Comparison of longitudinal excursion of a nerve-phantom model using quantitative ultrasound imaging and motion analysis system methods: A convergent validity study
Bibliographic record
Abstract
BACKGROUND: Quantitative ultrasound imaging is gaining popularity in research and clinical settings to measure the neuromechanical properties of the peripheral nerves such as their capability to glide in response to body segment movement. Increasing evidence suggests that impaired median nerve longitudinal excursion is associated with carpal tunnel syndrome. To date, psychometric properties of longitudinal nerve excursion measurements using quantitative ultrasound imaging have not been extensively investigated. METHODS: This study investigates the convergent validity of the longitudinal nerve excursion by comparing measures obtained using quantitative ultrasound imaging with those determined with a motion analysis system. A 38-cm long rigid nerve-phantom model was used to assess the longitudinal excursion in a laboratory environment. The nerve-phantom model, immersed in a 20-cm deep container filled with a gelatin-based solution, was moved 20 times using a linear forward and backward motion. Three light-emitting diodes were used to record nerve-phantom excursion with a motion analysis system, while a 5-cm linear transducer allowed simultaneous recording via ultrasound imaging. RESULTS: = 0.99) and agreement (mean absolute difference between methods = 0.85 mm; mean relative difference between methods = 7.48 %). Small discrepancies were largely found when larger excursions (i.e. > 10 mm) were performed, revealing slight underestimation of the excursion by the ultrasound imaging analysis software. CONCLUSION: Quantitative ultrasound imaging is an accurate method to assess the longitudinal excursion of an in vitro nerve-phantom model and appears relevant for future research protocols investigating the neuromechanical properties of the peripheral nerves.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".