Tibial bone defect prediction based on preoperative artefact‐reduced CT imaging is superior to standard radiograph assessment
Bibliographic record
Abstract
Abstract Purpose The purpose of this study was to evaluate the accuracy of preoperative CT‐based Anderson Orthopaedic Research Institute (AORI)‐grading and to correlate Computed tomography (CT)‐based volumetric defect measurements with intraoperative AORI findings. Methods 99 patients undergoing revision total knee arthroplasty (rTKA) with preoperative CT‐images were identified in an institutional revision registry. CT‐image segmentation with 3D‐Slicer Software was used to create 3D tibial bone defects which were then graded according to the AORI‐classification. The AORI classification categorizes tibial defects into three types: Type I has healthy cortical and cancellous bone near the joint line, Type II involves metaphyseal bone loss affecting one or both condyles, and Type III indicates deficient metaphyseal bone with distal defects and potential damage to the patellar tendon and collateral ligament attachments. These 3D‐CT gradings were compared to preoperative X‐ray and intraoperative AORI grading. The Friedman test was used to investigate differences between AORI values of each measurement method. Volumetric 3D‐bone defect measurements were used to investigate the relationship between AORI classification and volumetric defect size in the three anatomic zones of the tibia. Results Substantial agreements between preoperative 3D‐CT AORI and intraoperative AORI (kappa = 0.663; P < 0.01) and fair agreements between preoperative X‐ray AORI and intraoperative AORI grading (kappa = 0.304; P < 0.01) were found. Moderate correlations between volume of remaining bone and intraoperative AORI grading were found in epiphysis (rS = – 0.529; P < 0.001), metaphysis (rS = – 0.557; P < 0.001) and diaphysis (rS = – 0.421; P < 0.001). Small volumetric differences between AORI I vs. AORI II defects and relatively large differences between AORI II and AORI III defects in each zone were detected. Conclusion Tibial bone defect prediction based on preoperative 3D‐CT segmentation showed a substantial agreement with intraoperative findings and is superior to standard radiograph assessment. The relatively small difference in defect volume between AORI I, IIa and IIb suggests that updated CT‐based classifications might hold benefits for the planning of rTKA. Level of evidence Retrospective Cohort Study; III
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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 | 0.025 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".