlands.
Francisco J BlancoGrupo de Investigación de Reumatología (GIR), Centro de Investigación CICA, Departamento de Fisioterapia y Medicina, INIBIC - Complejo Hospitalario Universitario de A Coruña, SERGAS, Universidad de A Coruña, A Coruña, Coruña, Spain.
Ida K HaugenCenter for Treatment of Rheumatic and Musculoskeletal Diseases (REMEDY), Diakonhjemmet Hospital, Oslo, Norway.
Francis BerenbaumDepartment of Rheumatology, AP-HP Saint-Antoine Hospital, Paris, France.
Wolfgang WirthCenter for Anatomy and Cell Biology & Ludwig Boltzmann Institute for Arthritis and Rehabilitation (LBIAR), Research Program for Musculoskeletal Imaging, Paracelsus Medical University, Salzburg, Austria.
Felix EcksteinCenter for Anatomy and Cell Biology & Ludwig Boltzmann Institute for Arthritis and Rehabilitation (LBIAR), Research Program for Musculoskeletal Imaging, Paracelsus Medical University, Salzburg, Austria.
Frank W RoemerQuantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, MA, USA.
James W MacKayNorwich Medical School, University of East Anglia, Norwich, UK.

Funding

Innovative Medicines Initiative 115770
6 · The paper itself

Abstract

objectiveCartilage surface mapping is a technique that can visualize 3D cartilage thickness variation throughout a joint without a need for arbitrary regional definitions. The objective of this cross-sectional study was to utilize this technique to evaluate the cartilage thickness distribution in knee osteoarthritis patients and to analyze to what extent it depends on demographic, radiographic, and MRI structural pathology strata.

methodsPatients of the IMI-APPROACH cohort were included, with MRIs obtained at 1.5 T or 3 T. Tibial and femoral cartilage segmentation and registration with a canonical surface were performed semi-automatically. Kellgren-Lawrence and OARSI grading were performed on knee radiographs; MOAKS scoring was performed on MRI scans. The association of demographics and radiographic and MRI scorings with cartilage thickness distribution was analyzed with general linear models using statistical parametric mapping.

resultsTwo hundred eighty-seven patients were included. Male sex and height were positively associated with cartilage thickness particularly in the trochlea and medial femur, respectively, with differences up to 0.5 mm (male vs female), while radiographic joint space narrowing and bone marrow lesions showed region-specific negative associations (up to 0.14-0.5 mm per grade). Kellgren-Lawrence grade, MOAKS meniscal extrusion, and osteophytes showed patterns of positive and negative associations, with increasing grades showing reduced local tibiofemoral cartilage thickness, but greater thickness in the trochlea (both up to 0.2-0.3 mm per grade).

conclusionsDecreased height, female sex, and increasing tibiofemoral pathology were associated with thinner tibiofemoral cartilage. Unexpected results such as consistently thicker cartilage in the anterior femur with increasing disease or osteophytosis states provide opportunities for future research.

Indexed as

Cartilage, ArticularMagnetic Resonance ImagingOsteoarthritis, KneeAgedCohort StudiesCross-Sectional StudiesFemaleHumansImaging, Three-DimensionalKnee JointMaleMiddle Aged3DCartilage thicknessKneeOsteoarthritisPathology

Identifiers

PMID40113602
PMCPMC12361290

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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 OpenQuestion graph.