Radiation doses originating from diagnostic procedures during the treatment and follow-up of children and adolescents with malignant lymphoma
Bibliographic record
Abstract
Children with malignant lymphoma undergo many diagnostic procedures that involve exposure to ionising radiation. In addition, many, but by no means all, undergo further exposure to ionising radiation during radiotherapy. While therapeutic radiation exposures are prescribed, the extent of radiation exposure arising from diagnostic procedures utilised in such children is largely unknown. We completed an audit of the radiation doses arising from diagnostic imaging procedures performed in a cohort of children with malignant lymphoma. The cumulative effective radiation dose associated with radiographic and radioisotopic procedures was derived for 81 children and adolescents with malignant lymphoma during their diagnosis, treatment and follow-up. Thirty-eight of the 42 patients (90%) with Hodgkin lymphoma were alive at study termination, with follow-up periods ranging from 1.9 to 11.7 years (median 5.3). Thirty-three of the 39 patients (85%) with non-Hodgkin lymphoma were alive at study termination with follow-up periods ranging from 2.4 to 12.3 years (median 7.5). The median effective dose was 518 mSv for patients with Hodgkin lymphoma and 309 mSv for those with non-Hodgkin lymphoma. The maximum effective dose was 1.7 Sv. The principal contributors to the effective dose were computed tomography (CT) and nuclear medicine imaging procedures using (67)Ga. Protocols for the management of children and adolescents with malignant lymphoma should be reviewed in order to reduce the radiation detriment without loss of essential diagnostic information.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".