Reliability and Feasibility of Extended Field of View Ultrasound Imaging Techniques for Measuring the Limb Muscle Cross-Sectional Area
Bibliographic record
Abstract
Purpose: Panoramic ultrasound imaging (pUSI) is an extended field of view (FOV) imaging technique that enables visualization of larger muscles; however, it is not available in all ultrasound systems. Using an acoustic standoff pad that is compatible with any ultrasound system may be an alternative method to increase FOV, but it has not been used to evaluate limb muscles. The purpose of this study was to evaluate the reliability and feasibility of using pUSI and an acoustic standoff pad to measure the limb muscle cross-sectional area (mCSA). Method: A cross-sectional study was conducted. Using pUSI and an acoustic standoff pad, we obtained B-mode ultrasound images of the rectus femoris, biceps brachii, and lateral gastrocnemius muscles of 26 healthy participants on two occasions 7–10 days apart. The agreement between the two methods was determined using intra-class correlation coefficients (ICCs) and Bland–Altman plots. Test–retest reliability was assessed using ICCs and standard error of measurement (SEM). The feasibility of acquiring and analyzing the images was evaluated using a Likert scale. Results: The acoustic standoff pad and pUSI demonstrated strong agreement (ICC [3,3] > 0.85); however, the mCSAs were different ( p < 0.05). Test–retest reliability for each technique was high for all muscles (ICC [3,3] > 0.85; SEM = 0.6–1.5 cm 2 ). Image acquisition was highly feasible, but there were some limitations in analyzing the images. Conclusions: pUSI and an acoustic standoff pad are two reliable techniques for measuring mCSA, but the measurements are not directly comparable. Future studies should evaluate the accuracy of the acoustic standoff pad compared with gold-standard methods.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".