Breast Arterial Calcifications on Mammography: Awareness and Reporting Preferences Amongst Referring Physicians in Canada
Bibliographic record
Abstract
Purpose: Breast arterial calcifications (BAC) on mammography have been correlated with increased cardiovascular risk. The Canadian Society of Breast Imaging released a position statement on BAC reporting in January 2023. This study evaluates the awareness of the clinical significance of BAC and reporting preferences of referring physicians in Canada. Methods: A 15-question survey was distributed to Canadian physicians who may review mammography results via regional and subspecialty associations and on social media following local institutional ethical approval. Responses were collected over 10 weeks from February to April 2023. Results: Seventy-two complete responses were obtained. We are unable to determine the response rate, given the means of distribution. Only 17% (12/72) of responding physicians were previously aware of the association between BAC and increased cardiovascular risk, and 51% (37/72) preferred the inclusion of BAC in the mammography report. Fifty-six percent (40/72) indicated that BAC reporting would prompt further investigation, and 63% (45/72) would inform patients that their mammogram showed evidence of BAC. Sixty-nine percent (50/72) would find grading of BAC beneficial and 71% (51/72) agreed that there is a need for national guidelines. Conclusion: Less than a quarter of responding Canadian referring physicians were previously aware of the association between BAC and cardiovascular risk, although half of respondents indicated a preference for BAC reporting on mammography. Most participating physicians would inform their patients of the presence of BAC and consider further cardiovascular risk management. There was consensus that a national BAC grading system and clinical management guidelines would be beneficial.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".