Design and production of 3D printed bolus for electron radiation therapy
Why this work is in the frame
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Bibliographic record
Abstract
This is a proof-of-concept study demonstrating the capacity for modulated electron radiation therapy (MERT) dose distributions using 3D printed bolus. Previous reports have involved bolus design using an electron pencil beam model and fabrication using a milling machine. In this study, an in-house algorithm is presented that optimizes the dose distribution with regard to dose coverage, conformity, and homogeneity within the planning target volume (PTV). The algorithm takes advantage of a commercial electron Monte Carlo dose calculation and uses the calculated result as input. Distances along ray lines from the distal side of 90% isodose line to distal surface of the PTV are used to estimate the bolus thickness. Inhomogeneities within the calculation volume are accounted for using the coefficient of equivalent thickness method. Several regional modulation operators are applied to improve the dose coverage and uniformity. The process is iterated (usually twice) until an acceptable MERT plan is realized, and the final bolus is printed using solid polylactic acid. The method is evaluated with regular geometric phantoms, anthropomorphic phantoms, and a clinical rhabdomyosarcoma pediatric case. In all cases the dose conformity are improved compared to that with uniform bolus. For geometric phantoms with air or bone inhomogeneities, the dose homogeneity is markedly improved. The actual printed boluses conform well to the surface of complex anthropomorphic phantoms. The correspondence of the dose distribution between the calculated synthetic bolus and the actual manufactured bolus is shown. For the rhabdomyosarcoma patient, the MERT plan yields a reduction of mean dose by 38.2% in left kidney relative to uniform bolus. MERT using 3D printed bolus appears to be a practical, low-cost approach to generating optimized bolus for electron therapy. The method is effective in improving conformity of the prescription isodose surface and in sparing immediately adjacent normal tissues.
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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 | 0.002 | 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 | 0.000 |
| 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 it