Radiation exposure in prone vs. modified supine position during percutaneous nephrolithotomy: Results with an anthropomorphic model
Bibliographic record
Abstract
INTRODUCTION: Radiation exposure during urological procedures is still of concern in the urology community. It has been reported that percutaneous nephrolithotomy (PCNL) in supine position has less irradiation, as the puncture is mostly done under ultrasound guidance. However, it can also be done under fluoroscopy guidance. Unfortunately, data on radiation exposure during PCNL is lacking since they are often drawn from generalization and extrapolation, or they do not evaluate new procedures or different positions. The aim of our study was to compare the radiation dose depending on the position of the surgeon during PCNL. METHODS: A portable C-arm was used in standard mode (32 impulsions/second; 98 kV, 3.8 mA). Specific dosimeters were placed for lens, extremity, and torso. Anthropomorphic models and hand phantom models were used to reproduce the position of surgeon and patient (with same bone density as human) during PCNL in prone and modified supine position. Fluoroscopy time (FT) was six minutes to obtain higher exploitable signal, and the results are given for a FT of three minutes (more realistic). Ten percent of the FT is done with an angulation of 15 degrees and the rest in anteroposterior position. RESULTS: The equivalent doses (ED) are given in uSV (uncertainty k=2). During the modified supine position: neck, lens, right index finger, left thumb, and index finger received EDs of 99 (20%), 62 (18%), 437 (10%), 112 (12%), and 204 (10%), respectively. In a prone position, the phantom received ED on the neck, lens, right thumb and index finger, left thumb and index finger of 85 (20%), 92 (12%), 401 (10%), 585 (10%), 295 (10%), and 567 (10%), respectively. In both positions, the right hand seems more exposed than the left hand. CONCLUSIONS: The effective dose is 1.5- and 1.3-fold higher for lens and extremities, respectively, in prone position PCNL compared to modified supine position. Both positions are still well below the recommended limit for professional exposure.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".