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Record W1940449030 · doi:10.1186/ar1437

Magnetic resonance imaging, X-ray and dual X-ray absorptiometry techniques for assessment and monitoring of knee osteoarthritis

2004· article· en· W1940449030 on OpenAlexafffund
Pauline Boulos, Dean Inglis, Karen A. Beattie, George Ioannidis, Chris Gordon, J. Duryea, Colin E. Webber, Jonathan D. Adachi

Bibliographic record

VenueArthritis Research · 2004
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsHamilton Health SciencesMcMaster UniversitySt. Joseph’s Healthcare Hamilton
FundersCanadian Arthritis NetworkNational Cancer InstituteGenentechNational Institutes of HealthNatural Sciences and Engineering Research Council of CanadaDutch Arthritis AssociationOesterreichische NationalbankDeutsche ForschungsgemeinschaftNuffield FoundationArthritis SocietyPhysiotherapy Foundation of CanadaCanadian Institutes of Health ResearchLupus Research AllianceWellcome TrustNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Allergy and Infectious DiseasesHoward Hughes Medical InstituteLupus Research InstituteBiogenAustrian Science FundArthritis Foundation
KeywordsComputer science

Abstract

fetched live from OpenAlex

Healthy volunteers and patients with knee OA referred for assessment to a rheumatologist are invited to participate in the various studies. All patients are asked to complete preset questionnaires. Radiographs of the knee are performed postero-anteriorly in a standardized fixed-flexion position by trained technicians. Radiographs are subsequently digitized and analyzed for mJSW using an automated computer algorithm. A 1 T extremity MRI scanner is used for imaging each individual's knee. Sequences include a saggital T 1 -weighted, 3D spoiled gradient echo with fat saturation, a saggital T 1 -weighted fast spin echo (FSE), a coronal T 2 -weighted FSE and an axial FSE inversion recovery sequence. Quantitative cartilage measurements of normal and OA subjects' knees were obtained using a validated segmentation technique on both 1 T and 1.5 T MRI images. The 1 T extremity MRI scanner has been found to be reliable and of comparable precision in comparison with a 1.5 T whole-body scanner. The use of a fixed-flexion position and a computer algorithm to determine medial mJSW of the knee in patients having normal or osteoarthritic knees has been found to be reliable in both short-term and long-term studies. Forty-seven pairs of knee radiographs were assessed in the short-term study while 14 pairs in a long-term study were assessed. Reliability for both studies was measured by means of intraclass correlation coefficient and found to be 0.95–0.99 for both healthy subjects and those with OA. A cross-sectional study of 45 patients referred for assessment of knee pain is being completed. Data analyses will include comparison of pain scales, history and physical examination with MRI findings in the knee. Quantitative cartilage measurements using a 1 T office-based extremity MRI scanner have been found to be reliable and of comparable precision with those obtained using a 1.5 T whole-body MRI scanner. The use of a fixed-flexion radiographic technique for assessing mJSW has been found to be reliable in a long-term reproducibility study at our center. Early diagnosis and prompt assessments of patients with OA can be accessible using an office-based extremity MRI scanner and could prove to be a valuable clinical tool with the development of disease-modifying agents for the treatment of OA.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.930
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

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

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 head0.032
GPT teacher head0.321
Teacher spread0.289 · 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 designOther design
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
Published2004
Admission routes2
Has abstractyes

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