Three-Dimensional Magnetic Resonance Imaging for Guiding Tibial and Femoral Tunnel Position in Anterior Cruciate Ligament Reconstruction: A Cadaveric Study
Bibliographic record
Abstract
Background: Femoral and tibial tunnel malposition for anterior cruciate ligament (ACL) reconstruction (ACLR) is correlated with higher failure rate. Regardless of the surgical technique used to create ACL tunnels, significant mismatches between the native and reconstructed footprints exist. Purpose: To compare the position of tunnels created by a standard technique with the ones created based on preoperative 3-dimensional magnetic resonance imaging (3D MRI) measurements of the ACL anatomic footprint. Study Design: Controlled laboratory study. Methods: Using 3D MRI, the native ACL footprints were identified. Tunnels were created on 16 knees (8 cadavers) arthroscopically. On one knee of a matched pair, the tunnels were created based on 3D MRI measurements that were provided to the surgeon (roadmapped technique), while on the contralateral knee, the tunnels were created based on a standard anatomic ACLR technique. The technique was randomly assigned per set of knees. Postoperatively, the positions of the tunnels were measured using 3D MRI. Results: On the tibial side, the median distance between the center of the native and reconstructed ACL footprints in relation to the root of the anterior horn of the lateral meniscus medially was 1.7 ± 2.2 mm and 1.9 ± 2.8 mm for the standard and roadmapped techniques, respectively ( P = .442), while the median anteroposterior distance was 3.4 ± 2.4 mm and 2.5 ± 2.5 mm for the standard and roadmapped techniques, respectively ( P = .161). On the femoral side, the median distance in relation to the apex of the deep cartilage (ADC) distally was 0.9 ± 2.8 mm and 1.3 ± 2.1 mm for the standard and roadmapped techniques, respectively ( P = .195), while the median distance anteriorly from the ADC was 1.2 ± 1.3 mm and 4.6 ± 4.5 mm for the standard and roadmapped techniques, respectively ( P = .007). Conclusion: Providing precise radiological measurements of the ACL footprints does not improve the surgeon’s ability to position the tunnels. Future studies should continue to attempt to provide tools to improve the tunnel position in ACLR. Clinical Relevance: This cadaveric study indicates that despite the use of 3D MRI in understanding the ACL anatomy, re-creating the native ACL footprints remains a challenge.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".