Accuracy of injection pressure measurement at peripheral nerves using high-resolution 40 MHz ultrasound in an anesthetized porcine model
Bibliographic record
Abstract
Background Fluid injection pressure measurement is promoted as a marker of needle tip position that discriminates between tissue layers. However, clinical ultrasound has insufficient resolution to identify the exact position of the needle tip. Our primary objective was to use 40 MHz ultrasound in anesthetized pigs in order to precisely locate the tip of the needle and measure opening injection pressure in muscle, at epineurium and in subepineurium. Methods We surgically exposed the axillae of four anesthetized pigs. Two operators placed a 40 MHz ultrasound transducer over the pectoral muscle and imaged axillary, median and radial nerves. Injections (0.5 mL) were randomized to in-plane and out-of-plane needle trajectories and flow rates of 1, 6 and 12 mL/min. Results We identified 541 fascicles in 23 nerves. The ratio of fascicle area to nerve area remained constant at ~0.30 for all nerves. Axillary nerves were smaller than median and radial nerves, difference in diameter (95% CI) 1.61 (0.87 to 2.36) mm, p<0.001 and 1.59 (0.82 to 2.36) mm, p=0.001, respectively. Axillary nerves had less fascicles per nerve than median nerves, difference 7.63 (2.43 to 12.83) and radial nerves, difference 9.02 (3.64 to 14.40). We visualized the circumneurium and injection within the subcircumneural compartment. Intraneural injection increased nerve area (SD) from 5.7 (2.2) mm2 to 13.7 (5.5) mm2, difference 8.0 (5.4–10.6) mm2, p<0.001. Mean injection pressure was greater in subepineurium compared with muscle, geometric ratio 2.29 (1.30 to 4.10), p<0.001; and greater on epineurium compared with muscle, geometric ratio 1.73 (1.03 to 3.00), p=0.01. Twenty-two out of 23 injections in muscle, 14 out of 23 injections at epineurium and 11 out of 22 injections in subepineurium were <138 kPa (20 psi). Conclusion Needle tip position was not discernible using pressure monitoring. The circumneurium and subcircumneural injection compartment were observed but not intrafascicular injection.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".