Can extra-articular strains be used to measure facet contact forces in the lumbar spine? An <i>in-vitro</i> biomechanical study
Bibliographic record
Abstract
Experimental measurement of the load-bearing patterns of the facet joints in the lumbar spine remains a challenge, thereby limiting the assessment of facet joint function under various surgical conditions and the validation of computational models. The extra-articular strain (EAS) technique, a non-invasive measurement of the contact load, has been used for unilateral facet joints but does not incorporate strain coupling, i.e. ipsilateral EASs due to forces on the contralateral facet joint. The objectives of the present study were to establish a bilateral model for facet contact force measurement using the EAS technique and to determine its effectiveness in measuring these facet joint contact forces during three-dimensional flexibility tests in the lumbar spine. Specific goals were to assess the accuracy and repeatability of the technique and to assess the effect of soft-tissue artefacts. In the accuracy and repeatability tests, ten uniaxial strain gauges were bonded to the external surface of the inferior facets of L3 of ten fresh lumbar spine specimens. Two pressure-sensitive sensors (Tekscan) were inserted into the joints after the capsules were cut. Facet contact forces were measured with the EAS and Tekscan techniques for each specimen in flexion, extension, axial rotation, and lateral bending under a +/- 7.5 N m pure moment. Four of the ten specimens were tested five times in axial rotation and extension for repeatability. These same specimens were disarticulated and known forces were applied across the facet joint using a manual probe (direct accuracy) and a materials-testing system (disarticulated accuracy). In soft-tissue artefact tests, a separate set of six lumbar spine specimens was used to document the virtual facet joint contact forces during a flexibility test following removal of the superior facet processes. Linear strain coupling was observed in all specimens. The average peak facet joint contact forces during flexibility testing was greatest in axial rotation (71 +/- 25 N), followed by extension (27 +/- 35 N) and lateral bending (25 +/- 28 N), and they were most repeatable in axial rotation (coefficient of variation, 5 per cent). The EAS accuracy was about 20 per cent in the direct accuracy assessment and about 30 per cent in the disarticulated accuracy test. The latter was very similar to the Tekscan accuracy in the same test. Virtual facet loads (r.m.s.) were small in axial rotation (12 N) and lateral bending (20 N), but relatively large in flexion (34 N) and extension (35 N). The results suggested that the bilateral EAS model could be used to determine the facet joint contact forces in axial rotation but may result in considerable error in flexion, extension, and lateral bending.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".