Vertebral rotation measurement: a summary and comparison of common radiographic and CT methods
Bibliographic record
Abstract
Current research has provided a more comprehensive understanding of Adolescent Idiopathic Scoliosis (AIS) as a three-dimensional spinal deformity, encompassing both lateral and rotational components. Apart from quantifying curve severity using the Cobb angle, vertebral rotation has become increasingly prominent in the study of scoliosis. It demonstrates significance in both preoperative and postoperative assessment, providing better appreciation of the impact of bracing or surgical interventions. In the past, the need for computer resources, digitizers and custom software limited studies of rotation to research performed after a patient left the scoliosis clinic. With advanced technology, however, rotation measurements are now more feasible. While numerous vertebral rotation measurement methods have been developed and tested, thorough comparisons of these are still relatively unexplored. This review discusses the advantages and disadvantages of six common measurement techniques based on technology most pertinent in clinical settings: radiography (Cobb, Nash-Moe, Perdriolle and Stokes' method) and computer tomography (CT) imaging (Aaro-Dahlborn and Ho's method). Better insight into the clinical suitability of rotation measurement methods currently available is presented, along with a discussion of critical concerns that should be addressed in future studies and development of new methods.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.014 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".