Perspective review on applications of optics in spinal surgery
Bibliographic record
Abstract
Optical technologies may be applied to multiple facets of spinal surgery from diagnostics to intraoperative image guidance to therapeutics. In diagnostics, the current standard remains cross-sectional static imaging. Optical surface scanning tools may have an important role; however, significant work is required to clearly correlate surface metrics to radiographic and clinically relevant spinal anatomy and alignment. In the realm of intraoperative image guidance, optical tracking is widely developed as the current standard of instrument tracking, however remains compromised by line-of-sight issues and more globally cumbersome registration workflows. Surface scanning registration tools are being refined to address concerns over workflow and learning curves, and allow real-time update of tissue deformation; however, the line-of-sight issues plaguing instrument tracking remain to be addressed. In therapeutics, optical applications exist in both visualization, in the form of endoscopes, and ablation, in the form of lasers. Further work is required to extend the feasibility of laser ablation to multiple tissues, including disc, bone, and tumor, in a safe and time-efficient manner. Finally, we postulate some of the short- and long-term opportunities for future growth of optical techniques in the context of spinal surgery. Particular emphasis is placed on intraoperative image guidance, the area of the authors' primary expertise.
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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) | 0.003 | 0.001 |
| 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 | 0.001 |
| 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".