Reference dosimetry during diagnostic CT examination using XR‐QA radiochromic film model
Bibliographic record
Abstract
PURPOSE: The authors applied 2D reference dosimetry protocol for dose measurements using XR-QA radiochromic film model during diagnostic computed tomography (CT) examinations carried out on patients and humanoid Rando phantom. METHODS: Response of XR-QA model GAFCHROMIC™ film reference dosimetry system was calibrated in terms of Air-Kerma in air. Four most commonly used CT protocols were selected on their CT scanner (GE Lightspeed VCT 64), covering three anatomical sites (head, chest, and abdomen). For each protocol, 25 patients ongoing planned diagnostic CT examination were recruited. Surface dose was measured using four or eight film strips taped on patients' skin and on Rando phantom. Film pieces were scanned prior to and after irradiation using Epson Expression™ 10000XL document scanner. Optical reflectance of the unexposed film piece was subtracted from exposed one to obtain final net reflectance change, which is subsequently converted to dose using previously established calibration curves. RESULTS: The authors' measurements show that body skin dose variation has a sinusoidal pattern along the scanning axis due to the helical movement of the x-ray tube, and a comb pattern for head dose measurements due to its axial movement. Results show that the mean skin dose at anterior position for patients is (51 ± 6) mGy, (29 ± 11) mGy, (45 ± 13) mGy and (38 ± 20) mGy for head, abdomen, angio Abdomen, and chest and abdomen protocol (UP position), respectively. The obtained experimental dose length products (DLP) show higher values than CT based DLP taken from the scanner console for body protocols, but lower values for the head protocol. Internal dose measurements inside the phantom's head indicate nonuniformity of dose distribution within scanned volume. CONCLUSIONS: In this work, the authors applied an Air-Kerma in air based radiochromic film reference dosimetry protocol for in vivo skin dose measurements. In this work, they employed green channel extracted from the scanned RGB image for dose measurements in the range from 0 to 200 mGy. Measured skin doses and corresponding DLPs were higher than DLPs provided by the CT scanner manufacturer as they were measured on patients' skin.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".