Novel multi jet fusion 3D‐printed patient immobilization for radiation therapy
Bibliographic record
Abstract
PURPOSE: Thermoplastic immobilizers are used routinely in radiation therapy to achieve positioning accuracy. These devices are variable in quality as they are dependent on the skill of the human fabricator. We examine the potential multi jet fusion (MJF) 3D printing for the production immobilizers with a focus on the surface dosimetry of several MJF-printed PA12-based material candidates. Materials are compared with the goal of minimizing surface dose with comparison to standard thermoplastic. We introduce a novel metamaterial design for the shell of the immobilizer, with the aims of mechanical robustness and low-dose buildup. We demonstrate first examples of adult and pediatric cranial and head-and-neck immobilizers. METHODS: Three different PA12 materials were examined and compared to fused deposition modeling-printed polylactic acid (PLA), PLA with density lowered by adding hollow glass microspheres, and to perforated or perforated/stretched and solid status quo thermoplastic samples. Build-up dose measurements were made using a parallel plate chamber. A metamaterial design was established based on a packed hexagonal geometry. Radiochromic film dosimetry was performed to determine the dependence of surface dose on the metamaterial design. Full cranial and head-and-neck prototype immobilizers were designed, printed, and assessed with regard to dimensional accuracy. RESULTS: Build-up dose measurements demonstrated the superiority of the PA12 material with a light fusing agent, which yielded a ∼15% dose reduction compared to other MJF materials. Metamaterial samples provided dose reductions ranging from 11% to 40% compared to stretched thermoplastic. MJF-printed immobilizers were produced reliably, demonstrated the versatility of digital design, and showed dimensional accuracy with 97% of sampled points within ±2 mm. CONCLUSIONS: MJF is a promising technology for an automated fabrication of patient immobilizers. Material selection and metamaterial design can be leveraged to yield surface dose reduction of up to 40%. Immobilizer design is highly customizable, and the first examples of MJF-printed immobilizers demonstrate excellent dimensional accuracy.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".