TH‐C‐BRD‐07: Small Field Intracranial Radiosurgery Using Intermediate Energy X‐Rays (1 MV) to Improve Dose Gradient and Homogeneity
Bibliographic record
Abstract
Purpose: The radiological penumbra of small radiosurgical dose fields is dictated by the range of secondary electrons, which in turn is determined by the primary photon energy. The purpose of this work is to experimentally compare the dose gradient and homogeneity of a multiple beam dose distribution in a radiosurgery head phantom for 6 MV versus 1 MV while minimizing geometrical penumbra. Methods and Materials: A commercial radiosurgery head phantom (LUCY™) containing Gafchromic EBT film was used for all irradiations. A digital microscopy imaging system resolved steep dose gradients in the films and a Siemens linac was modified to produce 1 MV x‐rays. The XKnife™ RT3 TPS was modeled for both 1 and 6 MV to compare with measurements. Two‐beam (90° apart) and eighteen‐beam (10° apart) irradiations were done in the same plane as the film using a 5 mm tertiary collimator. The geometrical penumbra ranged from 0.2–0.4 mm, equivalent to a linac with a 1 mm focal spot with collimator 20 cm from the isocenter. Dose was normalized at the isocenter at depth 7 cm in phantom. Results: For the two‐beam irradiations, the 90%–50% and 90%–10% dose gradients at the beam intersection were 1.7 & 4.7 mm (6MV) versus 0.5 & 1.3 mm (1 MV) for identical irradiation conditions. For the eighteen‐beam arc, the 90%–80% & 90%–60% dose gradients in the plane of irradiation were 0.84 & 1.7 mm (6MV) versus 0.29 & 0.9 (1 MV). In all cases, the homogeneity across the isocenter was superior for 1 MV. The dose at the entrance of each beam was greater for 1 MV. Conclusions: A 1 MV x‐ray beam showed superior dose gradient and homogeneity compared to 6MV for the irradiations examined at the expense of an increase in dose at the beam entrance for the lower energy.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".