Small field of view cone beam CT temporomandibular joint imaging dosimetry
Bibliographic record
Abstract
OBJECTIVES: Cone beam CT (CBCT) is generally accepted as the imaging modality of choice for visualisation of the osseous structures of the temporomandibular joint (TMJ). The purpose of this study was to compare the radiation dose of a protocol for CBCT TMJ imaging using a large field of view Hitachi CB MercuRay™ unit (Hitachi Medical Systems, Tokyo, Japan) with an alternative approach that utilizes two CBCT acquisitions of the right and left TMJs using the Kodak 9000(®) 3D system (Carestream, Rochester, NY). METHODS: 25 optically stimulated luminescence dosemeters were placed in various locations of an anthropomorphic RANDO(®) Man phantom (Alderson Research Laboratories, Stanford, CT). Dosimetric measurements were performed for each technique, and effective doses were calculated using the 2007 International Commission on Radiological Protection tissue weighting factor recommendations for all protocols. RESULTS: The radiation effective dose for the CB MercuRay technique was 223.6 ± 1.1 μSv compared with 9.7 ± 0.1 μSv (child), 13.5 ± 0.9 μSv (adolescent/small adult) and 20.5 ± 1.3 μSv (adult) for the bilateral Kodak acquisitions. CONCLUSIONS: Acquisitions of individual right and left TMJ volumes using the Kodak 9000 3D CBCT imaging system resulted in a more than ten-fold reduction in the effective dose compared with the larger single field acquisition with the Hitachi CB MercuRay. This decrease is made even more significant when lower tube potential and tube current settings are used.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".