Patients effective dose estimation during AP pelvis radiography in some hospitals of Al Najaf city, Iraq
Bibliographic record
Abstract
Abstract Background: Monitoring patients radiation dose during anterior-posterior (AP) pelvis radiography is of paramount importance. This is due to the existence of the gonads within the pelvic region. Objective: The purpose of this work is to estimate effective dose (ED) for adult patients who examined for AP pelvis radiography in the governmental hospitals of Al Najaf city-Iraq. Materials and methods: The ED was estimated for 64 patients (male and female) who undertaking AP pelvis radiography using CALDOSE-X5 Monte Carlo software. The calculation of the ED was based on the measurements of X-ray tube output and the knowledge of exposure factors. The X- ray output was measured using Rad-Check ionization chamber for each X-ray tube. In total, seven X-ray tubes were enrolled to assess the patients’ ED. Exposure factors includes tube potential (kVp), tube loading (mAs) and X-ray source to image detector distance-SID (cm)); these were recorded for each patient together with their demographic data (weight(kg) and height(m)). Five major hospitals were considered in this work (i.e. Al Sadder, Al Hakeem, Al Furat, Al Manzrah and Middel Euphrates cancer center). Results: The average value of the estimated ED was ranged from 0.156±0.041 mSv to 0.4068±0.049 mSv across all hospitals. The value of max/min of the ED was ranged from 1.25 to 2.58 across different hospitals. The corresponding average values of the kVp used for this examination was ranged from 75 to 113.75 kVp; mAs: ranged from 11.7 to 42.1 mAs and for the SID the range was between 100 and 140.6 cm. Conclusion: The resulted data demonstrate there is a clear variability in patient dose and exposure factors set among the selected hospitals. The ED values were seen to be slightly lower than those reported by the UK (Survey-2010, 0.284 mSv) and were higher than those reported by certain countries (e.g. Canada, Ghana etc.). Overall, a periodic checking together with conducting a quality control testing is highly recommended.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".