The Intra- and Inter-Evaluator Reliability of Coronal Plane Vertebra Displacement Measurements on Spinal Ultrasound Images of Adolescents with Idiopathic Scoliosis
Bibliographic record
Abstract
Objective We aimed to establish the intra- and inter-evaluator reliability of apical vertebral translation (AVT), inter-apical distance and coronal balance measurements from three-dimensional ultrasound images (3DUS). Methods Female volunteers with and without adolescent idiopathic scoliosis underwent 3DUS scans in 10 positions: standing; arms anteriorly supported at 60° of shoulder flexion; fingers to clavicles, chin, zygomatic process and eyebrows; shoulders abducted 90° with hands open and thumbs on shoulders; hands on anterior wall with and without blocks; and hands unsupported. Custom software was utilized to obtain measurements. Intra-evaluator reliability ICC 2,1 with standard error of measurement (SEM) were obtained for measurements extracted twice by a blinded evaluator (1 wk apart) on scans with pre-marked laminae. Inter-evaluator reliability compared the first measurement occasion by three evaluators. Intra-evaluator reliability was also tested for standing, chin and abducted positions, by an evaluator first measuring pre-marked laminae, comparing (1+ y later) to landmarking laminae and repeating measurements. Results Forty-four females had a mean age, height and weight of 16.8 ± 4.4 y, 163.1 ± 5.9 cm and 56.1 ± 10.8 kg, respectively. Fourteen single and 13 double curve participants had mean maximum curve angles of 29.2° ± 4.4 and 25.5° ± 3.4, in standing, respectively. AVT, inter-apical distance and coronal balance measurements satisfied the criteria for individual use (ICC > 0.90) for both intra-evaluator scenarios (SEM below 0.89 mm for pre-marked laminae or <4.97 mm when re-marking laminae) and for the inter-evaluator reliability (SEM < 1.12 mm). Conclusion Reliable coronal plane vertebra displacement measurements can be obtained from 3DUS images in multiple standing positions.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".