Sonographic Features of Breast Carcinoma Presenting as Masses in<i>BRCA</i>Gene Mutation Carriers
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to review the sonographic features of breast cancer gene BRCA1- and BRCA2-associated breast carcinomas in comparison with "sporadic" breast carcinomas and benign breast masses. METHODS: Sonograms of 233 breast masses, including 33 BRCA-associated malignant masses (BRCA1, 15; BRCA2, 18), 148 sporadic malignant masses, and 52 benign masses, were reviewed by consensus by 2 radiologists according to American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) terminology. RESULTS: Most of the sporadic and BRCA1-and BRCA2-associated cancers displayed an irregular shape (91.2%, 93.3%, and 83.3%, respectively). BRCA1-associated cancers showed microlobulated margins in 53.3% versus 33.8% (sporadic) and 33.3% (BRCA2). A parallel orientation was most frequently encountered in BRCA1-associated lesions (46.7%) versus sporadic (33.8%) and BRCA2 (33.3%), whereas posterior acoustic shadowing was least frequently seen in BRCA1-associated lesions (13.3%) versus BRCA2 (16.7%) and sporadic (31.1%). Most (73.3%) of the BRCA1-associated lesions were classified as BI-RADS category 4, whereas most of the sporadic and BRCA2-associated lesions were classified as BI-RADS category 5 (66.2% and 72.2%). CONCLUSIONS: Sonographic features of BRCA-associated and sporadic breast carcinomas do not differ substantially. BRCA1-associated breast carcinomas trend toward less malignant sonographic characteristics, but strict application of the BI-RADS categorizations demands that they be classified as category 4 or 5.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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".