Investigation of planar image quality for a novel 2.5 MV diamond target beam from a radiotherapy linear accelerator
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: A commercial 2.5 MV beam has been clinically available for beam's-eye-view imaging in radiotherapy, offering improved contrast-to-noise ratio (CNR) compared to therapeutic beams, due to the softer spectrum. Previous research suggested that imaging performance could be improved using a low-Z diamond target to reduce the self-absorption of diagnostic energy photons. The aim of this study was to 1) investigate the feasibility of two 2.5 MV diamond target beamline configurations and 2) characterize the dosimetry and planar image quality of these novel low-Z beams. MATERIALS AND METHODS: The commercial 2.5 MV beam was modified by replacing the copper target with sintered diamond. Two beamlines were investigated: a carousel-mounted diamond target beamline and a 'conventional' beamline, with the diamond target in the target arm. Planar image quality was assessed in terms of spatial resolution and CNR. RESULTS: Due to image artifacts, image quality could not be assessed for the carousel-mounted low-Z target beam. The 'conventional' 2.5 MV low-Z beam quality was softer by 2.7% compared to the commercial imaging beam, resulting in improved CNR by factors of up to 1.3 and 1.7 in thin and thick phantoms, respectively. In regard to spatial resolution, the 'conventional' 2.5 MV low-Z beam slightly outperformed the commercial imaging beam. CONCLUSION: With a simple modification to the 2.5 MV commercial beamline, we produced an improved energy spectrum for imaging. This 2.5 MV diamond target beam proved to be an advantageous alternative to the commercial target configuration, offering both superior resolution and CNR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".