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Record W4415571050 · doi:10.1302/1358-992x.2025.11.023

EVALUATION OF 3D ULTRASOUND AS A TOOL TO EXAMINE SYNOVITIS VOLUME AND MORPHOLOGY IN RELATION TO PATIENT-REPORTED OUTCOMES

2025· article· en· W4415571050 on OpenAlexaffabout
Carla du Toit, Robert Dima, Matthew M. Hutter, Randa Mudathir, Aaron Fenster, Emily Lalone

Bibliographic record

VenueOrthopaedic Proceedings · 2025
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal synovial abnormalities and treatments
Canadian institutionsWestern University
Fundersnot available
KeywordsOsteoarthritisSynovitisUltrasoundRheumatology3D ultrasoundRadiographyGrading (engineering)Arthropathy

Abstract

fetched live from OpenAlex

Radiography is the primary imaging tool used to assess and monitor osteoarthritis (OA) in the first carpometacarpal joint (CMC1). However, studies have reported discrepancies between radiographic evidence of OA and patient-reported symptoms such as pain and disability. These discrepancies have been attributed to the lack of soft-tissue contrast associated with radiography in addition to the heterogeneous nature of osteoarthritis as a disease1. Synovitis has been associated with pain and disability and has been proven to be a driver of osteoarthritis disease progression2. 3D ultrasound has been validated for measuring synovial tissue volume in CMC1 OA patient, more work is required to examine sonographic features associated with CMC1 OA in a cohort of patients, including effusion morphology and tissue quality. Nine-teen CMC1 OA patients were recruited by an experienced hand surgeon and a rheumatologist. A 3D ultrasound (3D US) device and a 14L-5 linear probe were used to acquire 3D US image of the CMC1 joint of these patients. 2D US images were acquired and graded using the Outcome Measures in Rheumatology (OMERACT) semi-quantitative grading scales. Pain and disability interference was quantified using the Australian Canadian Hand Osteoarthritis Index. A two-point pinch grip test was conducted to determine grip force. A descriptive analysis was used to describe observed changes in synovial tissue morphology and volume as various imaging grading scales differ, and how these changes are related to outcomes of pain and functional strength. Three distinct OA phenotypes were distinguished by synovial tissue margin properties, synovial tissue volume, and pathophysiological appearance (effusion vs. hypertrophy) as can be seen in Table 1. Patients who presented with moderate synovial tissue volumes comprised predominately of synovial effusion (effusion dominant) had the lowest average pain interference scores and highest functional scores. These patients presented with uniform concave morphology of their joint effusion. In comparison, the second group of patients presented with more diffuse effusion morphology and increased hypertrophic tissue. These patients also had increased pain interference scores and decreased pinch grip values (Table 1). The last group of patients presented with predominantly osteochondral pathology with increased osteophyte presentation, decreased joint space, and decreased synovial tissue volumes. These patients also had the highest pain interference scores and weakest pinch grip forces (Fig.1). The results of this study indicate that morphological differences between signs of synovitis demonstrate that the relationship between disease progression, patient-related outcomes, and image-based evidence of OA in the CMC1 joint is complex. The structures involved change as the disease progresses to more severe stages as well as between bouts of inflammation and varies between patients. 3D US can provide potentially valuable imaging characteristics for monitoring OA. For any figures or tables, please contact the authors directly.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.066
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.289
Teacher spread0.274 · 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 teacher head, 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

Citations0
Published2025
Admission routes2
Has abstractyes

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