Validation of a Novel Minimally Invasive Intervertebral Disc Pressure Sensor Utilizing In-Fiber Bragg Gratings in a Porcine Model
Bibliographic record
Abstract
STUDY DESIGN: Nucleus pressure was measured within porcine intervertebral discs (IVDs) with a novel in-fiber Bragg grating (FBG) sensor (0.4 mm diameter) and a strain gauge (SG) sensor (2.45 mm). OBJECTIVE: To validate the accuracy of a new FBG pressure sensor designed for minimally invasive measurements of nucleus pressure. SUMMARY OF BACKGROUND DATA: Although its clinical utility is controversial, it is possible that the predictive accuracy of discography can be improved with IVD pressure measurements. These measurements are typically obtained using needle-mounted SG sensors inserted into the nucleus. However, by virtue of their size, SG sensors alter disc mechanics, injure anulus fibers, and can potentially initiate or accelerate degenerative changes thereby limiting their utility particularly clinically. METHODS: Six functional spinal units were loaded in compression from 0 N to 500 N and back to 0 N; nucleus pressure was measured using the FBG and SG sensors at various locations along anterior and anterolateral axes. RESULTS: On average maximum IVD pressures measured using the FBG and SG sensors were within 9.39% of each other. However, differences between maximum measured pressures from the FBG and SG sensors were larger (22.2%) when the SG sensor interfered with vertebral endplates (P < 0.05). The insertion of the FBG sensor did not result in visible damage to the anulus, whereas insertion of the SG sensor resulted in large perforations in the anulus through which nucleus material was visible. CONCLUSION: The new FBG sensor is smaller and less invasive than any previously reported disc pressure sensor and gave results consistent with previous disc pressure studies and the SG sensor. There is significant potential to use this sensor during discography while avoiding the controversy associated with disc injury as a result of sensor insertion.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".