SU-D-103-05: Radiochromic Film Based System for CTDI Measurements
Bibliographic record
Abstract
Purpose: We demonstrate a new method for computed tomography dose index (CTDI) measurements performed on CT scanners using XR-QA model radiochromic film dosimetry system. Method was tested by comparing measured to CT scanner listed CTDI values for fifteen different CT scanners at various locations. Methods: Reference dosimetry system was calibrated in terms of air kerma in air. Dose profiles were measured with XR-QA2 radiochromic film strips, sandwiched between acrylic rods cut in half and placed within CTDI phantoms. Film strips were scanned before and after irradiation with Epson Perfection V500 scanner in reflective mode. Reflectance change was measured using red color channel from TIFF images of scanned films and it was converted into air kerma in air using calibration curves. Measured air kerma in air was subsequently converted into absorbed dose to water following AAPM TG-61 protocol. We also investigated the impact of scan length by scanning CTDI phantom 5, 10, and 15 cm longitudinally. Results: Average doses along profiles from each film piece were used to calculate weighted CTDIvol. Average difference for the first 10 scanners between calculated and listed CTDIvol was 21.8% for Head and 10.4% for Body protocol. Our study also showed that as the scanning length was increasing, the difference between measured and tabulated CTDIvol decreased. For the last 5 CT scanners, the scanning length of 5-10 cm was changed to 15 cm for both Head and Body scanning protocols, resulting in average difference between measured and tabulated CTDIvol values of 3.8% for Head and 9.4% for Body scanning protocol. Conclusion: In contrast to ionization chamber measurement, the proposed method requires only a single exposure, does not need stem effect correction, and provides an acceptable accuracy when compared to CT scanner listed CTDIvol values. It also measures dose profiles allowing measurements of DLP and peak doses.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".