The effect of copper conversion plates on low‐Z target image quality
Bibliographic record
Abstract
PURPOSE: Common electronic portal imaging devices (EPIDs) contain a 1.0 mm copper conversion plate to increase detection efficiency of a therapeutic megavoltage spectrum. When used in imaging with a photon beam generated with a low atomic number (Z) target, the conversion plate attenuates a substantial proportion of photons in the diagnostic range, thereby reducing the achievable image quality. In this work, we measure directly dependence on low-Z target image quality as a function of copper plate thickness, for both planar imaging and cone beam computed tomography (CBCT). METHODS: Monte Carlo modeling was used to quantify changes to the diagnostic spectrum and detector response for low-Z target beams generated with either 2.35 or 7.00 MeV electrons incident on a carbon target. Planar contrast-to-noise ratio (CNR) and spatial resolution measurements were made as a function of copper thickness. CNR measurements were made for CBCT imaging as a function of dose both with and without the copper plate present in the EPID. RESULTS: The presence of copper in the EPID decreased the diagnostic photon population by up to 20% and suppressed the peak detector response (dose deposited in the scintillator) at 60 keV by a factor of 6.4. Planar CNR was increased by a factor ranging from 1.4 to 4.0, depending on the material imaged, with no copper present compared to a standard 1.0 mm thickness. Planar spatial resolution was only slightly degraded with increasing copper thickness. Increases in CBCT image CNR ranged from a factor of 1.3-2.1 with the copper plate removed. CONCLUSIONS: It is possible to increase the proportion of photons in the diagnostic energy range (25 keV-150 keV) reaching the phosphor screen by as much as 20% when removing the copper conversion plate. This results in significant increases of planar and CBCT image CNR. Consequently, we suggest that the copper conversion plate be removed from the EPID when used for low-Z target planar or CBCT imaging.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".