CT dose reduction: approaches, strategies and results from a province-wide program in Quebec
Bibliographic record
Abstract
Many studies have shown a statistically significant increase of life-time risk of radiation-induced cancer from CT examinations. In this context, in Canada, the Quebec's provincial clinical center of expertise in radiation safety (CECR) has led a province-wide tour of 180 CT installations in order to: (i) evaluate the technical and functional performance of CT scanners, (ii) evaluate and improve radiation safety practices and (iii) initiate, with local teams, a CT dose optimization process. The CT tour consisted of a two day visit of CT installations by a CECR multidisciplinary team of medical physicists, engineers and medical imaging technologists (MITs) carried out in close collaboration with local teams composed of MITs, radiologists, physicists, engineers and managers. The CECR has evaluated 112 CT scanners since 2011. Optimization of CT protocols was performed in all centers visited. The average dose reduction obtained from optimization was [Formula: see text], [Formula: see text] and [Formula: see text] for adult head, thorax and abdomen-pelvis, respectively. The main recommendations often made by the CECR experts were: (1) the implementation of low-dose protocols for the follow-up of pulmonary nodules and for renal calculi, (2) the compliance to the prescribed scan range as defined by local guidelines, (3) the correct positioning of patients and (4) the use of bismuth shielding to reduce the dose to radiosensitive organs. The CECR approach to optimize CT doses to patients is based on the active participation of local stakeholders and takes into account the performance of CT scanners. The clinical requirements as expressed by radiologists remain at the core of the optimization process.
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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 | 0.001 | 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 | 0.001 |
| 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".