Limb‐sparing in dogs using patient‐specific, three‐dimensional‐printed endoprosthesis for distal radial osteosarcoma: A pilot study
Bibliographic record
Abstract
Limb-sparing for distal radial osteosarcoma has a high rate of complications. Using personalized three-dimensional (3D)-printed implants might improve outcome. The goals of this study were to optimize use of patient-specific, 3D-printed endoprostheses for limb-sparing in dogs in the clinical environment and to report the outcome. This was a pilot study where five client-owned dogs were enrolled. Computed tomography (CT) of the thoracic limbs was performed, which was used to create patient-specific endoprostheses and cutting guides, and repeated on the day of surgery. Intra-arterial (IA) carboplatin was introduced in the clinical management. Limb-sparing was performed. Outcome measures were time required to produce the endoprosthesis and cutting guide, fit between cutting guide and endoprosthesis with host bones, gait analysis, size of the tumour, percent tumour necrosis, complications, disease-free interval (DFI) and survival time (ST). Four dogs received IA carboplatin. Excessive tumour growth between planning CT and surgery did not occur in any dog. The interval between the CT and surgery ranged from 14 to 70 days. Fit between the cutting-guide and endoprosthesis with the host bones was good to excellent. At least one complication occurred in all dogs. Two dogs were euthanized with STs of 192 and 531 days. The other dogs were alive with a follow up of 534 to 575 days. IA chemotherapy is a promising strategy to minimize the risk of excessive tumour growth while waiting for the endoprosthesis and cutting-guide to be made. The design of the cutting-guide was critical for best fit of the endoprosthesis with host bones.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".