Quantifying the effect of off‐focal radiation on the output of kilovoltage x‐ray systems
Bibliographic record
Abstract
In a typical x-ray tube, off-focal radiation is mainly generated by the backscattered electrons that reenter the anode outside the focal spot. In this study, BEAMnrc (an EGSnrc user-code) is modified to simulate off-focal radiation. The modified BEAMnrc code is used to study the characteristics of electrons that backscatter from the anode, and to quantify their effect on the output of typical x-ray systems. Results show that the first generation backscatter coefficient is approximately 50% for tungsten anodes at diagnostic energies, and approximately 38% for molybdenum anodes at mammography energies. Second and higher generations of backscatter have a relatively minor contribution. At the patient plane, our simulation results are in excellent agreement with experimental measurements in the literature for the spectral shape of both the primary and the off-focal components, and also for the integral off-focal-to-primary ratio. The spectrum of the off-focal component at the patient plane is softer than the primary, which causes a slight softening in the overall spectrum. For typical x-ray systems, the off-focal component increases patient exposure (for a given number of incident primary electrons) by up to 11% and reduces the half-value layer and the effective energy of the average spectrum by up to 7% and 3%, respectively. The larger effects are for grounded cathode tubes, smaller interelectrode distance, higher tube voltage, lighter filtration, and less collimation. Simulation time increases by approximately 30% when the off-focal radiation is included, but the overall simulation time remains of the order of a few minutes. This study concludes that the off-focal radiation can have a non-negligible effect on the output parameters of x-ray systems and that it should be included in x-ray tube simulations for more realistic modeling of these systems.
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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".