Development, physical properties and clinical applicability of a mechanical Multileaf Collimator for the use in Cobalt-60 radiotherapy
Bibliographic record
Abstract
According to the Directory of Radiotherapy Centres (DIRAC) there are 2348 Cobalt-60 (Co-60) teletherapy units worldwide, most of them in low and middle income countries, compared to 11046 clinical accelerators. To improve teletherapy with Co-60, a mechanical Multi-Leaf Collimator (MLC) was developed, working with pneumatic pressure and thus independent of electricity supply. Instead of tungsten, brass was used as leaf material to make the mechanical MLC more affordable. The physical properties and clinical applicability of this mechanical MLC are presented here. The leakage strongly depends on the fieldsize of the therapy unit due to scatter effects. The maximum transmission through the leaves measured 2.5 cm from the end-to-end gap, within a field size of 20 cm × 30 cm defined by jaws of the therapy unit at 80 cm SAD, amounts 4.2%, normalized to an open 10 cm × 10 cm field, created by the mechanical MLC. Within a precollimated field size of 12.5 cm × 12.5 cm, the end-to-end leakage is 6.5% normalized to an open 10 cm × 10 cm field as well. This characteristic is clinically acceptable considering the criteria for non-IMRT MLCs of the International Electrotechnical Commission (IEC 60601-2-1). The penumbra for a 10 cm × 10 cm field was measured to be 9.14 mm in plane and 8.38 mm cross plane. The clinical applicability of the designed mechanical MLC was affirmed by measurements relating to all relevant clinical properties such as penumbra, leakage, output factors and field widths. Hence this novel device presents an apt way forward to make radiotherapy with conformal fields possible in low-infrastructure environments, using gantry based Co-60 therapy units.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".