The effect of the flattening filter on photoneutron production at 10 MV in the Varian TrueBeam linear accelerator
Bibliographic record
Abstract
Purpose Neutrons are an unavoidable by‐product of high‐energy radiation therapy treatments that deliver unwanted nontarget dose to patients. Use of flattening‐filter‐free (FFF) photon beams has been shown to significantly reduce photoneutron production per monitor unit (MU) of dose delivered. The purpose of this investigation was to characterize the photoneutron production of the 10 MV and 10 MV FFF beams of the Varian TrueBeam TM linear accelerator. Methods Neutron fluence spectra were measured using a Nested Neutron Spectrometer TM (NNS, Detec Inc., Gatineau, Canada). The ratios of neutron fluence and ambient dose equivalent for the 10 MV FFF beam relative to the 10 MV beam, dubbed FF‐ratios (FFF/FF), were used to characterize the difference between the two beams. FF‐ratios were compared under the following three conditions (a) per MU, at various locations in the treatment room, (b) per MU, with the linac jaws opened and closed, and (c) per electron striking the bremsstrahlung target, as opposed to per MU, at one location with the jaws closed. Results On average, the neutron fluence for the 10 MV FFF beam was 37% lower per MU than the 10 MV beam (FF‐ratio = 0.63). The FF‐ratio in neutron fluence and ambient dose equivalent did not vary by much between different locations within the treatment room. However, the FF‐ratio in neutron ambient dose equivalent was reduced significantly when the linac jaws were opened compared to closed, which implies that the jaws contribute more to the photoneutron spectrum of the 10 MV FFF beam than to the 10 MV beam. Finally, it was found that the 10 MV FFF beam produces more photoneutrons per electron striking the bremsstrahlung target than the 10 MV beam (FF‐ratio = 2.56). Conclusions The photoneutron fluence per MU produced by the 10 MV FFF beam is 37% lower than the 10 MV beam of a Varian TrueBeam linac. Accordingly, a reduction in neutron dose received by patients is achieved through use of the unflattened beam, provided that treatment plans for each beam require approximately the same number of MU. It was found to be instructive to compare the photoneutron yield per source electron between the two beams as it helped provide an understanding of the physics underlying photoneutron production in both beams.
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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 | 0.000 | 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 | 0.000 | 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".