Anatomical study of the innervation of posterior knee joint capsule: implication for image-guided intervention
Bibliographic record
Abstract
Background and objectives Peripheral nerve block is an important component of the multimodal analgesia for total knee arthroplasty. Novel interventional techniques of ultrasound-guided nerve block supplying the posterior knee joint capsule require knowledge of the innervation of the posterior capsule. The objectives of this cadaveric study were to determine the course, frequency, and distribution of the articular branches innervating the posterior knee joint capsule and their relationships to anatomical landmarks. Methods Fifteen lightly embalmed specimens were meticulously dissected. The origin of articular branches was identified, their frequency recorded, and the course documented in relation to anatomical landmarks. The capsular distribution of articular branches was documented and a frequency map generated. Results In all specimens, articular branches from the posterior division of the obturator and tibial nerves were found to supply the posterior capsule. Additionally, articular branches from common fibular nerve and sciatic nerve were found in eight (53%) and three (20%) specimens, respectively. The capsular distribution of tibial nerve spanned the entire posterior capsule. The posterior division of obturator nerve supplied the superomedial aspect of the posterior capsule overlapping with the tibial nerve. The superolateral aspect of the posterior capsule was innervated by the tibial nerve and, when present, the common fibular/sciatic nerves. Conclusions Frequency map of the course and distribution of the articular branches and their relationship to anatomical landmarks form an anatomical basis for peripheral nerve block approaches that provide analgesia to the posterior knee joint capsule.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".