Penumbra width determination of single beam and 201 beams of Gamma Knife machine model 4C using Monte Carlo simulation
Bibliographic record
Abstract
Abstract Background One of the stereotactic radiosurgery techniques is Gamma Knife radiosurgery, in which intracranial lesions that are inaccessible or inappropriate for surgery are treated using 201 cobalt-60 sources in one treatment session. In this conformal technique, the penumbra width, which results in out-of-field dose in tumour-adjacent normal tissues should be determined accurately. The aim of this study is to calculate the penumbra widths of single and 201 beams for different collimator sizes of Gamma Knife machine model 4C using EGSnrc/BEAMnrc Monte Carlo simulation code and comparison the results with EBT3 film dosimetry data. Methods and materials In this study, simulation of Gamma Knife machine model 4C was performed based on the Monte Carlo codes of EGSnrc/BEAMnrc. To investigate the physical penumbra width (80−20%), the single beam and 201 beams profiles were obtained using EGSnrc/DOSXYZnrc code and EBT3 films located at isocentre point in a spherical Plexiglas head phantom. Results Based on the results, the single beam penumbra widths obtained from simulation data for 4, 8, 14 and 18 mm collimator sizes along X axis were 0·75, 0·77, 0·90 and 0·92 mm, respectively. The data for 201 beams obtained from simulation were 2·61, 4·80, 7·92 and 9·81 mm along X axis and 1·31, 1·60, 1·91 and 2·14 mm along Z axis and from film dosimetry were 3·21, 4·90, 8·00 and 10·61 mm along X axis and 1·22, 1·69, 2·01 and 2·25 mm along Z axis, respectively. Conclusion The differences between measured and simulated penumbra widths are in an acceptable range. However, for more precise measurement in the penumbra region in which dose gradient is high, Monte Carlo simulation is recommended.
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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 | 0.001 |
| 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 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".