Using Laser Range-finding to Measure Bore Depth in Surgical Drilling of Bone
Bibliographic record
Abstract
BACKGROUND: Measuring drilled bore depth in bone is an important part of osteosynthesis surgery. Current methods have substantial limitations in terms of reliability, leading to placement of incorrectly sized screws and unsatisfactory user experience. QUESTIONS/PURPOSES: (1) Can a prototype laser range-finder measure bore depth in bone as well as or better than a conventional depth gauge in terms of accuracy and precision (that is, variability)? METHODS: A conventional analog orthopaedic surgical depth gauge was compared with a laser range-finder-based prototype. Experiments were conducted on four pig hind limbs, with bicortical holes drilled in the femur and the tibia. Two surgeons alternated drilling bores in three different clinically relevant conditions: straight drilling through the diaphysis, angled drilling through the diaphysis, and straight drilling through the metaphysis. Depth measurements were taken with the laser range-finder-based prototype, and the conventional depth gauge and compared against depth measurements obtained from a CT image that served as the reference measurement. RESULTS: In straight diaphyseal drilling the laser range-finder-based prototype had a larger mean error of 1.34 mm (± 0.7 mm) compared with a mean error of -0.06 mm (± 1.38 mm) using the conventional gauge (95% CI 0.824 to 1.976; p < 0.001). In angled diaphyseal drilling, there was no difference in mean error between the laser range-finder-based prototype (1.66 ± 0.86 mm) and the conventional gauge (2.36 ± 3.79 mm [95% CI -2.338 to 0.938]; p = 0.393). In straight metaphyseal drilling, there was no difference in mean error between the laser range-finder-based prototype (2.11 ± 0.8 mm) and the conventional gauge (1.51 ± 3.19 mm [95% CI -0.500 to 1.700]; p = 0.280). The laser range-finder-based prototype had greater precision (smaller variance) than the conventional depth gauge in straight diaphyseal drilling (p < 0.001), angled diaphyseal drilling (p < 0.001), and straight metaphyseal drilling (p < 0.001). CONCLUSIONS: A laser range-finder-based prototype mounted on a conventional surgical drill demonstrated overall similar accuracy and better precision in measuring drilled bore depth in bone compared with the conventional depth gauge. CLINICAL RELEVANCE: A device based on this concept could improve the reliability of bore depth measurement in surgical practice and could therefore reduce the frequency of screw replacement and associated complications.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".