Systematic Review of MRI, Ultrasound, and Scintigraphy as Outcome Measures for Structural Pathology in Interventional Therapeutic Studies of Knee Arthritis: Focus on Responsiveness
Bibliographic record
Abstract
OBJECTIVE: validated imaging outcome tools to assess response to therapies in a single joint are required. Our aim was to review the published literature to ascertain the responsiveness of novel imaging techniques as outcome measures in interventional therapeutic studies of knee arthritis. METHODS: an Ovid Medline search was performed for original articles in English that used imaging techniques to assess response at the knee joint to therapy in osteoarthritis, rheumatoid arthritis, and psoriatic arthritis. Changes in response to therapy were assessed with regard to both internal and external responsiveness. RESULTS: in the studies that presented appropriate statistical data to allow responsiveness to be assessed, MRI was generally found to be internally responsive to pathologies imaged, and externally responsive, referenced against both other imaging modalities and biochemical biomarkers of arthritis. Ultrasonography was found to demonstrate internal responsiveness with regard to synovial thickness, effusion size, and popliteal cyst size. External responsiveness was demonstrated against several referenced health status measures. Scintigraphy was found to be externally responsive in the majority of studies, with internal responsiveness demonstrated in 1 study. CONCLUSION: while the imaging techniques appear to be responsive from the data we present, further inspection reveals that interpreting the responsiveness of imaging techniques was difficult, largely because of a lack of standardization of image acquisition, definitions of pathology, and scoring systems. Refined pathological definitions and scoring systems are required to enable the development of valid and responsive tools for interventional clinical trials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".