SU‐E‐I‐10: Dose Measurement Methodology for Dental Cone‐Beam CT
Bibliographic record
Abstract
Purpose: Dental Cone Beam CT (CBCT) was introduced to perform 3D high resolution imaging at lower dose than multi‐slice CT (MSCT). No consensus has been found to measure the dose delivered by this equipment, unlike the CTDI measurement used for the narrow beam MSCT. The goal of this study is to determine the suitability of the dosimetry methods published in AAPM Report 111 for dental equipment. Methods: A protocol derived from one proposed by Dixon et al. was applied to dose measurements of MSCT, dental CBCT (small and large fields of view) and a dental panoramic system. The CTDI protocol was also performed on the MSCT to compare both methods under different scanning conditions. Experiments were executed to characterize the dose distribution using a thimble ionization chamber (dose free‐in‐air, dose in a CTDI phantom) and gafchromic film (beam profiles, dose in an anthropomorphic phantom). Experiments were performed on the CBCT with a CTDI head phantom alone and with the head phantom placed on a body phantom to measure the importance of scattered radiation due to the chest. Results: The dose measured in the centre of the phantom and field of view from the large field of view dental CBCT (11.4 mGy/100mAs) is 2 times lower than that of MSCT (20.7 mGy/100mAs) for the same FOV, but approximately 20 times higher than for a panoramic system (0.6 mGy/100mA.s). The impact of scattered radiation due to the chest phantom measured with the Dixon et al. method was not significant. The dose distributions measured with the PMMA phantom and the anthropomorphic phantom were similar. Conclusion: Although the dose delivered by the dental CBCT was reduced by a factor of 2 compared to MSCT for the same field of view, it is approximately 20 times higher than the dose delivered by the panoramic system.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".