Geometric Torsion in Idiopathic Scoliosis
Bibliographic record
Abstract
STUDY DESIGN: Three-dimensionally reconstructed spines of 62 subjects with idiopathic scoliosis were reviewed for three-dimensional pattern classification based on the measurement of geometric torsion. OBJECTIVES: To evaluate the relevance of geometric torsion as a three-dimensional index of scoliosis, and to develop a three-dimensional classification of deformity for idiopathic scoliosis as opposed to the current classifications based on two-dimensional frontal views. SUMMARY OF BACKGROUND DATA: Attempts have been made to measure the geometric torsional shape of scoliotic curves represented curvilinearly. However, the geometric torsion phenomenon has never been properly analyzed and thus has never been precisely defined. METHODS: Standardized stereoradiographs of 62 patients with idiopathic scoliosis were obtained and used to generate three-dimensional reconstructions. A continuous parametric form of the curved line that passes through the vertebrae was created by least square fitting of Fourier series functions. Frenet's formulas then were used to calculate the geometric torsion. RESULTS: Analysis of geometric torsion associated with 94 major scoliotic curves allowed three basic categories of torsion curve patterns to be identified. Scoliotic spines with multiple major curves are described by a combination of basic torsion patterns, one for each curve. CONCLUSIONS: A three-dimensional analysis of the spine in terms of geometric torsion has defined three distinct patterns of torsion in a group of scoliotic curves. Geometric torsion had extreme values at the levels of upper and lower vertebrae, but zero or nearly zero values at the levels of the apices. The torsional phenomenon can be unidirectional or bidirectional in both single and double major curves.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".