Low‐ target optimization for spatial resolution improvement in megavoltage imaging
Bibliographic record
Abstract
PURPOSE: Recently, several authors have shown contrast improvements in megavoltage portal imaging and cone-beam computed tomography using low atomic number (Z) targets. This work compliments previous studies by investigating the effects of varying different beam production parameters including target atomic number, target thickness, and incident electron energy on spatial resolution. METHODS: Target materials of beryllium, aluminum, and tungsten were investigated over a range of thicknesses between 10% and 100% of the continuous slowing down approximation range of electrons. Incident electron kinetic energies of 4.5 and 7.0 MeV were used, in conjunction with custom targets installed above the carousel of a modern radiotherapy linear accelerator. Monte Carlo simulations of the accelerator were constructed and compared to the experimental results. RESULTS: The results showed that thinner targets, as well higher incident electron energies, generally produce more favorable modulation transfer function (MTF) curves. Due to an MTF dependence of the detector system on the photon energy, the experimental results showed that low-Z targets produced superior MTF curves. Simulations showed 14.5% and 21.5% increases in f50 for the 7.0 and 4.5 MeV targets (A1; 60% R% CSDA), respectively, when moved from the carousel to the location of the clinical target. f50 values for the custom targets were compared to the clinical 6 MV beam and were found to be between 10.4% lower (4.5 MeV/W) and 15.5% higher (7.0 MeV/Be). CONCLUSIONS: Integration of low-Z external targets into the treatment head of a medical linear was achieved with only minor modifications. It was shown that reasonably high resolution images on par or better than those acquired with the clinical 6 MV beam can be achieved using external low-Z targets.
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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".