Implant placement accuracy in total knee arthroplasty: validation of a CT-based measurement technique
Bibliographic record
Abstract
BACKGROUND: The primary goal of many computer-assisted surgical systems like robotics for total knee arthroplasty (TKA) is to accurately execute a preoperative plan. To assess whether the preoperative plan was executed accurately in 3D, one option is to compare the planned and postoperative implant placement using a preoperative and postoperative CT scan of the patient's limb. This comparison requires a 3D-to-3D surface registration between the preoperative and postoperative 3D bone models and between the planned and postoperative 3D implants. Hence, the present study aimed at validating this measurement technique by determining (I) the anatomical regions that result in the lowest 6-degree of freedom (DoF) errors for 3D-to-3D surface registration of bone models, (II) the 6-DoF errors for 3D-to-3D surface registration of the implant models, and (III) the 6-DoF of the complete measurement technique. METHODS: Four different regions of the femur were tested to determine which one would result in the most accurate 3D-to-3D registration of the bone models using 12 cadaveric lower limb specimens. Next, total knee arthroplasties were performed on six specimens, and the accuracy of the 3D-to-3D implant registration was evaluated against a gold standard registration performed using fiducial markers. RESULTS: The most accurate 3D-to-3D bone registration was obtained when using the largest anatomical regions available after TKA, being the full 3D femur model or the femur model without the distal femur which resulted in root mean square errors within 0.2 mm for translations and 0.2° for rotation. The accuracy of the 3D-to-3D femoral and tibial implant registration was within 0.7 mm for translations and 0.4°-0.6° for rotations, respectively. The accuracy for the overall procedure was within 0.9 mm and 0.6° for both femur and tibia when using femoral regions resulting in accurate 3D-to-3D bone registration. CONCLUSIONS: In conclusion, this measurement technique can be used in applications where measurement errors up to 0.9 mm in translations and up to 0.6° in rotations in component placement are acceptable.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".