A comparative study of the effective radiation doses from cone beam computed tomography and plain radiography for sialography
Bibliographic record
Abstract
OBJECTIVES: As a first step in developing a protocol for multidimensional sialography using cone beam CT (CBCT), the objective of this study was to compare the effective radiation doses from sialography of the parotid and submandibular glands using plain radiography and CBCT. METHODS: The effective doses were calculated from dose measurements made at 25 selected locations in the head and neck of a radiation analogue dosimeter (RANDO) phantom, using International Commission on Radiological Protection 2007 tissue weighting factors. RESULTS: The effective dose (E) changed in relationship to changes in CBCT field of view (FOV), peak kilovoltage (kVp) and milliamperage (mA). Specifically, E decreased from a maximum of 932 microSv (30 cm FOV, 120 kVp, 15 mA) to 60 microSv (15 cm FOV, 80 kVp, 10 mA) for a parotid gland study and to 148 microSv (15 cm FOV, 80 kVp, 10 mA) for a submandibular study. The collective series of plain radiographs made during sialography of the parotid and submandibular glands yielded effective doses of 65 microSv and 156 microSv, respectively. The plain parotid gland series included one panoramic, two anterior-posterior skull and four lateral skull radiographs, whereas the submandibular gland series included one panoramic, one standard mandibular occlusal and four lateral skull radiographs. CONCLUSION: The effective doses from CBCT examinations centred on the parotid and submandibular glands were similar to those calculated for plain radiograph sialography when a 15 cm FOV was chosen in combination with exposure conditions of 80 kVp and 10 mA.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".