Technical report: Rapid intraoperative reconstruction of cranial implants using additively manufactured moulds
Bibliographic record
Abstract
During craniotomies, a portion of the calvarium or skull is removed to gain access to the intracranial space. When it is not possible to re-implant the flap, surgeons may repair the defect intraoperatively or at a later date. With larger defects being more difficult to repair intraoperatively, we investigated a method for the creation of patient-specific moulds for ad hoc bone flap reconstruction using rapid prototyping. Patient-specific moulds were created based on light scanned models of the defect, using custom software and rapid prototyping. Polymethylmethacrylate bone implants were created for three retrospective craniotomy cases and evaluated based on original flap and skull reconstruction accuracy. Bone implants created using our moulding method reconstruct the original flap and skull with an average reconstruction accuracy of 0.82 and 1.3 mm, respectively. Average skull reconstruction accuracy obtained by surgeons performing freehand implant reconstruction was 1.49 mm. Time needed to generate moulds was between 2 h and 45 min and 6 h and 20 min. Improvements to current printing technology will make this procedure technically feasible for future cranial procedures.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".