Development of a database of organ doses for paediatric and young adult CT scans in the United Kingdom
Bibliographic record
Abstract
Despite great potential benefits, there are concerns about the possible harm from medical imaging including the risk of radiation-related cancer. There are particular concerns about computed tomography (CT) scans in children because both radiation dose and sensitivity to radiation for children are typically higher than for adults undergoing equivalent procedures. As direct empirical data on the cancer risks from CT scans are lacking, the authors are conducting a retrospective cohort study of over 240,000 children in the UK who underwent CT scans. The main objective of the study is to quantify the magnitude of the cancer risk in relation to the radiation dose from CT scans. In this paper, the methods used to estimate typical organ-specific doses delivered by CT scans to children are described. An organ dose database from Monte Carlo radiation transport-based computer simulations using a series of computational human phantoms from newborn to adults for both male and female was established. Organ doses vary with patient size and sex, examination types and CT technical settings. Therefore, information on patient age, sex and examination type from electronic radiology information systems and technical settings obtained from two national surveys in the UK were used to estimate radiation dose. Absorbed doses to the brain, thyroid, breast and red bone marrow were calculated for reference male and female individuals with the ages of newborns, 1, 5, 10, 15 and 20 y for a total of 17 different scan types in the pre- and post-2001 time periods. In general, estimated organ doses were slightly higher for females than males which might be attributed to the smaller body size of the females. The younger children received higher doses in pre-2001 period when adult CT settings were typically used for children. Paediatric-specific adjustments were assumed to be used more frequently after 2001, since then radiation doses to children have often been smaller than those to adults. The database here is the first detailed organ-specific paediatric CT scan database for the UK. As well as forming the basis for the UK study, the results and description of the methods will also serve as a key resource for paediatric CT scan studies currently underway in other countries.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".