Development of a Protocol for Measuring the Tensile Properties of the Swallowing Musculature: A Potential Methodology for Quantifying Radiofibrosis
Bibliographic record
Abstract
Radiotherapy for head and neck cancer (HNC) can lead to fibrosis (RF) and dysphagia. However, the relationship between these conditions remains unclear due to a lack of valid/objective RF measurement tools. Three studies were designed to address this knowledge gap. First, a systematic review was conducted to identify and evaluate existing tools for measuring RF in HNC patients. Eight electronic databases and five HNC journals were searched. Two blinded raters reviewed each reference. Included studies were critically appraised using Quality Assessment of Diagnostic Accuracy Studies-2. A narrative review was also conducted to identify tools for measuring fibrosis elsewhere in the body. One low cost tool with good clinical availability was shear wave elastography (SWE). SWE is sensitive to muscle fiber orientation; however, little is known about the musculoaponeurotic architecture of the swallowing musculature. Therefore, the second study evaluated the musculoaponeurotic architecture of the suprahyoid muscles (AD, anterior digastric/GH, geniohyoid/PD, posterior digastric/MH, mylohyoid/SH, stylohyoid). Ten cadaveric specimens were volumetrically dissected, digitized, and modeled, as in situ. Architectural parameters for each muscle were quantified and functionally distinct regions identified. The final study assessed the potential of using SWE to measure the stiffness of GH and genioglossus (GG), in vivo, in ten healthy adult subjects. Ten stiffness measurements were obtained bilaterally at rest and during swallowing exercises. The systematic review found nine tools that had published data regarding their reliability/validity. No valid and reliable tools had been applied to the swallowing musculature. All studies were at a high risk of bias. The anatomical study found that GH, SH, and PD had a single belly; MH had distinct anterior and posterior regions; AD varied by participant, with 1-3 distinct bellies. GH had the most consistent fiber bundle orientation and was therefore selected for initial SWE investigations. The third study showed that using SWE to measure the stiffness of GH and GG at rest and during certain exercises is possible and well-tolerated. Measuring the tensile properties of the swallowing musculature could offer insight into the underlying causes of dysphagia post-radiotherapy for HNC, and could thereby guide the development of novel, individualized, and targeted interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.063 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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".