Breast Cancers Detected at Screening MR Imaging and Mammography in Patients at High Risk: Method of Detection Reflects Tumor Histopathologic Results
Bibliographic record
Abstract
Purpose To compare the clinical, imaging, and histopathologic features of breast cancers detected at screening magnetic resonance (MR) imaging, screening mammography, and those detected between screening examinations (interval cancers) in women at high risk. Materials and Methods This retrospective institutional review board-approved, HIPAA-compliant review of 7519 women at high risk for breast cancer who underwent screening with MR imaging and mammography between January 2005 and December 2010 was performed to determine the number of screening-detected and interval cancers diagnosed. The need for informed consent was waived. Medical records were reviewed for age, risk factors (family or personal history of breast cancer, BRCA mutation status, history of high-risk lesion or mantle radiation), tumor histopathologic results, and time between diagnosis of interval cancer and most recent screening examination. The χ(2) test and logistic regression methods were used to compare the features of screening MR imaging, screening mammography, and interval cancers. The Wilcoxon signed-rank test was used to calculate P values. Results A total of 18 064 screening MR imaging examinations and 26 866 screening mammographic examinations were performed. Two hundred twenty-two cancers were diagnosed in 219 women, 167 (75%) at MR imaging, 43 (19%) at mammography, and 12 (5%) interval cancers. Median age at diagnosis was 52 years. No risk factors were associated with screening MR imaging, screening mammography, or interval cancer (P > .06). Cancers found at screening MR imaging were more likely to be invasive cancer (118 of 167 [71%]; P < .0001). Of the 43 cancers found at screening mammography, 38 (88%) manifested as calcifications and 28 (65%) were ductal carcinoma in situ. Interval cancers were associated with nodal involvement (P = .005) and the triple-negative subtype (P = .03). Conclusion In women at high risk for breast cancer who underwent screening with mammography and MR imaging, invasive cancers were more likely to be detected at MR imaging, whereas most cancers detected at screening mammography were ductal carcinoma in situ. Interval cancers were found infrequently and were more likely to be node positive and of the triple-negative subtype. (©) RSNA, 2016.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".