<b>MR Imaging, MR Arthrography, and Specimen Correlation of the Posterolateral Corner of the Knee:</b> An Anatomic Study
Bibliographic record
Abstract
OBJECTIVE: We sought to evaluate the anatomy of the posterolateral aspect of the knee with anatomic dissection, MR imaging, MR arthrography, and sectional anatomy. MATERIALS AND METHODS: We assessed the posterolateral corner of the knee during dissection of one gross anatomic specimen. MR imaging and MR arthrography were performed in seven additional knee specimens. T1-weighted spin-echo MR images were obtained in the standard imaging planes as well as in the coronal oblique plane. The specimens underwent T1-weighted spin-echo MR imaging after administration of intraarticular contrast material and were sectioned into planes corresponding to those of the MR images. RESULTS: At anatomic dissection, the following posterolateral structures were identified: the arcuate ligament (medial and lateral limbs), fabellofibular ligament, popliteofibular ligament, popliteus tendon and its two posterior attachments to the lateral meniscus, fibular collateral ligament, direct and anterior arms of the tendon of the long head of the biceps femoris muscle, and direct and anterior arms of the tendon of the short head of the biceps femoris muscle. Correlation of MR imaging and anatomic findings showed that the popliteofibular ligament and oblique popliteal ligament were found in 57% and 100% of specimens, respectively. At least one of the two limbs of the arcuate ligament was identified in 71% of specimens. The fabellofibular ligament was not identified on MR images in any of the specimens. The anteroinferior and posterosuperior popliteomeniscal fascicles were identified in all specimens. CONCLUSION: The posterolateral corner of the knee comprises complex and variable anatomic structures. Recognition of these variations is important in the assessment of MR images of the knee.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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".