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Record W2012548795 · doi:10.1002/art.30471

Quantitative magnetic resonance imaging evidence of synovial proliferation is associated with radiographic severity of knee osteoarthritis

2011· article· en· W2012548795 on OpenAlexaff
Svetlana Krasnokutsky, Ilana Belitskaya‐Lévy, Jenny T. Bencardino, Jonathan Samuels, Mukundan Attur, Ravinder R. Regatte, Perry Rosenthal, Jeffrey D. Greenberg, Mark E. Schweitzer, Steven B. Abramson, Leon Rybak

Bibliographic record

VenueArthritis & Rheumatism · 2011
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal synovial abnormalities and treatments
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsMedicineOsteoarthritisMagnetic resonance imagingRadiographySynovitisOdds ratioNuclear medicineConfidence intervalConcordanceKnee JointImaging biomarkerBody mass indexRadiologyArthritisInternal medicinePathologySurgery

Abstract

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OBJECTIVE: To evaluate the relationships between both quantitative and semiquantitative assessments of the degree of knee synovitis on 3T magnetic resonance imaging (MRI) and the severity of knee osteoarthritis (OA) on radiography. METHODS: Fifty-eight patients with knee OA underwent nonfluoroscopic fixed-flexion knee radiography. In addition, dynamic contrast-enhanced 3T MRI of the knees was performed, before and after gadolinium administration, to quantify synovial membrane volume (SV) as a measure of synovial proliferation (expressed as the quantitative SV), and semiquantitative measures of synovitis were also applied using both contrast-enhanced and unenhanced images. Two radiologists scored the knee radiographs using the Osteoarthritis Research Society International atlas; interreader agreement was assessed using kappa statistics and concordance correlation coefficients. Multiple linear and logistic regression analyses were used to assess associations among variables, while controlling for the effects of age, body mass index, sex, and meniscal extrusion. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated for measures of disease activity. RESULTS: The Kellgren/Lawrence (K/L) grade of radiographic knee OA severity (β=0.78), the diseased compartment joint space width (dcJSW) (β=-0.22), and the diseased compartment joint space narrowing (dcJSN) score (β=0.53) were each significantly associated with the quantitative SV (P=0.0001, P=0.0003, and P=0.0001, respectively). Furthermore, the quantitative SV strongly correlated with the total volume of subchondral bone marrow lesions (BMLs) (β=0.22, P=0.0003). The K/L grade, dcJSW, and dcJSN score were each significantly associated with the semiquantitative Boston Leeds Osteoarthritis Knee Score (BLOKS) for the extent of infrapatellar synovitis (OR 9.05 [95% CI 1.94, 42.3] for K/L grade; OR 0.75 [95% CI 0.54, 1.03] for dcJSW; and OR 2.22 [95% CI 1.15, 4.31] for dcJSN score) and extent of joint effusion (OR 5.75 [95% CI 1.23, 26.8] for K/L grade; OR 0.70 [95% CI 0.50, 0.98] for dcJSW; and OR 1.96 [95% CI 1.02, 3.74] for dcJSN score). In addition, the semiquantitative synovitis grade on contrast-enhanced MRI was significantly associated with the K/L grade (β=0.036, P=0.0040) and dcJSN score (β=0.015, P=0.0266), and also significantly associated with the BLOKS synovitis score. CONCLUSION: Synovitis is a characteristic feature of advancing knee OA and is significantly associated with the K/L grade, JSW, JSN score, and total volume of BMLs on radiographs. Furthermore, BLOKS scoring of synovitis on unenhanced MRI is associated with measurements of synovitis on contrast-enhanced MRI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.247
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations161
Published2011
Admission routes1
Has abstractyes

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