Novel Ultrasound Image Acquisition Protocol and Scoring System for the Pediatric Knee
Bibliographic record
Abstract
OBJECTIVE: The use of musculoskeletal ultrasound is increasing among pediatric rheumatologists. Reliable scoring systems are needed for the objective assessment of synovitis. The aims of this study were to create a standardized and reproducible image acquisition protocol for B-mode and Doppler ultrasound of the pediatric knee, and to develop a standardized scoring system and determine its reliability for pediatric knee synovitis. METHODS: Six pediatric rheumatologists developed a set of standard views for knee assessment in children with juvenile arthritis. Subsequently, a comprehensive literature review, practical exercises, and a consensus process were performed. A scoring system for both B-mode and Doppler was then developed and assessed for reliability. Interreader reliability or agreement among a total of 16 raters was determined using 2-way single-score intraclass correlation coefficient (ICC) analysis. RESULTS: Twenty-one views to assess knee arthritis were initially identified. Following completion of practical exercises and subsequent consensus processes, 3 views in both B-mode and Doppler were selected: suprapatellar longitudinal and medial/lateral parapatellar transverse views. Several rounds of scoring and modifications resulted in a final ICC of suprapatellar view B-mode 0.89 (95% confidence interval [95% CI] 0.86-0.92) and Doppler 0.55 (95% CI 0.41-0.69), medial parapatellar view B-mode 0.76 (95% CI 0.68-0.83) and Doppler 0.75 (95% CI 0.66-0.83), and lateral parapatellar view B-mode 0.82 (95% CI 0.75-0.88) and Doppler 0.76 (95% CI 0.66-0.84). CONCLUSION: A novel B-mode and Doppler image acquisition and scoring system for assessing synovitis in the pediatric knee was successfully developed through practical exercises and a consensus process. Study results demonstrate overall good-to-excellent reliability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".