Total Ankle Arthroplasty Accuracy and Reproducibility Using Preoperative CT Scan-Derived, Patient-Specific Guides
Bibliographic record
Abstract
BACKGROUND: Preoperative navigation has provided many potential benefits for total knee arthroplasty, including patient-specific alignment, repeatable implant placement, and decreased operative time. For the first time, this technology was applied to total ankle arthroplasty (TAA). This study evaluated repeatability of tibia and talus patient-specific guide placement and deviation between the preoperative plan and actual implant placement. METHODS: Routine ankle CT scans were acquired of 15 cadaveric lower extremity limbs, converted into 3D solid models, and imported into a computer-assisted design assembly. Anatomic landmarks defining tibia/talus alignment were established and used to perform a virtual TAA. Commercially available implant components were placed to mimic traditional cases. An operative guide referencing the cadaver-specific anatomy was engineered to define the resection planes necessary to re-create virtual placement of traditional tibia and talus implants in the postoperative position. Board-certified TAA orthopaedic surgeons with no prior preoperative navigation experience placed the operative guides onto the bones based on tactile and visual feedback. Guide placement was repeated 4 times to determine variability. Final implant position was recorded with an infrared probe, confirmed with CT scans, and compared to the preoperative plan. Average deviations between planned and actual guide placement were determined for all rotational and translational degrees of freedom (DOF). In addition, implant component location was measured radiographically. RESULTS: Intraobserver tibia and talus guide variation between all trials was 0.26 ± 0.18 degrees and 0.36 ± 0.25 degrees in flexion/extension, 0.61 ± 0.58 and 0.53 ± 0.53 in varus/valgus, and 0.79 ± 0.38 degrees and 1.15 ± 0.77 degrees in internal/external rotation, respectively. Average variation between preoperative and postoperative implant placement was less than 2 degrees and 1.4 mm in all specimens tested. CONCLUSION: Preliminary data suggest that preoperative navigation and custom operative guides result in reliable and reproducible placement of TAA implants and patient-specific ankle alignment. Deviation of final implant placement from the preoperative plan was less than 2 degrees in all angular DOF, providing greater accuracy than the ±3 degrees determined in other implant system studies using traditional instrumentation and computer navigation. CLINICAL RELEVANCE: We have further demonstrated that final implant position is successfully guided by these patient-specific guides, with reproducibility of tibial component placement falling within 2 degrees of the intended target. This level of reproducibility suggests a promise for this technology, and it is hoped this level of accuracy will become the benchmark for the next generation of total ankle arthroplasty.
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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 | 0.015 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".