PEDIATRIC REGIONAL DRL ASSESSMENT IN COMMON CT EXAMINATIONS FOR MEDICAL EXPOSURE OPTIMIZATION IN TEHRAN, IRAN
Bibliographic record
Abstract
The main purpose of this pilot study was to assess the regional diagnostic reference level (RDRL) of computed tomography (CT) examinations to optimise medical exposure in five pediatric medical imaging centers in Tehran, Iran where the most frequent CT examinations were investigated. For each patient, CT volume dose indexes (CTDIvol) and dose length product (DLP) in each group were recorded and their third quartile was calculated and set as RDRL. Pediatrics were divided into four age groups (<1; 1-5; 5-10 and 10-15 years). Then, the third quartile values for head, chest and abdomen-pelvic CTs were, respectively, calculated for each group in terms of CTDIvol: 21.3, 24.4, 24.2 and 36.3 mGy; 2.9, 3.2, 3.7 and 5.7 mGy; 3.7, 5.7, 6.3 and 6.8 mGy; and in terms of DLP: 322.2, 390.1, 424.9 and 694.1 mGy.cm; 53.1, 115.2, 145.3 and 167.6 mGy.cm and 128.7, 317.7, 460.2 and 813.8 mGy.cm. Finally, RDRLs were compared with other countries and preceding data in Iran. As a result, CTDIVOL values were lower than other national and international studies except for chest and abdomen-pelvic values obtained in Europe. Moreover, this matter applied to DLP so that other formerly reported values were higher than the present study but European values for chest and abdomen-pelvic scans and also Tehran studies conducted in 2012. Variation of scan parameters (tube voltage (kVp), tube current (mAs) and scan length), CTDIvol and DLP of different procedures among different age groups were statistically significant (P-value < 0.05). The variations in dose between CT departments as well as between identical scanners suggest a large potential for optimization of examinations relative to which this study provides helpful data.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".