Intraoperative Tracking of the Trunk DuringPosterior Instrumentation of the Scoliotic Spine: A Feasibility Study
Bibliographic record
Abstract
Scoliosis involves spine and trunk deformities. However, during posterior instrumentation of the scoliotic spine, only the exposed spine is currently seen or tracked using navigation systems. A technique for intraoperative tracking of the trunk was developed in order to optimize the surgical correction of the scoliotic trunk deformity. The feasibility of this technique was assessed by comparing the trunk geometry between 19 normal and 21 scoliotic subjects, using an experimental set-up simulating the position adopted during posterior scoliosis surgery. Eleven magnetic sensors placed on anatomical landmarks of the trunk were used to compute nine geometric indices. The geometric indices were closer to zero for normal subjects. Therefore, indices approaching zero during the surgical manoeuvres would indicate a reduction of the trunk asymmetry. Only three of the nine indices were significantly different between normal and scoliotic subjects. This result indicates that the positioning of the subjects on the Relton-Hall frame tends to "normalize" the trunk geometry since the standing position gives more significant differences between normal and scoliotic subjects. The real-time quantification of the trunk geometry during surgical correction of scoliosis may allow the surgeon to improve the correction of both spinal and trunk deformities or to optimize the positioning of the patients on the operating table.
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 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 | 0.000 | 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".