Utilization of breast MRI and breast MRI-guided biopsy in clinical practice: results of a survey in Québec and France
Bibliographic record
Abstract
BACKGROUND: To investigate the practice regarding breast MRI exams and breast MRI-guided biopsies in two countries with different health care systems, France and Québec. A 12-item questionnaire was distributed online among radiologists from France and Québec, attempting to determine: demographic characteristics and breast MRI diagnostic and MRI-guided practices (indications, workload, availability, and waiting time assessment). RESULTS: One hundred and seventy radiologists (France, 132 respondents (28.5%); Quebec, 38 respondents (35.2%)) participated in the survey, most of them based in non-academic centers. Thirty-eight percent of Quebec and 2.3% of French radiologists did not perform breast MRI in their daily practice. Nearly 50% of French and Quebec respondents interpreted 1-10 breast MRI exams per week. Decision-making factors of preoperative MRI were similar in both countries (pathology, age, and breast density), with a heavier emphasis placed on the surgeon's opinion in Quebec (47.8% versus 21.8% (p = 0.009)). Quebec demonstrated a higher waiting time than France (1-2 weeks in 40% versus less than 1 week in 40%). MRI-guided breast biopsies (less than 5 MRI-guided biopsies per week) were being performed by a minority of the respondents (36% in France and 43% in Québec). CONCLUSION: Most of radiologists performing breast MRIs work in non-academic institutions in both countries. Waiting time is higher in Quebec, but most of preoperative breast MRIs are performed within 3 weeks in both countries. The surgeon plays an important role in recommending preoperative MRI in Quebec. MRI-guided breast biopsies are not widely available in both countries.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".