Clinical Accuracy of Computer-Assisted Two-Dimensional Fluoroscopy for the Percutaneous Placement of Lumbosacral Pedicle Screws
Bibliographic record
Abstract
STUDY DESIGN: Clinical case series. OBJECTIVE: The primary objective of this study was to evaluate the clinical accuracy of computer-assisted two-dimensional fluoroscopy (2D-CAS) for the percutaneous placement of lumbosacral pedicle screws. SUMMARY OF BACKGROUND DATA: Loss of visual anatomic landmarks and reduced tactile feedback increases the risk of pedicle screw misplacement by when using minimally invasive (MIS) percutaneous techniques. However, objective data on screw misplacement in this scenario is lacking. METHODS: A MIS-2D-CAS technique (FluoroNav) was used for the placement of pedicle screws in 41 consecutive patients undergoing MIS-interbody instrumented fusion. Postoperative computerized tomography (CT) was obtained in all patients at 6 months after surgery and was evaluated by 3 observers. The relative position of the screw to the pedicle was graded regarding pedicle breach (I, no breach; II, <2 mm; III, 2-4 mm; IV, >4 mm), breach direction, vertebral body perforation and screw trajectory. Interobserver reliability of CT grading was assessed with kappa statistics. RESULTS: A total of 161 screws were placed. No neurologic, vascular, or visceral injuries occurred. About 37 (23%) screws breached the pedicle. The majority (83.8%, 31/37) of breaches were graded II. There were 5 Grade III and 1 Grade IV breaches. Medial versus lateral breaches occurred in 30% (11/37) and 60% (22/37), respectively; 10% (4/37) of the breaches were superior. Overall, 8 (5%) vertebral body breaches occurred. Of the pedicle screws, 19 (12%) had trajectories that deviated from acceptable, with the majority being medial (16/19, 84%). Fluoroscopy time for screw placement was typically less than 20 seconds total per case. There was 1 clinically significant breach at L5 (III, medial) which resulted in a L5 radiculopathy. Kappa statistics showed excellent overall agreement between reviewers (k = 0.73-0.92; 90%-96% agreement). CONCLUSION: The two-dimensional (2D) virtual fluoroscopy is a clinically acceptable option for percutaneous placement of pedicle screws. However, this technique requires cautious application and is particularly vulnerable to axial trajectory errors.
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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 | 0.003 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".