Four-Dimensional CT Analysis of Normal Syndesmotic Motion
Bibliographic record
Abstract
BACKGROUND: The syndesmosis ligament complex stabilizes the distal tibiofibular joint while allowing for small amounts of physiologic motion. When injured, malreduction of the syndesmosis is the most important factor that contributes to inferior functional outcomes. Syndesmotic reduction is a dynamic measure, which is not adequately captured by conventional computed tomography (CT). Four-dimensional CT (4DCT) can image joints as they move through range of motion (ROM). The aim of this study was to employ 4DCT to determine in vivo syndesmotic motion with ankle ROM in uninjured ankles. METHODS: Uninjured ankles were analyzed in patients who had contralateral syndesmotic injuries, as well as a cohort of healthy volunteers with bilateral uninjured ankles. Bilateral ankle 4DCT scans were performed as participants moved their ankles between maximal dorsiflexion and plantarflexion. Multiple measures of syndesmotic width, as well as sagittal translation and fibular rotation, were automatically extracted from 4DCT using a custom program to determine the change in syndesmotic position with ankle ROM. RESULTS: = .43). No participants with bilateral uninjured ankles had a side-to-side difference in syndesmotic width of 2 mm or greater. CONCLUSION: 4DCT allows accurate, in vivo syndesmotic measurements, which change with ankle ROM, confirming prior work that was limited to biomechanical studies. Side-to-side syndesmotic measurements are consistent within subjects, validating the method of templating syndesmotic reduction off the contralateral ankle, in a consistent ankle position, to achieve anatomic reduction of syndesmotic injury. LEVEL OF EVIDENCE: Level II, prospective cohort study.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| 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) | 0.003 | 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".