Radiation dose in CT colonography–trends in time and differences between daily practice and screening protocols
Bibliographic record
Abstract
The purpose of this study was to evaluate the currently used effective doses in CT colonography (CTC) and to search for trends in time. A Pubmed search for articles and a search for congress abstracts concerning CTC was performed. Research institutions were sent a CTC dose questionnaire concerning the type of CT system employed and the CT parameters used. With the ImPACT CT Dosimetry Spreadsheet effective doses were calculated. Of 83 institutions, 34 returned a complete questionnaire; 21 (62%) used 64-detector row CT and 17 (50%) used dose modulation. The median effective dose per institution was 5.7 mSv (2.8 mSv supine; 2.5 mSv prone) for screening protocols and 9.1 mSv (5.2 and 3.0 mSv, respectively) for daily practice protocols (p<0.05). Doses did not differ significantly between CT machines with different numbers of detector rows. In 17 institutions incorporated in a study in 2004 as well, the median dose for daily practice protocols changed from 11 mSv in 2004 to 9.7 mSv now (n.s.). Median effective dose for CTC is significantly lower for screening than for daily practice protocols. Although the number of CTC protocols with dose modulation increased substantially since 2004, no significant decrease in effective dose was found.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".