Topical contrast agents to improve soft-tissue contrast in the upper airway using cone beam CT: a pilot study
Bibliographic record
Abstract
The purpose of this study is to explore the topical use of radiographic contrast agents to enhance soft-tissue contrast on cone beam CT (CBCT) images. Different barium sulphate concentrations were first tested using an airway phantom. Different methods of barium sulphate application (nasal drops, syringe, spray and sinus wash) were then tested on four volunteers, and nebulized iodine was tested in one volunteer. CBCT images were performed and then assessed subjectively by two examiners for contrast agent uniformity and lack of streak artefact. 25.0% barium sulphate presented adequate viscosity and radiodensity. Barium sulphate administered via nasal drops and sprays showed non-uniform collection at the nostrils, along the inferior and/or middle nasal meatuses and posterior nasal choana. The syringe and sinus wash showed similar results with larger volumes collecting in the naso-oropharynx. Nebulized iodine failed to distribute into the nasal cavity and scarcely collected at the nostrils. All methods of nasal application failed to adequately reach or uniformly coat the nasal cavity beyond the inferior nasal meatuses. The key factors to consider for optimum topical radiographic contrast in the nasal airway are particle size, flow velocity and radio-opacity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".