Reliability of a novel 3-dimensional computed tomography method for reverse shoulder arthroplasty postoperative evaluation
Bibliographic record
Abstract
BACKGROUND: Long-term function and survival of reverse shoulder arthroplasties (RSAs) are reliant on component positioning and fixation. Conventional postoperative analysis is performed using plain radiographs or 2-dimensional (2D) computed tomography (CT) images. Although 3-dimensional (3D) CT would be preferred, its use is limited by metal artifacts. This study proposes a new 3D CT method for postoperative RSA evaluation and compares its interobserver reliability with conventional methods. MATERIALS AND METHODS: Preoperative and postoperative CT scans, as well as postoperative radiographs, were obtained from 18 patients who underwent RSA implantation; the scapula, implant, and screws were reconstructed as 3D CT models. The postoperative 3D scapula and implant were imported into preoperative coordinates and matched to the preoperative scapula. Standardized scapula coordinates were defined, in which the glenoid baseplate version and inclination angle were measured. The percentage of screw volume in bone was measured from a Boolean intersection operation between the preoperative scapula and screw models. Four independent reviewers performed the measurements using 3D CT and conventional 2D methods. Intraclass correlation coefficients (ICCs) were used to compare the reliability of the methods. RESULTS: The 3D CT method showed excellent reliability (ICC > 0.75) in baseplate inclination (ICC = 0.92), version (ICC = 0.97), and screw volume in bone (ICC = 0.99). Conventional 2D methods demonstrated poor reliability (ICC < 0.4). For radiographs, inclination showed poor reliability (ICC = 0.09) and the screw percentage in bone showed fair reliability (ICC = 0.54). Version was not measured with plain radiographs. For 2D CT slice measurements, inclination showed poor reliability (ICC = 0.02), version showed excellent reliability (ICC = 0.81), and the screw percentage in bone showed poor reliability (ICC = 0.28). CONCLUSION: The new 3D CT-based method for evaluating RSA glenoid implant positioning and screw volume in bone showed excellent reliability and overcame the metal-artifact limitation of postoperative CT and 3D CT reconstruction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 teacher head, 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".