Factors influencing spinal curvature measurements on ultrasound images for children with adolescent idiopathic scoliosis (AIS)
Bibliographic record
Abstract
The measurements of spinal curvatures using the ultrasound (US) imaging method on children with scoliosis have been comparable with radiography. However, factors influencing the reliability and accuracy of US measurement have not been studied. The purpose of this study is to investigate the effects of curve features and patients' demographics on US measurements and to determine which factors influence the reliability and accuracy. Two hundred children with scoliosis were recruited and scanned with US by one experienced operator and three trainees. One experienced rater measured the proxy Cobb angles from US images twice one week apart and compared the results with clinical radiographic records. The correlation and accuracy between the US and radiographic measurements were subdivided by different curve severities, curve types, subjects' weight status and US acquisition experiences. A total of 326 and 313 curves were recognized from radiographs and US images, respectively. The mean Cobb angles of the 13 missing curves were 17.4±7.4° and 11 at the thoracic region. Among the 16 curves showing large discrepancy (≥6°) between US and radiographic measurements, 7 were main thoracic and 6 were lumbar curves. Twelve had axial vertebral rotation (AVR) greater than 8°. The US scans performed by the experienced operator showed fewer large discrepancy curves, smaller difference and higher correlation than the scans from the trainees (3%, 1.7±1.5°, 0.95 vs 6%, 2.4±1.8°, 0.90). Only 4% missing and 5% large discrepancy curves were demonstrated for US measurements in comparison to radiography. The missing curves were mainly caused by small severity and in the upper spinal region. There was a higher chance of the large discrepancy curves in the main thoracic and lumbar regions with AVR>8°. A skilled operator acquired better US images and led to more accurate measurements especially for those subjects with larger curvatures, AVR and body mass index (BMI).
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 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 | 0.001 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".