Advancing Use of DEXA Scans to Quantitatively and Qualitatively Evaluate Lateral Spinal Curves, for Preliminary Identification of Adolescent Idiopathic Scoliosis
Bibliographic record
Abstract
Abstract Dual-energy X-ray absorptiometry (DEXA) scan is an emerging screening method for identifying likely adolescent idiopathic scoliosis (AIS). Using DEXA in an unbiased population sample (the Raine Study), we aimed to report the inter-rater reliability and minimal detectable change (MDC 95 ) for scoliosis curve angle measurement, identify likely AIS prevalence, and the concordance between reported AIS diagnosis and DEXA-identified likely AIS. Scoliosis curve angles were measured using the modified Ferguson method on DEXA scans ( n = 1238) at age 20 years. For curve angle inter-rater reliability, two examiners measured angles (6–40°) on 41 scans. Likely, AIS was determined with quantitative and qualitative criteria (modified Ferguson angles ≥ 10° and expert review of spinal curves).The inter-rater reliability for scoliosis curve angle measurement was good–excellent (ICC: 0.82; 95% CI: 0.71–0.89; p < 0.001), and MDC 95 was 6.2°. The prevalence of likely AIS was 2.1% (26/1238). Diagnosis of AIS was reported despite little or no scoliosis curve (< 3.8°) for 20 participants (1.6%), and diagnosis of AIS was not reported despite scoliosis curve ≥ 10° for 11 participants (0.9%). Results support the use of modified Ferguson method to measure scoliosis curve angles on DEXA. There is potential utility for using a combination of quantitative measurement and qualitative criteria to evaluate DEXA images, to identify likely AIS for reporting prevalence. Without formal school screening, the analysis of DEXA in this population sample suggested that relying on current health professional diagnosis alone could result in 2.5% of this cohort being at risk of false positive diagnosis or delay in necessary management due to non-diagnosis of AIS.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".