High-Speed Fluoroscopy to Measure Dynamic Spinal Cord Deformation in an <i>In Vivo</i> Rat Model
Bibliographic record
Abstract
Although spinal cord deformation is thought to be a predictor of injury severity, few researchers have investigated dynamic cord deformation, in vivo, during impact. This is needed to establish correlations among impact parameters, internal cord deformation, and histological and functional outcomes. Relying on surface deformations alone may not sufficiently represent spinal cord deformation. The objective of this study was to develop a high-speed fluoroscopic method of tracking the surface and internal cord deformations of rat spinal cord during experimental cord injury. Two radio-opaque beads were injected into the cord at C5/6 in the dorsal and ventral white matter. Four additional beads were glued to the surface of the cord. Dynamic bead displacement was tracked during a dorsal impact (130 mm/sec, 1 mm depth) by high-speed radiographic imaging at 3000 FPS, laterally. The internal spinal cord beads displaced significantly more than the surface beads in the ventral direction (1.1-1.9 times) and more than most surface beads in the cranial direction (1.2-1.5 times). The dorsal beads (internal and surface) displaced more than the ventral beads during all impacts. The bead displacement pattern implies that the spinal cord undergoes complex internal and surface deformations during impact. Residual displacement of the internal beads was significantly greater than that of the surface beads in the cranial-caudal direction but not the dorsoventral direction. Finite element simulation confirmed that the additional bead mass likely had little effect on the internal cord deformations. These results support the merit of this technique for measuring in vivo spinal cord deformation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".