Measuring absorbed dose for i-CAT CBCT examinations in child, adolescent and adult phantoms
Bibliographic record
Abstract
OBJECTIVES: Design and construct child and adolescent head phantoms to measure the absorbed doses imparted during dental CBCT and compare with the absorbed dose measured in an adult phantom. METHODS: A child phantom was developed to represent the smallest patients receiving CBCT, usually for craniofacial developmental concerns, and an adolescent phantom was developed to represent healthy orthodontic patients. Absorbed doses were measured using a thimble ionization chamber for the custom-built child and adolescent phantoms and compared with measurements using a commercially available adult phantom. Imaging was performed with an i-CAT Next Generation (Imaging Sciences International, Hatfield, PA) CBCT using two different fields of view covering the craniofacial complex (130 mm high) or maxilla/mandible (60 mm high). RESULTS: Measured absorbed doses varied depending on the location of the ionization chamber within the phantoms. For CBCT images obtained using the same protocol for all phantoms, the highest absorbed dose was measured in all locations of the small child phantom. The lowest absorbed dose was measured in the adult phantom. CONCLUSIONS: Images were obtained with the same protocol for the adult, adolescent and child phantoms. A consistent trend was observed with the highest absorbed dose being measured in the smallest phantom (child), while the lowest absorbed dose was measured in the largest phantom (adult). This study demonstrates the importance of child-sizing the dose by using dedicated paediatric protocols optimized for the imaging task, which is critical as children are more sensitive to harmful effects of radiation and have a longer life-span post-irradiation for radiation-induced symptoms to develop than do adults.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".