Multi‐institutional study on image quality for a novel CBCT solution on O‐ring linac
Bibliographic record
Abstract
Abstract Introduction This work presents a multi‐institutional study on image quality provided by a novel cone beam computed tomography (CBCT). The main goal is to investigate the consistency of imaging performance across multiple institutions. Methods Phantoms for measuring relative electron density (RED) and image quality were sent to six institutions for imaging on Ethos and Halcyon units equipped with HyperSight CBCT. The imaging protocols included tube potential from 100 to 140 kVp and exposure from 80 to 800 mAs. Imaging performance was evaluated with regard to RED versus Hounsfield units (HU), uniformity, contrast‐to‐noise ratio (CNR), slice thickness, circular symmetry, modulation transfer function (MTF), and spatial resolution. Results Among all institutions, some variability was observed among institutions in the RED‐to‐HU relationship, especially for RED values greater than 1, although no outliers were found (| z ‐score| < 2 in all cases). In this range, RED/HU slopes were 475 ± 25 10 −6 RED/HU at 100kVp, 505 ± 20 10 −6 RED/HU at 125kVp, and 550 ± 20 10 −6 RED/HU at 140kVp. Radial uniformity ranged from 1 to 7 HU, depending on protocol. Circular symmetry for two points 50 mm apart showed consistency within one‐pixel dimension. Integral nonuniformity was between 1 and 10, with no difference observed between vertical and horizontal dimensions. Contrast rods with 1% gave CNR = 0.5, 1 and 2 for 100(88), 125(176), and 140(528) in kVp(mAs), and contrast rods with 0.5% had CNR = 0.2, 0.4 and 0.8 for 100(88), 125(176), and 140(528) in kVp(mAs). Spatial resolution given by MTF at 10% and 50% yielded values of 0.55 ± 0.01 mm −1 and 0.35 ± 0.02 mm −1 , respectively. Conclusions This multi‐institutional analysis of CBCT imaging performance showed consistency in radial uniformity, circular symmetry, integral nonuniformity, contrast, and spatial resolution. Some variability was seen in the RED‐to‐HU relationship for RED > 1 depending on exposure. More data from different institutions would be necessary to establish more robust statistical metrics, which ensure quality parameters.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".